NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

Technical Report

NREL/TP-6A20-72345

April 2019

Cross-Border Energy Trade between 

Nepal and India: Trends in Supply 

and Demand

David J. Hurlbut

National Renewable Energy Laboratory
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Technical Report

NREL/TP-6A20-72345

April 2019

Cross-Border Energy Trade between 

Nepal and India: Trends in Supply 

and Demand

David J. Hurlbut

National Renewable Energy Laboratory

Prepared under State Department Agreement No. IAG-16-02007

Suggested Citation 

Hurlbut, David J.. 2019. Cross-Border Energy Trade between Nepal and India: 

Trends in Supply and Demand. Golden, CO: National Renewable Energy Laboratory.

NREL/TP-6A20-72345. https://www.nrel.gov/docs/fy19osti/72345.pdf. 
NOTICE

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable 

Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding 

provided by U.S. Department of State. The views expressed herein do not necessarily represent the views of the 

DOE or the U.S. Government.

This report is available at no cost from the National Renewable 

Energy Laboratory (NREL) at www.nrel.gov/publications.

U.S. Department of Energy (DOE) reports produced after 1991 

and a growing number of pre-1991 documents are available 

free via www.OSTI.gov.

Cover Photos by Dennis Schroeder: (clockwise, left to right) NREL 51934, NREL 45897, NREL 42160, NREL 45891, NREL 48097, 

NREL 46526.

NREL prints on paper that contains recycled content.
iii

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Preface

This paper is part of a series of studies on the opportunities for—and associated value of—

increased power trade in the South Asian region, including India, Nepal, Bhutan, Bangladesh, 

and Sri Lanka. This work is supported by the U.S. Department of State’s Bureau of South and 

Central Asian Affairs Regional Connectivity Program. 

Another study in this series uses production cost modeling to quantify potential cross-border 

energy trading benefits more thoroughly, based on scenarios derived from the economic analysis 

in this study. The third study uses the economic and production cost analyses to explore

regulatory issues that could affect cross-border electricity trade. The results reflect input from 

power system engineers, planners, regulators, and electricity developers as part of stakeholder 

engagement under the U.S. Agency for International Development’s South Asia Regional 

Initiative for Energy Integration.
iv

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

Acknowledgments

The author is grateful for operational data, advice, and comment from the Nepal Electricity 

Authority, especially from Kulman Ghising, Rabindra Raj Shrestha, Shaligram Acharya, 

Hitendra Dev Shakya, Bishnu Prasad Shrestha, and Binod Lohani. U.S. Embassy staff—

particularly Kevin Price—also provided invaluable logistical assistance during in-country visits 

to Nepal, as did Michael Boyd and Shanker Khagi from the U.S. Agency for International 

Development’s Nepal Mission. 

Troy Kofroth of the Millennium Challenge Corporation and S.K. Soonee of the Power System 

Operation Corporation of India provided important feedback on initial drafts of this report. Nate 

Blair, Jaquelin Cochran, Jeff Logan, Brendan McBennett, David Palchak, and Amy Rose of the 

National Renewable Energy Laboratory (NREL) provided important detailed review comments. 

Donna Heimiller of NREL provided geographic information systems support. 
v

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

List of Acronyms

CBA cost-benefit analysis

CBET cross-border energy trading

GIS geographic information systems

IEX Indian Energy Exchange

IPP independent power producer

LMP locational marginal price

PCM production cost modeling

PPA power purchase agreement

NEA Nepal Electricity Authority

NREL National Renewable Energy Laboratory

RLDC Regional Load Dispatch Center

RoR run-of-river

VOLL value of lost load

WECS Water and Energy Commission Secretariat
vi

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Executive Summary

This report examines the economic factors affecting cross-border energy trading (CBET) 

between Nepal and India. Its objective is to identify market factors and institutional issues that 

are most likely to affect the usefulness of infrastructure investments aimed at maximizing the 

benefits of CBET. The analysis assesses supply and demand characteristics by examining hourly 

load data, pricing data, generation capacity, tariffs, and historical CBET flows. It uses 

Government of Nepal load forecasts, planned capacity additions, and historical trends for 

construction delays to project plausible trajectories of shortages and surpluses in domestic 

generation.

A 2017 study for the South Asian Regional Initiative for Energy Integration concluded that 

Nepal, which generates nearly all of its domestic power from hydroelectric resources, could reap 

significant economic benefits by expanding CBET with India (SARI/EI and IRADe 2017). 

Strategic transmission expansion could affect how much of these latent benefits are actually 

achieved, however. In turn, the effectiveness of different transmission expansion options could 

depend on domestic economic conditions and how they might change over time.

Figure ES 1 shows the key interconnection points between the two countries’ grids. Supply and 

demand on both sides of the Indo-Nepalese border will affect which points have the greatest 

potential for maximizing CBET benefits. The aim of this economic analysis is to understand 

trends in supply, demand, and prices, and to identify which transmission corridors have the best 

potential for benefiting both countries.

Figure ES 1. Major CBET interconnections between Nepal and India.

Note: The Dhalkebar-Muzzafarpur connection would repower the existing line from 132 kilovolts (kV) to 400 kV, 

requiring no additional right-of-way.

The economic analysis supports four major conclusions:

• Up to 2018 the primary driver for CBET has been the alleviation of load shedding in 

Nepal, but the completion of new generation will most likely reduce load shedding and 

Nepal’s need to import power from India for that purpose. Future CBET in both 

directions will likely depend on the cost of alternative generation sources in each country. 
vii

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

• Market fundamentals and longer-term trends appear to favor connections to India’s 

Northern Regional Load Dispatch Center (RLDC) region, which tends to be a net 

importer of electricity. Upgrading the Butwal-Gorakhpur path is consistent with this 

likely value proposition.

• While connections across the Western Tarai area could further increase mutually 

beneficial CBET opportunities, doing so could depend on system upgrades within Nepal 

to increase the capacity to move power west of the Butwal flowgate.

• Maximizing the value of any new transmission intended to enhance CBET value will 

likely depend on bilateral tariff reform and greater operational coordination between 

Nepal and India.

The results of this economic analysis help characterize regional grid scenarios for 2022 that are 

simulated with production cost modeling, which is the focus of the companion paper in this 

series, “Cross-Border Energy Trade between Nepal and India: Assessment of Trading 

Opportunities” (McBennett et al. 2019). These technical simulations provide additional detail on 

the regional distribution of benefits. 
viii

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table of Contents

Executive Summary................................................................................................................................... vi

1 Introduction........................................................................................................................................... 1

2 Planning Principles for CBET and Transmission.............................................................................. 3

2.1 Scenario Development .................................................................................................................. 3

2.2 Cost-Benefit Analysis ................................................................................................................... 4

3 Market Factors Affecting CBET Transmission Use .......................................................................... 6

3.1 Supply and Demand ...................................................................................................................... 7

3.2 Demand Patterns ........................................................................................................................... 9

3.3 Prices........................................................................................................................................... 11

3.4 Existing Energy Trading ............................................................................................................. 15

3.5 Impact of Load Shedding on the Value of Imports..................................................................... 16

3.6 Eastern Tarai CBET .................................................................................................................... 20

Major Bilateral Project: Arun 3.................................................................................................. 22

3.7 Western Tarai CBET................................................................................................................... 22

Major Bilateral Project: Upper Karnali....................................................................................... 23

3.8 Discussion ................................................................................................................................... 25

4 Variations in Construction Costs...................................................................................................... 28

4.1 Terrain Assessment ..................................................................................................................... 28

4.2 Methodology and Results............................................................................................................ 29

5 Production Cost Modeling................................................................................................................. 31

5.1 Fundamentals .............................................................................................................................. 31

5.2 Questions To Be Addressed with PCM....................................................................................... 32

References................................................................................................................................................. 34

Appendix: Exchange Rates Applied to the Analysis............................................................................. 36
ix

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

List of Figures

Figure ES 1. Major CBET interconnections between Nepal and India ....................................................... vi

Figure 1. Geographic alignment of significant grid regions in Nepal and India........................................... 6

Figure 2. Distribution of 2016–2017 electricity sales in Nepal by region and customer type...................... 8

Figure 3. One-year time series of daily peak generation delivered to load in Nepal.................................. 10

Figure 4. Three-year time series of daily peak and minimum load in India. .............................................. 10

Figure 5. Monthly IEX prices and power flows across the Eastern Tarai CBET ....................................... 12

Figure 6. Monthly power flows across Western Tarai CBET..................................................................... 12

Figure 7. Price duration curves for Uttar Pradesh and Bihar...................................................................... 13

Figure 8. Same-hour price differences between Uttar Pradesh and Bihar .................................................. 13

Figure 9. Monthly generation for Nepal, by resource type ......................................................................... 17

Figure 10. Short-term projection of supply and served load for test hour .................................................. 18

Figure 11. Daily load profiles for Bihar, by month..................................................................................... 21

Figure 12. Daily load profiles for Uttar Pradesh, by month........................................................................ 24

Figure 13. Map of major CBET interconnections....................................................................................... 28

Figure 14. Geospatial analysis of areas around CBET points..................................................................... 29

List of Tables

Table 1. Daily Profiles of Nepal’s Electricity Generation, by Nepali Calendar Month................................ 7

Table 2. India's Northern and Eastern Load Dispatch Center Regions, Year Ending April 2017 ................ 9

Table 3. Prices Paid by NEA for Energy from New Merchant Generators................................................ 11

Table 4. Market Prices for Day-Ahead Exchanges in Bihar and Uttar Pradesh, by Month........................ 14

Table 5. Distribution of Nepal’s Electricity Imports, by Month................................................................. 15

Table 6. Domestic Generation Available for Critical Load Shedding Hours in Nepal............................... 18

Table 7. Land Classification System........................................................................................................... 29

Table 8. Scoring of CBET Points Based on Geospatial Attributes............................................................. 30
1

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

1 Introduction

Electricity demand on both sides of the border between Nepal and India is growing rapidly, 

increasing the urgency of infrastructure planning and development. This report draws on 

international experience to develop a framework for transmission planning specifically aimed at 

prioritizing opportunities for increasing cross-border energy trading (CBET) along the IndoNepalese border. 

The severe earthquake and aftershocks that devastated the Kathmandu Valley and central Nepal 

in mid-2015 complicate any time series analysis of electricity demand and production in the 

country. For this reason, this report focuses generally on the Nepalese calendar year beginning 

April 13, 2016 (1 Baishakh 2073) as the start of the country’s post-earthquake redevelopment 

period.1 This time frame allows at least one full reporting year of operational data from the 

Nepal Electricity Authority (NEA). The preceding year was dominated by extraordinary 

economic disruption and one-time emergency response, so much as to reduce confidence in 

including observations for that year in an analysis of future economic trends. 

Moreover, Nepal’s constitutional and political framework in the post-earthquake period is 

substantially different from what it was before the disaster. This could affect Indo-Nepalese 

CBET in two important ways relevant to this report. First, Nepal’s infrastructure planning could 

follow a strategy that is significantly different from pre-2015 planning. A change in strategy 

could affect investment in new large-scale hydropower projects, as well as national strategies for 

dealing with domestic issues such as dry-season load shedding and the course of post-earthquake 

economic growth. Second, in many cases Indo-Nepalese CBET currently adheres to pre-2015 

bilateral arrangements that are unconnected to power market economics. One important question 

that the governments of Nepal and India might consider is whether to replace or amend these 

pre-2015 agreements with institutions that are more market-oriented. Much of the analysis 

contained in this report assumes that CBET can adapt to changing market conditions. 

Efficiently implemented CBET expands the electric system’s operational footprint. Numerous 

studies—as well as experience in several countries—demonstrate the value of greater integration 

over a larger geography. The benefits include lower cost of scheduling and dispatch, reduced 

area control error, a greater selection of resources for balancing, greater operational flexibility, 

and lower cost of renewable energy integration. For example, the introduction of a regional, 

multi-jurisdiction market for settling energy imbalances has saved utilities in the western United 

States more than $400 million (Indian rupees 2,850 crore) since it began in 2014. That market 

includes one large system operator that accounts for about 60% of the group’s total demand, and 

five smaller control areas. Of the $71 million (Indian rupees 458 crore) in benefits seen in the 

second quarter of 2018, more than 61% accrued to the smaller control areas (CAISO 2018). 

CBET is not an exercise separate from all other transmission planning. On both sides of the 

border, electricity planning addresses larger objectives and requires comprehensive power 

system planning. CBET might add to the range of options for achieving economically efficient 

 

1 The Indian civil calendar year and the Nepali year do not completely align but are reasonably close enough for 

aggregating data. For the Gregorian calendar year 2016, the month Vaishakha on India’s calendar began six days 

after 1 Baishakha on the Nepali calendar. 
2 

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

electricity service to all, but it is not a goal by itself. What makes CBET a special category of

system planning is the need for collaboration and joint planning across national boundaries. Joint 

planning ensures that assumptions about CBET and what it can accomplish are consistent. This 

enhances the quality of each country’s own planning and can expand options for achieving 

domestic goals.

This report begins with an overview of multi-jurisdictional transmission planning in other world 

power markets. Rather than provide an exhaustive literature review, the aim is to distill best 

practices to a select number of key principles that can guide joint planning by India and Nepal. 

Among the most important of these principles is the need to create transparency by involving key 

stakeholders. 

The report then examines the most important market factors that will influence the value of 

CBET at different points along the border. The report concludes with a summary of the specific 

questions arising from the economic analysis that production cost modeling can help address. 

This economic analysis informs the scenarios modeled in the companion study, “Cross-Border 

Energy Trade between Nepal and India: Assessment of Trading Opportunities” (McBennett et al. 

2019). 

The modeling results, along with the economic analysis in this report, will provide the basis for 

an examination of regulatory, planning, and operational changes that might improve 

opportunities for CBET. 
3

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2 Planning Principles for CBET and Transmission 

Multi-jurisdiction regional transmission operators around the world rely on formal, transparent 

planning processes to prioritize investments in new transmission infrastructure.2 These processes 

are tailored to the needs of each particular market, but many have common aims, such as:

• Minimizing total electric system costs

• Meeting all reliability standards

• Supporting government policies in the most economically efficient manner

• Allocating the cost of transmission investments in a way that matches the distribution of 

benefits.

Systematic planning is even more important when the grid spans multiple jurisdictions, each with 

its own decision-making authority. A transparent planning process allows all participants to 

evaluate a wide variety of options, test theoretical benefits against practical limitations, and 

identify strategies that benefit everyone. In many jurisdictions, planning is done over a moving 

5-, 10- or 20-year time horizon, updated every 1 or 2 years. This allows for full consideration of 

known plant retirements, the online dates of plants currently under construction, and load 

growth.

In planning transmission for CBET between India and Nepal, this study draws on two tools: 

scenario development and cost-benefit analysis (CBA). This section provides a basic explanation 

of both tools. The economic analysis in Section 3 will help define scenarios around which 

transmission analysis can be framed. The production cost modeling (PCM) described in Section 

3.8 and the construction factors modeled in Section 4 will provide CBA inputs. 

2.1 Scenario Development

Scenario analysis is a planning exercise that anticipates long-term structural changes to the 

economy at large. It is particularly useful for countries anticipating major economic transitions. 

Scenarios could include significantly greater use of electric vehicles, changes in energy imports 

or exports, and shifts in personal consumption patterns, as well as adoption of policies aimed at 

 

2 For example, the U.S.-based Midcontinent Independent System Operator uses the following principles in its multiyear transmission expansion planning:

• Make the benefits of an economically efficient electricity market available to customers by identifying 

transmission projects that provide access to electricity at the lowest total electric system cost.

• Develop a transmission plan that meets all applicable [government and] transmission owner planning 

criteria and safeguards local and regional reliability through identification of transmission projects to meet 

those needs.

• Support state and federal energy policy requirements by planning for access to a changing resource mix.

• Provide an appropriate cost allocation mechanism that ensures that costs of transmission projects are 

allocated in a manner roughly commensurate with the projected benefits of those projects.

• Analyze system scenarios and make the results available to state and federal energy policy makers and 

other stakeholders to provide context and to inform choices.

• Coordinate planning processes with neighbors and work to eliminate barriers to reliable and efficient 

operations.
4

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

increasing CBET. Potential scenarios that could be particularly relevant to cross-border 

transmission projects for India and Nepal might include:

• Institutional reform. Replacing administrative rules with markets can affect the size of 

economic benefits as well as how those benefits are distributed. Reform scenarios can 

range from modest changes such as bilateral spot markets to major changes such as the 

creation of an independent system operator and security-constrained economic dispatch.

• Rural electrification. The pace and geographic characteristics of grid-connected rural 

electrification can affect both the quantity of electricity needed and the points of 

congestion on the transmission system.

• Industrialization and accelerated economic growth. Economic development that 

accelerates industrial and commercial electricity consumption can affect the system’s 

ability to use demand response as a tool for maintaining reliability and reducing peak 

load. This is especially important if either country has renewable energy goals.

• Plant retirements and additions. Replacing old thermal plants can change the total cost 

of generation and—depending on the size of the plants—congestion on the transmission 

system. 

The number of potential scenarios that could be modeled is large. Therefore, the goal of Section 

3 is to narrow the list of useful scenarios to focus on factors that could have a large economic 

impact across the region based on conditions that can be observed and measured using data that 

are currently available for this project. Future analyses can examine scenarios that are not tested 

here.

Sensitivity analyses test the robustness of conclusions to changes in external variables such as 

fuel prices and load growth. Sensitivities that span a range of plausible future conditions enable 

identification of “no regrets” solutions: investments that provide additional value to society 

regardless of how key factors might change.

2.2 Cost-Benefit Analysis

Transmission planners typically use CBA to compare the net economic effect of build-out 

proposals. CBA compares the cost of a new transmission project with its predicted economic 

benefits, summarized as a cost-benefit ratio:

cost-benefit ratio = ∑ benefits i i

transmission project costs

where i is a specific type of economic change attributable to the new line, such as lower 

systemwide variable cost of generation, increase or decrease in the amount of operating reserves 

needed, or a change in the expected amount of unserved energy. The components may be 

estimated over the economic life of the investment on a net present value basis or may be 

levelized to annual values.3

 

3 A net present value approach allows for costs or benefits to vary from one year to another.
5

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

The denominator includes only the direct cost of building the transmission project. Any other 

non-project cost is included in the numerator as a “benefit” with a negative value. For example, a 

new transmission line to a wind power development zone could reduce total production costs (a 

positive benefit) but might also increase the amount and cost of operating reserves needed to 

ensure reliability (a negative benefit). The numerator would account for both; the cost-benefit 

ratio would compare the aggregation of all benefits—positive and negative—against the 

project’s direct cost.

A cost-benefit ratio greater than 1.0 indicates that the estimated benefits of a transmission project 

are greater than its cost. Regulatory authorities may set decision benchmarks to guide 

transmission planning. In the United States, for example, some authorities give greater weight to 

a proposed transmission project if the cost-benefit ratio is larger than 1.25 (FERC 2011).
6

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3 Market Factors Affecting CBET Transmission Use 

Future market conditions will ultimately govern whether any new transmission line is used and 

useful. This section describes market conditions observed through NEA operational data, factors 

likely to affect forward trends, and how these trends might affect the prioritization of CBET 

transmission expansion options.

The Indo-Nepalese border touches four distinct power markets. As the map in Figure 1

illustrates, these four areas align somewhat geographically into two potential CBET areas: 

• The Western Tarai, comprising power flows between western Nepal and India’s Northern 

Regional Load Dispatch Center (RLDC) region

• The Eastern Tarai, comprising power flows between the rest of Nepal and India’s Eastern 

RLDC region. 

Internal east-west flows are limited on both sides of the border. This suggests that each northsouth CBET path could have its own economic dynamics, making it reasonable to treat them 

separately. Differences include energy pricing patterns, seasonal demand, and the value of 

economically driven trades in both directions. These in turn could affect the value of new 

transmission across each CBET area.

Butwal is a pivotal point on Nepal’s power grid. A 132-kV substation constitutes the sole 

flowgate to the country’s western system. What makes Butwal especially strategic for CBET is 

its ability to connect to Uttar Pradesh and India’s Northern RLDC region via Gorakhpur. Both 

countries have identified a future 400-kV line between Butwal and Gorakhpur as a bilateral 

priority (GoI/GoN 2017). 

Figure 1. Geographic alignment of significant grid regions in Nepal and India

132 kV flowgate 

between western, 

eastern networks

•

Butwal

Kathmandu

Northern RLDC Area Eastern RLDC Area

•

Gorakhpur
7

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3.1 Supply and Demand 

NEA had 526 megawatts (MW) of generating capacity in 2017, 90% of which was hydropower

(NEA 2017a). Less than 1% of NEA’s capacity is located west of Butwal.4 Independent power 

producers (IPPs) had about 441 MW of capacity, with only 32 MW operating west of Butwal. 

Developers currently have nearly 2 gigawatts (GW) of new capacity financed and under 

construction, with 5% of that total west of Butwal (NEA 2017c).

Due to its high reliance on run-of-river (RoR) hydropower, Nepal’s domestic generation 

resources produce the most power during the post-monsoon months from Bhadra to Kartik (late 

August to early November). Table 1 shows the temporal distribution of Nepal’s domestic 

generation for 2016–2017, averaged by hour for each month. 

Figure 2 shows the geographic distribution of power sales in Nepal for the 12 months ending 

April 12, 2017. The Western Tarai (points west of Butwal) constitutes about 10% of NEA sales, 

while the Butwal area itself accounts for about 14% (NEA 2017a). 

Table 1. Daily Profiles of Nepal’s Electricity Generation by Nepali Calendar Month

(April 13, 2016 through April 12, 2017, averaged by month)

BaishakhJesthaAsadhShrawanBhadraAshwinKartikMangsirPoushMaghFalgunChaitra

Hour of operating day

24 341 357 462 473 536 553 551 447 325 273 304 320

23 355 366 470 477 530 558 557 463 347 307 321 342

22 338 365 494 500 555 565 571 498 396 367 367 372

21 340 365 478 490 554 572 588 534 453 422 422 421

20 326 358 464 478 555 576 597 550 483 446 454 470

19 321 341 456 472 555 574 600 575 522 493 501 499

18 281 329 458 467 550 573 606 598 540 445 470 371

17 296 336 451 462 551 562 582 517 414 336 380 356

16 322 346 450 464 543 561 574 532 421 352 389 372

15 324 348 442 456 532 557 563 526 428 347 399 380

14 287 346 445 449 533 552 553 527 428 349 397 386

13 285 343 447 459 543 557 565 526 432 351 399 382

12 288 341 446 463 539 558 571 528 439 372 414 408

11 287 339 451 472 541 556 578 540 462 399 431 423

10 284 340 448 474 551 570 585 552 474 407 443 416

9 263 341 453 480 547 569 587 554 486 415 455 410

8 237 334 451 480 551 574 591 561 503 439 470 427

7 251 332 453 478 552 569 598 565 487 410 452 406

6 278 337 451 475 543 571 594 539 420 344 392 359

5 277 332 454 467 550 558 573 478 349 289 329 327

4 284 334 454 463 545 553 553 442 318 265 300 302

3 300 337 452 467 543 549 547 432 308 259 292 300

2 308 337 455 463 542 553 547 432 310 261 295 309

1 321 350 464 470 538 552 552 442 312 264 293 303

Source: NEA 2017b

 

4 This excludes about 4.5 MW of isolated hydro capacity.
8

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 2. Distribution of 2017–2018 electricity sales in Nepal by region and customer type.

Source: NEA 2018.

Note: GWh = gigawatt hour.

Domestic demand has been slightly higher than industrial demand for the past 10 years (NEA 

2017a and 2018). For the year ending April 2018, 43% of NEA’s sales were to domestic 

customers and 38% were to industrial customers. Nearly 73% of Nepal’s industrial demand is 

concentrated near Hetauda, Butwal, and Biratnagar. This geographic distribution has 

implications for load interruption. In other world markets, industrial consumers are major 

participants in strategies such as interruptible tariffs and demand response. Therefore, loadshedding strategies that focus on industrial load would tend to have a larger impact on the 

Eastern Tarai CBET area. 

The geographic division in India is defined by grid operations. India’s national power grid 

includes two dispatch center regions that are adjacent to Nepal. Uttar Pradesh, bordering western 

Nepal, is the state with the largest load in the Northern RLDC region. The Eastern RLDC region 

borders Nepal through the state of Bihar.

Hetauda

Janakpur

Nepalganj

Attariya

Pokhara

Butwal

Biratnagar

Kathmandu
9 

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

Table 2. India's Northern and Eastern Load Dispatch Center Regions, Year Ending April 2017

Northern RLDC Eastern RLDC

Effective capacity (2017) 75.1 GW

(36% hydro, other renewables) 

37.1 GW

(16% hydro)

Annual energy met (2016–2017) 345.4 TWh 134.1 TWh

Net energy flow between regions

← 20.1 TWh ←

(to Northern RLDC

from Eastern RLDC)

Source: POSOCO 2017a and 2017b, CEA 2016a and 2016b. 

Note: “Effective capacity” is the total installed capacity by technology adjusted by the most recent applicable all-India 

forced outage rates reported by India’s Central Electricity Authority. TWh = terawatt hour. 

Table 2 contrasts supply and demand for the two RLDC regions. The Northern region has twice 

as much generating capacity but more than two and a half times the energy demand. Net exports 

from the Eastern region to the Northern region were equivalent to 15% of the total energy met in 

the Eastern region for the year ending March 2017. These patterns indicate that India is not a 

homogeneous market with respect to future CBET. Based on 2017 conditions, India’s Northern 

regional network connecting to the Western Tarai appears to have a relatively stronger appetite 

for imports that is fairly consistent throughout the year. The Eastern regional network connecting 

to the Eastern Tarai has been an exporter historically, but this could change as India adds more 

renewable resources in Rajasthan and elsewhere.5

3.2 Demand Patterns

Daily and seasonal load patterns can affect the direction, quantity, and value of cross-border 

exchanges. Patterns may be complementary (higher demand on one side of the border coinciding 

with surplus supply on the other side), or they may be parallel and result in more intense 

competition for scarce resources at particular times. 

Figure 3 and Figure 4 suggest load patterns on the Nepali and Indian sides of the Eastern Tarai 

CBET area are somewhat similar. Daily peak demand tends to occur shortly after sunset, both in 

Bihar and Nepal. The coincidence of peak demand could result in competition for cross-border 

supplies that would tend to be strongest in the early evening. If this pushes wholesale market 

prices higher, the direction and volume of CBET would depend on the cost of each side’s 

domestic supply alternatives that are on the economic margin in the early evening hours. For 

example, if greater competition causes on-peak power prices across the Eastern Tarai to increase 

to $50/megawatt hour (MWh), the economic benefit of cross-border exchanges to India would 

depend on whether adding more of India’s own domestic resources would cost it more than 

$50/MWh. 

5 The additional wind and solar capacity allows the Northern RLDC region to replace its imports from the Eastern

region with generation from states such as Rajasthan that have abundant wind and solar resources. These scenarios 

are modeled in McBennett et al. 2019. 
10

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 3. One-year time series of daily peak generation delivered to load in Nepal.

Source: NEA 2017b.

Note: Chart does not quantify load shedding. Orange markers indicate the time of peak demand during load 

shedding, but not the amount of demand.

Uttar Pradesh Bihar

▲ Peak load hour of the day

▲ Minimum load hour of the day

Sunset 

Sunrise

Length of day

Figure 4. Three-year time series of daily peak and minimum load in India.

Source: POSOCO 2017a and 2017b.
11

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Peak-hour trends in Uttar Pradesh are more distributed, which tends to make the state’s demand 

for imports more consistent throughout the day. On the other side of the Western Tarai, demand 

in Nepal is about 0.1% of demand in the Northern RLDC region and too small to provide any 

significant economic counterbalance. This suggests that the economic success of new large-scale 

generation in western Nepal might follow market conditions in India more than those in Nepal.

3.3 Prices

NEA pays domestic power producers more for energy delivered during the dry season than for 

energy delivered during the rainy season, with an additional premium based on energy delivered 

during peak load hours (NEA 2017d). 

RoR generators generally receive $81.75 per MWh for energy delivered during the dry season 

and $46.72 for energy delivered during the rest of the year. Peaking RoR generators can receive 

as much as $102.68 per MWh if they deliver at their rated capacity four to six hours during the 

peak period of the day. Table 3 shows the tariff schedule for NEA payments to merchant 

generators.

The domestic payment rates influence CBET because they set the economic benchmark for 

future power exports to India. For example, if market prices in Bihar during the dry season are 

less than $46.72, IPPs will export little or no energy from Nepal if they can sell to NEA.

Table 3. Prices Paid by NEA for Energy from New Merchant Generators

Dry Season Wet Season

Peaking run-of-river hydro

4–6 hours at peak $102.68/MWh 

$46.72/MWh

(all run-of-river types,

all hours)

3–4 hours at peak $91.48/MWh 

2–3 hours at peak $85.64/MWh 

1–2 hours at peak $82.73/MWh 

Simple run-of-river hydro $81.75/MWh 

Source: NEA 2017d.

Note: Rates escalate 3% per year for 8 years.

Most of the energy currently imported into Nepal across the Eastern Tarai is under a power 

purchase agreement (PPA) with NTPC Vidyut Vyapar Nigam, which manages cross-border 

activity for India’s government-owned NTPC Ltd.6 The PPA rate is about $56/MWh (NEA 

2017a). Energy imported into Nepal across the Tanakpur-Mahendranagar line is under a PPA 

with PTC India Ltd. at a rate of about $53/MWh (NEA 2017a). 

 

6 The Government of India holds a 75% interest in NTPC.
12

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 5. Monthly IEX prices and power flows across the Eastern Tarai CBET.

Source: IEX 2017, POSOCO 2017a.

Figure 6. Monthly power flows across Western Tarai CBET.

Source: IEX 2017, POSOCO 2017b.

Within India, prices for energy traded on the Indian Energy Exchange (IEX) vary based on 

supply and demand by location. For example, day-ahead prices in Bihar averaged $36/MWh for 

the 12 months ending April 12, 2017, about 36% lower than the PPA price governing most 

exchanges across the Eastern Tarai.7 Figure 5 tracks the volume of power traded across the 

CBET area (left axis) against average monthly price on the IEX for Bihar (right axis). 

By comparison, IEX prices for Uttar Pradesh averaged $40/MWh for the year ending April 12,

2017. Figure 6 shows that the highest market prices generally occurred in January, with mid-day 

prices (9 a.m.–5 p.m.) averaging at or above $50/MWh for December through February. Thus, 

the official PPA rate currently governing exchanges across the Western Tarai CBET region was 

 

7 IEX places Odisha in a pricing zone separate from the rest of the Eastern RLDC region. Data reported here are for 

the northern part of the region, excluding Odisha.

Eastern Tarai 

CBET volume

Average IEX dayahead prices

 $-

 $20

 $40

 $60

0

100

200

300

Apr-16 Jul-16 Oct-16 Jan-17

GWh $/MWh

Western Tarai 

CBET volume

Average IEX dayahead prices

 $-

 $20

 $40

 $60

0

10

20

30

Apr-16 Jul-16 Oct-16 Jan-17

GWh $/MWh
13

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

sometimes near or below market prices, unlike the rate for exchanges across the Eastern Tarai 

CBET region, which was almost always above market prices.

Wholesale market energy prices can run higher in Uttar Pradesh than in Bihar. This is 

economically consistent with the fact that the Northern RLDC region was a net importer and the 

Eastern RLDC region a net exporter during this time. Figure 7 shows the one-year price duration 

curves for the two states. (Note that matching x-axis points on the two curves do not correspond 

to the same hour.)

Figure 8 shows the difference in prices between Uttar Pradesh and Bihar for the same market 

hours, arranged as a duration curve. Day-ahead prices were the same 64% of the time. About 

30% of the time, prices in Uttar Pradesh were higher by as much as $25/MWh (IEX 2017). 

Hourly price differences tended to be distributed throughout the operating day.

Figure 7. Price duration curves for Uttar Pradesh and Bihar.

Source: IEX 2017. Note: Curves are not time-synchronized.

Figure 8. Same-hour price differences between Uttar Pradesh and Bihar

Source: IEX 2017. Note: At no time were day-ahead prices in Bihar higher than in Uttar Pradesh.
14

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 4. Market Prices for Day-Ahead Exchanges in Bihar and Uttar Pradesh, by Month

(April 13, 2016, through April 12, 2017, averaged by month)

BaishakhJesthaAsadhShrawanBhadraAshwinKartikMangsirPoushMaghFalgunChaitra

Bihar ($/MWh)

Operating hour

24 $44 $36 $35 $31 $38 $38 $35 $28 $28 $31 $32 $41 

23 $46 $39 $38 $35 $43 $39 $38 $29 $31 $31 $32 $43 

22 $46 $40 $40 $42 $50 $45 $42 $34 $35 $34 $38 $49 

21 $42 $40 $41 $47 $53 $47 $44 $38 $39 $38 $39 $50 

20 $39 $38 $39 $41 $51 $46 $44 $38 $41 $40 $40 $50 

19 $34 $32 $35 $31 $37 $39 $45 $41 $44 $41 $38 $41 

18 $35 $33 $34 $27 $33 $36 $43 $45 $46 $43 $35 $38 

17 $37 $38 $36 $28 $33 $36 $38 $38 $40 $40 $38 $40 

16 $39 $39 $38 $29 $34 $35 $37 $35 $39 $41 $39 $43 

15 $38 $38 $37 $30 $34 $35 $37 $33 $39 $40 $38 $42 

14 $36 $35 $36 $28 $33 $35 $37 $32 $39 $40 $37 $40 

13 $36 $34 $36 $31 $34 $35 $38 $36 $42 $43 $40 $41 

12 $37 $34 $36 $34 $36 $36 $39 $39 $44 $46 $42 $43 

11 $36 $32 $35 $31 $33 $36 $38 $39 $46 $44 $39 $42 

10 $33 $30 $33 $29 $32 $35 $38 $39 $45 $45 $39 $42 

09 $32 $26 $31 $27 $31 $34 $37 $37 $41 $45 $42 $41 

08 $25 $23 $30 $26 $31 $33 $36 $34 $36 $39 $38 $39 

07 $27 $20 $28 $25 $30 $33 $35 $33 $33 $36 $33 $38 

06 $34 $24 $29 $25 $30 $33 $33 $26 $24 $29 $28 $37 

05 $34 $28 $30 $25 $30 $32 $33 $23 $23 $29 $31 $37 

04 $35 $29 $31 $27 $31 $32 $32 $20 $20 $28 $29 $36 

03 $38 $31 $31 $26 $33 $33 $32 $21 $20 $28 $30 $37 

02 $40 $34 $32 $28 $34 $34 $33 $24 $22 $29 $30 $38 

01 $43 $37 $34 $29 $36 $35 $35 $28 $27 $29 $31 $39 

Uttar Pradesh ($/MWh)

Operating hour

24 $56 $48 $39 $32 $39 $43 $36 $33 $31 $33 $34 $42 

23 $51 $50 $43 $41 $45 $46 $39 $41 $39 $47 $46 $49 

22 $49 $47 $41 $44 $50 $50 $42 $39 $43 $55 $45 $53 

21 $45 $46 $42 $48 $53 $50 $44 $43 $50 $69 $50 $54 

20 $40 $41 $39 $42 $51 $46 $44 $39 $42 $51 $43 $52 

19 $37 $39 $36 $32 $37 $40 $45 $41 $45 $51 $40 $42 

18 $44 $47 $37 $28 $34 $42 $43 $47 $48 $47 $39 $39 

17 $47 $50 $41 $29 $34 $43 $38 $45 $42 $50 $44 $41 

16 $46 $49 $43 $30 $35 $42 $38 $44 $41 $45 $43 $44 

15 $45 $49 $42 $30 $36 $45 $38 $43 $42 $49 $49 $43 

14 $43 $47 $40 $28 $34 $46 $38 $43 $44 $49 $45 $41 

13 $43 $45 $39 $31 $35 $44 $38 $47 $46 $66 $52 $44 

12 $43 $42 $38 $36 $37 $44 $40 $53 $48 $57 $56 $45 

11 $41 $38 $35 $31 $33 $40 $39 $51 $49 $66 $56 $47 

10 $39 $35 $33 $30 $32 $38 $39 $50 $50 $73 $58 $45 

09 $36 $30 $31 $28 $31 $35 $38 $47 $44 $56 $49 $43 

08 $30 $27 $30 $26 $31 $35 $36 $37 $37 $44 $44 $39 

07 $33 $28 $28 $26 $30 $34 $35 $36 $33 $39 $36 $38 

06 $40 $34 $29 $25 $30 $37 $33 $28 $24 $34 $33 $38 

05 $49 $38 $31 $25 $32 $42 $33 $27 $23 $29 $31 $37 

04 $51 $40 $33 $27 $33 $44 $32 $23 $20 $28 $29 $36 

03 $52 $42 $32 $27 $34 $45 $32 $24 $20 $28 $30 $37 

02 $52 $43 $33 $28 $35 $42 $34 $27 $22 $29 $31 $38 

01 $53 $47 $36 $29 $36 $42 $36 $31 $27 $30 $31 $39 

Source: IEX 2017.
15

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 4 provides a more detailed breakdown of average prices. Each column represents the 

average 24-hour price profile for the month. High prices for the day tended to occur an hour after 

sunset, consistent with peak demand in both Bihar and Nepal. Only during the evening hours of 

the late monsoon season (mid-August to mid-September) and the middle of the dry season (midMarch to mid-April) did market prices consistently reach $50/MWh. In only 86 hours—less than 

1% of the time—were IEX prices for Bihar higher than the tariff rate currently governing CBET 

from Bihar to Nepal.

3.4 Existing Energy Trading

Power exchanges largely flowed to Nepal for 2016–2017. Volume followed the ebb in net 

generation from Nepal’s domestic hydropower resources during the dry season, as shown in 

Table 5. About 90% of the power Nepal imported from India flowed across the Eastern Tarai 

(POSOCO 2017a and 2017b).

Table 5. Distribution of Nepal’s Electricity Imports, by Month

(April 13, 2016, through April 12, 2017, averaged by month)

BaishakhJesthaAsadhShrawanBhadraAshwinKartikMangsirPoushMaghFalgunChaitra

Hour of operating day

24 289 269 237 221 203 133 93 168 275 325 283 330

23 287 274 236 215 199 140 102 168 279 329 291 334

22 286 268 239 224 208 148 110 172 285 336 294 332

21 281 268 243 228 216 171 153 209 303 344 304 339

20 281 268 245 230 214 181 185 238 299 341 311 347

19 288 268 227 225 221 191 206 264 309 340 317 352

18 263 242 208 196 195 170 190 250 304 317 295 318

17 278 254 216 204 207 132 119 188 264 299 273 324

16 280 257 226 217 214 137 116 185 282 333 294 341

15 271 258 225 212 210 132 109 174 276 329 288 339

14 262 250 215 207 205 130 107 166 267 321 279 336

13 261 251 220 205 210 137 112 167 269 316 282 335

12 266 248 214 206 206 133 115 176 269 326 279 334

11 272 253 224 211 207 142 125 199 283 339 292 343

10 264 251 226 208 211 140 130 210 293 346 297 344

9 265 252 226 214 209 142 135 234 298 339 298 337

8 263 251 226 215 206 139 147 251 307 346 306 343

7 265 257 223 214 205 140 143 242 300 345 297 342

6 266 251 216 197 188 133 123 205 293 343 293 323

5 267 241 208 191 180 106 96 160 263 318 272 316

4 271 252 215 194 173 94 78 148 249 310 262 304

3 274 255 221 198 180 98 75 145 250 303 263 301

2 274 254 227 203 187 106 81 150 251 310 266 305

1 283 261 230 206 195 112 84 150 256 312 269 311

Source: NEA 2017b.
16

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3.5 Impact of Load Shedding on the Value of Imports

Load shedding in Nepal is currently a major factor affecting CBET in the post-earthquake 

electricity market. Power imported from India is key to NEA’s strategy for reducing the impact 

of load shedding, particularly during the post-monsoon months and the dry season. The country’s 

total domestic generation from Magh to Jestha (mid-January to mid-June) was one-half to twothirds of its maximum generation during the monsoon and post-monsoon season. This coincided 

with maximum imports from India.

Two uncertainties complicate an analysis of load shedding. First is the difficulty of calculating 

how many megawatts of customer demand are actually lost when a specific substation or feeder 

line is taken out of service. Equipment power ratings might be known, but actual usage that is 

foregone might not be. The second problem is that NEA does not have an estimate of Nepal’s 

value of lost load (VOLL), so even if the quantity of lost load were known, its value still would 

not be. NEA also does not offer an interruptible tariff from which VOLL may be inferred.

Estimating VOLL is challenging even for the world’s most advanced power markets. Systemwide VOLL estimates in U.S. markets range from around $10,000/MWh to $14,000/MWh 

(London Economics 2013). Where VOLL is estimated separately for customer classes, it can 

reach $30,000/MWh or more for commercial and industrial customers. In some markets, VOLL 

is inferred from existing tariff rates. 

While there is no convention for adapting VOLL from one country to another, adjusting existing 

estimates using gross domestic product (GDP) per capita can provide a crude and general 

approximation of how VOLL estimates in the United States might economically compare in 

Nepal (for GDP per capita, see World Bank 2017). Using this adjustment, the equivalent values 

in Nepal are about three times higher than the cost of importing power from India for the purpose 

of reducing load shedding. When considering commercial and industrial load only, the adjusted 

VOLL is around 10 times higher.

Therefore, a major question affecting the value of options for future CBET is when load 

shedding will cease. The economic drivers could change significantly at that point, altering the 

balances of supply and demand that affect which cross-border transmission paths are most likely 

to have the greatest long-term value.
17

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 9. Monthly generation for Nepal, by resource type.

Source: Compiled from NEA 2017b. Note: Load shedding was not reported prior to Kartik 2073.

Figure 9 shows the generation resources used to serve load in Nepal from mid-April 2016 

through mid-November 2017, corresponding to the 2073 Nepalese calendar year and the first 

seven months of the 2074 calendar year. The data show that load shedding was frequent in Poush 

(mid-December to mid-January) and began to abate in Jestha (mid-May through mid-June) with 

the beginning of the monsoon season and a corresponding increase in domestic hydro generation. 

Domestic generation for the seven months ending in Kartik 2074 (mid-April through midNovember 2017) was 30% higher than for the same period a year earlier.

8 Imported power was 

18% higher.

The month with the most frequent recorded load shedding during the period examined was Magh 

(mid-January to mid-February). In the absence of data on total customer demand and actual lost 

load, this analysis uses Magh as a test for critical load shedding trends in Nepal. In the average 

daily profile for that month, the peak volume of load served typically occurred during the hour 

ending at 7 p.m., which we use here for testing supply and demand trends affecting future load 

shedding. Average load served for this test hour was 833 MW (NEA 2017b).

Table 6 and Figure 10 show the domestic generation resources that were typically available 

during the test hour. Imports from India used to supplement domestic generation at this time 

averaged 340 MW, or about 41% of average energy delivered to load. The higher availability of 

NEA hydro—66%—reflects NEA’s operating strategy of reducing early morning and midday

operation levels at its own peaking RoR hydro resources and increasing its generation during the 

mid-morning and evening hours. 

 

8 NEA reports operations data by Nepalese months. We retain that time aggregation here.

0%

20%

40%

60%

80%

0

250

500

750

1,000

BaishakhJesthaAsadhShrawanBadraAshwinKartikMangsirPoushMaghFalguChaitraBaishakhJesthaAsadhShrawanBadraAshwinKartik

2073 2074

% of hours

in month GWh

Nepal IPP NEA RoR NEA storage Imports % of hours with load shedding
18

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 6. Domestic Generation Available for Critical Load Shedding Hours in Nepal

Energy Served, 6 p.m. to

7 p.m. Period, Magh 2073*

Projected Capacity Available for 

Dry-Season Peak Demand (MW)

Average MW

% of 

Nameplate 2018 2019 2020

NEA hydro 252 66% 281 582 622

NEA storage 74 80% 85 85 85

IPP hydro 168 38% 257 to 398 290 to 484 333 to 596

Total 493 623 to

764

957 to 

1,151

1,040 to 

1,303

Imports 340

Availability for 

peak load, holding 

imports constant

833 963 to 

1,104

1,297 to 

1,491

1,380 to 

1,643

*Corresponds to Jan. 14 to Feb. 12, 2017.

Notes on table assumptions and methodology: “Projected capacity available for dry-season peak demand” is the 

nameplate MW projected by NEA to be online for the indicated year, multiplied by the percentages in column 3.

Projections for new IPP capacity are taken from NEA 2017c and only include projects under construction that have 

closed on financing. 

Figure 10. Short-term projection of supply and served load for test hour.

Source: NEA 2014, WECS 2017. Note: “Load served” excludes unserved load (load shedding). Load served for 2017 

is projected forward hypothetically using two growth rates projected by the Nepal Water and Energy Commission 

Secretariat (WECS). The low growth curve is the WECS reference scenario, based on annual economic growth of 

7.2%. The high growth curve assumes 9.2% economic growth plus short-term policy interventions by the Government 

of Nepal.

NEA hydro

NEA storage

IPP hydro

 -

 500

 1,000

 1,500

 2,000

2017 2018 2019 2020

New IPP 

capacity 

discounted 

for project 

delays based 

on historical 

trends

Gap met with imported power

Load

served

Diminished load shedding, 

trend toward reduced imports
19

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

NEA’s projected amount of new capacity from 2018 to 2020 indicates a potential for greater 

resource availability—and, therefore, reduced load shedding—during the dry season. The largest 

NEA project currently under construction is the 456-MW Upper Tamakoshi hydroelectric 

project, which is scheduled to be online in early 2019 (NEA 2017a). Upper Tamakoshi, along 

with new hydro capacity from IPPs, could double Nepal’s domestic generating capacity available 

during the dry season by 2019. These numbers suggest that for the test hour, resource availability 

could increase at an annual rate of 19% to 26% from 2018 to 2020.

NEA uses load growth projections by Nepal’s Water and Electricity Commission Secretariat, 

which models economic growth and national energy consumption under various assumptions. Its 

reference scenario assumes annual economic growth of 7.2% and shows electricity demand 

growing 15.1% annually from 2015 to 2020 and 12.2% annually from 2020 to 2025. The 

commission also modeled demand with 9.2% economic growth accompanied by targeted policy 

interventions by the government. This scenario results in 31.7% annual demand growth from 

2015 to 2020 (boosted by assumed policy interventions), leveling off to 9.7% annual demand 

growth from 2020 to 2025. 

Figure 10 applies these two growth trajectories to total load served (domestic generation plus 

imports) for the test hour. In this figure, the gap between the line representing load served and 

the domestic supply stack approximates the projected use of imports for the test hour. A smaller 

gap implies less need for load shedding, holding imported power constant. 

The gap shrinks considerably in 2019, largely due to the projected completion of Upper 

Tamakoshi (NEA 2017a). The chart suggests that in 2019, Nepal’s domestic generation could 

meet nearly all of the demand that was served in 2017, depending on overall economic growth. 

(For reasons previously discussed in this section, the point at which load shedding could end 

completely is difficult to predict due to the lack of data on actual lost load for 2017.)

One important variable will be the actual pace of capacity additions from IPPs. Delays and 

cancellations can happen even if the project has secured financing and is under construction. For 

example, of all IPP capacity with an expected commercial operation date of 2016, only 38% was 

actually online in 2017 (NEA 2017b and 2017c). Therefore, to account for possible project 

delays and attrition, Table 6 and Figure 10 show new IPP capacity as a range. The high value is 

the nameplate capacity of all generators expected to be online, while the low value discounts new 

generation for each year by 38%. 

The consequence for CBET between India and Nepal is that load shedding is not likely to be a 

major driver for trades from India to Nepal in the near future and could cease to be so well 

within the time it would take to build a new transmission line between the two countries. The 

economic benchmark for the value of imports will no longer be Nepal’s VOLL, which, while 

unspecified, is effectively higher than the tariff prices governing flows from India to Nepal. The 

value of future CBET—and, therefore, of new transmission supporting it—will most likely be 

determined by ordinary market factors.
20

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3.6 Eastern Tarai CBET

Existing connections across the Eastern Tarai CBET area include three 132-kV lines and four 33-

kV lines. Net power trades from India to Nepal over these paths amounted to 1,869 GWh for the 

12 months ending in March 2017, an increase of 46% from the previous year (POSOCO 2017a). 

Plans for new generation capacity east of the Butwal flowgate appear to be outpacing the 

anticipated growth in electricity demand in Nepal. IPPs are expected to add between 400 MW 

and 1,000 MW of new generation between 2017 and 2020, along with the 544 MW NEA plans 

to add itself. This would increase the eastern grid’s total capacity by an average of 36% to 59% 

per year, depending on project delays. 

Bihar, the state bordering most of the Eastern Tarai, historically has been a net importer of power 

from other parts of the Eastern RLDC region. Bihar was 19% of the region’s average load for the 

year ending March 2017 but provided only 6% of regional generation (POSOCO 2017a). About 

92% of the Eastern RLDC region’s generation for the year ending March 2017 came from coal, 

with nearly all of the remainder coming from hydro. 

Growth in the region’s generation capacity has been keeping pace with demand, with about 60% 

of the additions in 2016 coming from new thermal generators and the rest from new hydro. As of 

July 2017, the region also had about 1,000 MW of renewables, nearly half of which was bagasse 

processing in West Bengal.

The Eastern RLDC currently has surplus supply for most of the year, enabling it to export 

upwards of 20 TWh to the Northern RLDC. The eastern region’s highest peak demand was 19.6 

GW in March 2017. Its total effective generating capacity was 30.9 GW, giving it a large 

effective reserve margin of nearly 58% (POSOCO 2017a, CEA 2016a, CEA 2016b).9

Bihar, West Bengal, and Odisha have a significant amount of load-driven up-ramping during the 

three hours before evening peak. Figure 11 shows the average daily load profile by month for 

Bihar. Low demand in the late afternoon followed by high demand after sundown often results in 

about 1,000 MW of up-ramping in the early evening hours of winter. Load analysis data for all 

states in the Eastern RLDC region show a pattern of about 5,000 MW of coincident ramping in 

November over the three hours prior to peak, about one-quarter of that occurring in Bihar 

(POSOCO 2016). 

During this same month, the Eastern RLDC region’s 5,759 MW of hydro resources ran at about 

half the pace they did in September and October. This suggests that some of the region’s 

ramping requirements in November 2016 might have been provided by resources other than 

hydro—possibly coal units, which have limited ramping capability.

 

9 Effective generating capacity was obtained by adjusting the region’s installed capacity of coal/lignite and hydro 

(31.4 GW and 5.8 GW) by the most recent all-India forced outage rates for these technologies (19% and 5%), as 

reported by India’s Central Electricity Authority.
21

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 11. Daily load profiles for Bihar, by month.

Source: POSOCO 2016.

~1,000-MW ramp 

over < 3 hours
22

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

As demand throughout the Eastern RLDC region increases, the ramping burden during these 

months could require operational flexibility that the region’s coal units might not be capable of 

providing as cost-effectively as imports might. This could provide a high-value opportunity for 

power exports from Nepal to the Eastern RLDC region as more of Nepal’s hydropower comes 

online.

One factor that could increase the flow of power from Nepal across the Eastern Tarai is potential 

demand in Bangladesh. Both countries have been investigating hydro development in Nepal for 

use in Bangladesh (The Independent 2017). However, India’s guidelines for CBET might prevent 

a direct exchange between Nepal and Bangladesh. Transfers and prices that are determined 

administratively through Indian intermediaries could both increase transaction costs and result in 

less efficient power dispatch.

Major Bilateral Project: Arun 3

(Estimated online date: 2023)

SJVN Ltd., a power producer owned by the 

Government of India and the State 

Government of Himachal Pradesh, is 

developing the 900-MW Arun 3 

hydroelectric project in eastern Nepal. The 

Indian government approved the project in 

early 2017, and work has begun on land 

acquisition, transmission, roads, and other 

infrastructure for construction. (Subedi

2017).

Under the memorandum of understanding 

between the Government of Nepal and 

SJVN, Nepal would receive an estimated 800 

GWh of power from the project annually, 

which is slightly more than NEA’s annual 

sales in its Biratnagar region. The balance would flow into Bihar via a dedicated 400-kV transmission 

line from Dhalkebar on the border to Muzzafarpur. Another dedicated 400-kV line would carry power 

from Arun 3 to Dhalkebar (IBN 2017).

3.7 Western Tarai CBET

Net flows across the Western Tarai CBET—nearly all of it on the Tanakpur-Mahendranagar 

connection—amounted to 190 GWh for the 12 months ending April 2017, much less than the 

volume traded across the Eastern Tarai CBET (POSOCO 2017b). Imports into Nepal slowed 

significantly during the post-monsoon months of October and November, with the volume 

dropping to less than one-third the pace of the rest of the year. 

Nepal’s western grid was a net importer of energy throughout the 2016–2017 year. The region 

had about 34 MW of generating capacity, most of it owned by IPPs. The three largest hydro 

stations—which account for more than three-fourths of the Western region’s grid capacity—
23

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

generated about 127 GWh of energy for the year ending April 12, 2017, 27% as much electricity 

as NEA sold through its two western offices (NEA 2017a and 2017b).

NEA plans to add 30 MW in the Western region, and new IPP capacity could amount to another 

37 MW to 97 MW by 2020. If these additions operate comparably to the region’s existing 

capacity, they could shift the western NEA grid from being a net importer of electricity to a 

position in which internal generation is about the same as consumption. 

Uttar Pradesh is the Northern RLDC region’s largest load center with 31% of total regional 

demand. Coal is the Northern RLDC’s largest generation source, although with a 65% share of 

the mix it is not as dominant as is the case for the Eastern RLDC. Hydro provided 26% of the 

Northern region’s power (compared to less than 8% in the Eastern RLDC region), with the 

remainder divided among nuclear, natural gas, and a growing share of wind and solar (POSOCO 

2017b). 

Rapid development of wind and solar power is another contrast between the Northern RLDC and 

the Eastern RLDC regions. Most of the Northern RLDC region’s activity has been in Rajasthan, 

which as of April 2017 had 1.8 GW of solar capacity and 3.9 GW of wind capacity. Uttar 

Pradesh and Uttarakhand had another 314 MW of solar photovoltaic (PV). Higher penetrations 

of wind and solar PV will increase the Northern RLDC’s need for flexible resources, which 

could increase the value of power from flexible hydro resources in Nepal across the Western 

Tarai CBET area.

Major Bilateral Project: Upper 

Karnali

(No estimated online date)

GMR, a private infrastructure developer 

headquartered in New Delhi, is negotiating 

a finance package for the 900-MW Upper 

Karnali hydroelectric project, located in 

western Nepal. As of this writing, the firm 

had requested additional time to close on 

project financing (Subedi 2017).

Nepal would get more than 400 GWh per 

year under the terms of GMR’s agreement 

with the Government of Nepal, which is 

slightly less than the 482 GWh that NEA 

sold west of Butwal in its Attariya and 

Nepalganj regions in 2016–2017. This, 

combined with other capacity additions that 

are expected to be online by 2020, could put the region in a position of being a net exporter, excluding 

the power that GMR would export into the Northern RLDC region (IBN 2017).
24

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 12. Daily load profiles for Uttar Pradesh, by month.

Source: POSOCO 2016.

~2,500-MW ramp 

over < 3 hours
25

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 12 shows that demand in Uttar Pradesh during March tends to increase by nearly 2,500 

MW in less than three hours around sunset. Evening ramping can also be significant during other 

months (POSOCO 2016). Thus, while the Northern RLDC region has more flexible hydro 

capacity than the Eastern region has, the need for such flexibility—as reflected in seasonal 

ramping requirements—is much larger in Uttar Pradesh than in Bihar.

3.8 Discussion

The detailed analysis of this section supports the following conclusions:

1. Load shedding in Nepal will most likely cease to be a driver for CBET between India and 

Nepal within the time it would take to build a new transmission line.

A. In the first post-earthquake calendar year, the dominant driver for CBET was load 

shedding in Nepal. While the true VOLL remains undetermined, Nepal’s policy 

of relying on imports to relieve load shedding implies that the value per MWh 

was higher than the tariff prices governing CBET. This is consistent with 

practices elsewhere in the world, including markets where the value of lost load 

has been calculated.

B. Once Nepal has sufficient internal resources to minimize load shedding, the 

implicit VOLL will no longer be the primary factor behind the value of CBET 

economics. The tariff rate that currently governs most CBET across the Eastern 

Tarai could then begin to suppress further bulk trades of energy from Bihar to 

Nepal. 

2. Market fundamentals and longer-term trends for Indo-Nepalese CBET appear to favor 

connections to India’s Northern RLDC region, which tends to be a net importer of 

electricity. Upgrading the Butwal-Gorakhpur path is consistent with the likely value 

propositions.

A. Butwal to Gorakhpur appears to be the highest-value path for new CBET 

transmission in the near future. This path provides access to India’s Northern 

RLDC region and has already been identified as a priority for transmission 

development (GoI/GoN 2017, MCC 2017). Wholesale prices in Uttar Pradesh are 

generally higher than in Bihar, and the Northern RLDC area is rapidly increasing 

its use of large-scale wind power and PV. Greater use of variable renewable 

resources tends to increase the need for grid flexibility, which reservoir storage 

and peaking RoR hydro can provide. 

B. In contrast, in the Eastern RLDC region, low market prices in Bihar could limit 

bulk trades of hydropower from Nepal to Bihar. The rate currently paid by NEA 

to IPPs for peaking RoR hydro—around $47/MWh in the wet season from June to 

November, and up to $103/MWh during the dry season—is consistently higher 

than market prices in Bihar, except in the early evening hours from mid-August to 

mid-September (NEA 2017a). However, production cost modeling could provide 

additional insights about the effect CBET across the Eastern Tarai might have on

the redistribution of power flows in the Eastern RLDC region. This could reveal 

hidden CBET potential value.
26

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3. While connections across the Western Tarai area could further increase mutually 

beneficial CBET opportunities, doing so could depend on system upgrades within Nepal 

to increase the capacity to move between Butwal and Nepalganj.

A. The Western Tarai CBET could offer significant economic potential for mutually 

beneficial power exchanges. However, Nepal’s ability to take full advantage of 

CBET opportunities across the Western Tarai might depend on internal 

transmission development in conjunction with new cross-border transmission. 

The existing transmission flowgate at Butwal could limit the ability of generators 

in eastern Nepal to sell into India’s higher-priced Northern RLDC region via 

Nepalganj and Attariya. One question for PCM is whether the Butwal-toNepalganj path would be congested under future load growth scenarios. 

Specifically, would the proposed 400-kV interconnection from Butwal to 

Gorakhpur be sufficient for economic deliveries from eastern Nepal into Uttar 

Pradesh, or would congestion on the path from Butwal to Nepalganj indicate the 

benefit of expanding that internal path? (This will be tested more rigorously in the 

production cost modeling phase of this project.)

4. Maximizing the value of any new transmission intended to enhance CBET could depend 

on bilateral tariff reform and greater operational coordination between Nepal and India.

A. India’s growing need for system flexibility could create new CBET value on both 

sides of the border. This, however, will most likely depend on efficient real-time 

price formation, which in turn could depend on greater integration of grid 

operations and markets. Unlike bulk power sales, deployment of flexibility 

resources is an hourly—even subhourly—optimization task. If peaking RoR and 

storage hydroelectric projects in Nepal are to be an additional source of flexibility 

for renewable energy development in India’s Northern RLDC region, CBET 

interties along the Western Tarai will need an operational status equivalent to 

other parts of the Indian grid.

B. Indian energy developers are already looking to Nepal for new hydro capacity 

serving the Eastern and Northern RLDC regions, as exemplified by the Arun 3 

and Upper Karnali projects. Both are planned as peaking RoR hydro. The value to 

the Eastern RLDC lies primarily in additional operational flexibility: the resource 

mix is currently 92% coal and load in Bihar and West Bengal have severe upramping requirements in the evenings. The value to the Northern RLDC lies in the 

ability to integrate a growing portfolio of wind and solar in Rajasthan, along with 

seasonal load ramping needs. With greater operational coordination between India 

and Nepal, other hydro resources in Nepal could supplement the flexibility value 

provided by the Arun 3 and Upper Karnali projects. 

5. Next steps

A. The question of whether the benefits of added flexibility would be enough to 

warrant additional transmission connections across the Eastern or Western Tarai

would need to be examined in greater detail through PCM. Reduced CBET due to 

reduced load shedding in Nepal would leave more capacity available on existing 

cross-border transmission. Whether that is likely to be enough will depend on 
27

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Nepal’s mix of flexible peaking RoR hydro and less-flexible RoR hydro, the 

timing of load ramps, power flows elsewhere in India, and other factors.

B. PCM can test load growth and capacity growth scenarios that could accelerate or 

delay the need for new cross-border transmission. PCM can also compare two 

paths for moving hydropower from Nepal to the Northern RLDC region: via 

Butwal, or via the Western Tarai, assuming expansion of the Butwal flowgate 

within Nepal.

C. All these factors tend to increase the uncertainty and risk of new transmission 

projects intended to support CBET. Whether new transmission would be used and 

useful would depend on energy prices—and on whether generators can respond to 

them. The fixed rate governing CBET pricing could distort the price signals, 

although tariff reforms allowing market-based CBET pricing could help. Such 

reforms would increase the opportunities for hedging and other measures to 

manage risk. A broad application of reform would include ensuring the ability of 

IPPs in Nepal to submit energy offers into India’s power markets, and the ability 

of industrial customers in Nepal’s Eastern Tarai to participate in any current or 

future demand response programs managed through the Eastern RLDC 

operations. Similarly, market liberalization between Nepal, India’s Eastern RLDC 

area, and Bangladesh could increase regional flows in an economically efficient 

manner. Without such market liberalization, the economic rationale for expanding 

the existing transmission infrastructure across the Eastern Tarai to support CBET 

could be limited.
28

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

4 Variations in Construction Costs

Terrain characteristics can affect the cost of building new transmission, which in turn can affect 

the balance between costs and benefits among transmission expansion options. This section 

reports the results of a geographic information systems (GIS) analysis of likely CBET 

interconnection points along the Indo-Nepalese border and how they might vary with respect to 

the cost of construction. The analysis focuses on the physical attributes of the surrounding area, 

and not on legal or economic issues such as right-of-way or local land values.

The map in Figure 13 shows the eight major interconnection points that currently exist on the 

border. It was assumed for the GIS analysis that the most likely form of CBET-related 

transmission expansion would be to upgrade these existing interconnections to 400 kV, as these 

points already have connecting substations identified on the Indian and Nepalese grids. One 

point—Dhalkebar to Muzzafarpur—was excluded from the analysis because the necessary 

infrastructure for 400-kV service is already in place.

Figure 13. Map of major CBET interconnections.

Note: The Dhalkebar-Muzzafarpur connection would repower the existing line from 132 kV to 400 kV, requiring no 

additional right-of-way.

4.1 Terrain Assessment

The U.S. Bureau of Land Management has a terrain classification system that it uses for 

permitting infrastructure development on land owned by the U.S. government. Each is a physical 

characteristic and is therefore comparable from one country to another. The categories are also 

identifiable by way of satellite imagery.

These different terrain types pose different challenges with respect to siting and building new 

transmission. In 2012, utilities and stakeholders in the western United States assigned cost 

multipliers to each category as part of a regional transmission planning exercise (Black & Veatch 

2012). Like Nepal, the western United States includes mountains, forests, hills, waterways, 

farmland, and urban areas. 
29

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 7 shows the terrain categories and the multipliers associated with each terrain type. This 

analysis assumes that while the basic cost of building new transmission might differ between the 

United States and South Asia, stretches across forested areas and mountains will always be more 

difficult and more expensive than the basic cost of putting a line across flat farmland. The 

analysis makes the assumption that the degree of additional difficulty in the South Asian and 

U.S. contexts is comparable.

Table 7. Land Classification System

Terrain Type Multiplier

Scrubbed/Flat 1.0

Farmland 1.0

Desert/Barren Land 1.05

Irrigated Farmlands/Wetlands 1.2

Rolling Hills (2%–8% slope) 1.4

Urban 1.59

Mountains (>8% slope) 1.75

Forested 2.25

Source: Black & Veatch 2012.

4.2 Methodology and Results

Figure 14 shows the types of terrain within a 40-kilometer radius of each CBET point. Irrigated 

farmland dominates all areas, although in Nepal some areas have forests and rolling hills close to 

the border.

Figure 14. Geospatial analysis of areas around CBET points
30

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

The last step of the analysis was to score each CBET point based on its weighted geospatial 

attributes as follows:

ssssssssss = �sshaa ii

ii

∗ mmmmmmmmmmmmmmmm ii

where i is a terrain type, sharei is the percentage of land within a 40-km radius of the CBET 

point characterized by that terrain type, and multiplieri is the multiplier associated with the 

terrain type. A higher score indicates a higher proportion of difficult terrain in the vicinity of the 

CBET point. While it might be possible to find a low-cost transmission route in any of the areas, 

a higher score means relatively fewer options for doing so.

Table 8 shows results of the GIS screening and scoring. The scores suggest the largest number of 

options for minimizing the cost of building new transmission for CBET are likely to be found at 

the far eastern end of the Eastern Tarai (Biratnagar/Duhabi-Purnea and Duhabi-Kataiya 

Powerhouse) and at the far western end of the Western Tarai (Attariya/Beldandi-Bareilly). 

Table 8. Scoring of CBET Points Based on Geospatial Attributes

CBET Point Score Score Indexed to Mean

Biratnagar/Duhabi-Purnea 1.20 0.94

Duhabi-Kataiya Powerhouse 1.22 0.96

Attariya/Beldandi-Bareilly 1.24 0.97

Lamki-Bareilly 1.28 1.00

Butwal-Gorakhpur 1.28 1.00

Ramnagar-Gandak 1.33 1.04

Kohalpur/Nepalganj-Lucknow 1.39 1.09

Note: lower score implies lower cost per mile.

All CBET points are surrounded by irrigated farmland, making the multiplier for that type of 

land the effective baseline for all scores. Kohalpur and Ramnagar are also close to forested hills, 

which could add to the cost of extending transmission from the border to Nepal’s interior.
31 

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

5 Production Cost Modeling

Production cost modeling (PCM) provides a more detailed look into electricity supply and 

demand. For issues involving cross-border trading in South Asia, CBET can provide technical 

insights that a general economic analysis cannot. For example, hourly (and even subhourly) 

changes in supply and demand can cause prices to change throughout the course of a day. This 

affects the long-term value of flows across a particular transmission path. 

One important question that PCM can test is the economic benefit of greater regional 

coordination. A typical simulation of the whole grid assumes that the flow of power across a 

political border is not constrained by institutional rules. Combining this basic scenario with a 

companion scenario that accounts for cross-border institutional factors can quantify the 

additional benefits of reforming CBET rules. 

The most important limitation of PCM is that it does not account for generator fixed costs, which 

are outside the scope of PCM. PCM’s objective is to operate a given set of units most efficiently, 

and it therefore considers only variable costs, not fixed. 

PCM does not anticipate new investment decisions even if a new generator would significantly 

reduce the total variable cost of generation. It can, however, serve as a tool for evaluating a 

potential investment. By contrasting locational marginal price (LMP) in scenarios with and 

without the potential new investment, a developer or lender can test the likelihood that energy 

prices would be high enough to provide a return on investment if the new plant were built. 

5.1 Fundamentals 

PCM simulates how generators would be dispatched over a defined period of time if the sole 

objective were to minimize variable operating costs. This solution represents an economically 

ideal dispatch—what the system would tend to do absent any unpredictable shock or out-ofmarket intervention by authorities. Hours (or smaller time increments) are optimized 

sequentially, with the outcome of each time increment providing the initial conditions for 

optimizing the next time increment. 

A simulation neither adds nor retires any generator, although it can leave an existing unit idle if 

using it would increase the cost of generation. Similarly, PCM accounts for transmission limits 

but does not add or expand transmission if a path is congested. It models all infrastructure as it is 

assumed to exist under the scenario being tested.

A PCM simulation relies on the operational specifications of all generators and transmission 

lines. These include:

• Each generator’s cost of being turned on

• Minimum and maximum production limits (in megawatts) specific to each generator

• Maximum ramp rates (in megawatts per minute) specific to each generator

• Heat rates (in British thermal units of fuel per kilowatt-hour produced) specific to each

generator
32 

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

• Limits on the amount of power that can flow safely across each transmission line.

The simulation also requires a number of assumptions, such as: 

• Fuel prices

• Hourly demand for energy at specific points on the grid

• The amount of capacity to be held back as operating reserves

• Hourly generation profiles for wind and solar resources.

With all of these parameters, PCM identifies the generators capable of meeting demand for each 

hour (or each subhourly time increment) at the lowest total cost. It starts idle units for the next 

hour if the ones already committed do not have enough economical capacity left on them to meet 

the increase in load, or if transmission congestion limits the ability to ramp up the use of more 

economical resources.

An important output from PCM simulation is LMP. An LMP is the additional cost to the system 

if demand at a given point increases by 1 MW. If there is transmission congestion, the same 

operating time can have different LMPs at different points on the grid. Prices on the load side of 

a transmission constraint will tend to be higher than LMPs elsewhere on the system. This reflects 

the cost of shifting dispatch from low-cost units to higher-cost units on the load side of the 

constraint to avoid exceeding a transmission line’s safe operating limit. 

Day-ahead and real-time energy markets operated by regional transmission organizations in the 

United States rely on software similar to PCM to conduct security-constrained economic 

dispatch. There are two important differences between market dispatch software and PCM: 

• Market dispatch software allows generators to submit strategically crafted offer curves

(monotonically increasing price-to-quantity points for a single unit, with the ability to

change the curves), whereas PCM usually relies on static assumptions about a unit’s

marginal cost, which is a function of the unit’s heat rate and the price of fuel.

• Market dispatch software optimizes over a shorter time period (24 hours for day-ahead

market operations), whereas PCM can optimize an entire year or longer.

In regional transmission organizations, load-serving entities pay the LMPs affecting their service 

areas, and generators receive payments based on the LMPs at the nodes where they connect. 

5.2 Questions To Be Addressed with PCM

Prioritizing new CBET transmission will likely depend on how the addition of new generation in 

Nepal will affect optimal power flows on the grid regionally. The end of load shedding in Nepal 

will likely reverse the direction of some economic drivers for CBET. The full effect of this 

change on transmission investment, however, could depend on several other factors. 

The second paper in this series (McBennett et al. 2019) uses PCM to test the key questions 

resulting from the economic analysis in this report. The scenarios examine different levels of

new IPP capacity additions, the effect of cross-border operational coordination on potential 

CBET benefits, the potential impacts of greater CBET between India and Nepal on India’s 
33

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

ability to integrate large penetrations of new wind and solar capacity, and the effects a dedicated 

Nepal-Bangladesh trade would have on CBET value.
34

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

References 

Black & Veatch. 2012. Capital Costs for Transmission and Substations: Recommendations for 

WECC Transmission Expansion Planning (report prepared for the Western Electricity 

Coordinating Council). Overland Park, KS: Black & Veatch. 

https://www.wecc.biz/Reliability/1210_BV_WECC_TransCostReport_Final.pdf.

CAISO (California Independent System Operator). 2018. Western EIM Benefits Report: Fourth 

Quarter 2017. Folsom, CA: CAISO. https://www.westerneim.com/Documents/ISOEIMBenefitsReportQ4_2017.pdf.

CEA (Central Electricity Authority). 2016a. Review of Performance of Hydro Power Stations, 

2015–16. New Delhi, India: CEA.

CEA. 2016b. Overview of Annual Performance Review of Thermal Power Stations for 2014–15. 

FERC (Federal Energy Regulatory Commission). 2011. “Transmission Planning and Cost 

Allocation by Transmission Owning and Operating Public Utilities (Final Rule). Docket No. 

RM10-23-000 (Order 1000).” https://ferc.gov/industries/electric/indus-act/trans-plan.asp.

GoI/GoN (Government of India and Government of Nepal). 2017. India-Nepal Joint Statement 

during the State Visit of Prime Minister of Nepal to India. August 23–27, 2017.

IBN (Office of the Investment Board of Nepal). 2017. “Our Projects.” http://ibn.gov.np/ourprojects. Accessed January 2018.

IEX (Indian Energy Exchange). 2017. Day-ahead market prices for zones E1 (including Bihar) 

and N2 (including Uttar Pradesh). New Delhi, India: IEX.

London Economics. 2013. Estimating the Value of Lost Load (briefing paper prepared for the 

Electric Reliability Council of Texas, Inc.). Boston: London Economics. 

http://www.ercot.com/content/gridinfo/resource/2014/mktanalysis/ERCOT_ValueofLostLoad_Li

teratureReviewandMacroeconomic.pdf.

McBennett, B., A. Rose, D. Hurlbut, D. Palchak, and J. Cochran. 2018. Cross-Border Energy 

Trade between Nepal and India: Assessment of Trading Opportunities. Golden, CO: National 

Renewable Energy Laboratory technical report (forthcoming).

MCC (Millennium Challenge Corporation). 2017. Summary of the Nepal Compact. Washington, 

DC: MCC.

NEA (Nepal Electricity Authority). 2014. “Energy Demand and Peak Load Forecasts (Base 

Case).” Email correspondence with NEA planning department (on file with NREL).

NEA. 2017a. Annual Report. Kathmandu, Nepal: NEA.

NEA. 2017b. Daily operation logs, Nepalese calendar year 2073.

NEA. 2017c. IPP list. Updated spreadsheet, NEA Power Trade Department. 
35

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

NEA. 2017d. NEA Board Decisions on the Power Purchase Rates and Associated Rules for PPA 

of ROR/PROR/Storage Projects Effective from 2074/01/14. April 27, 2017.

NEA. 2018. Annual Report. Kathmandu, Nepal: NEA.

POSOCO (Power System Operation Corporation Ltd.). 2016. “Electricity Demand Pattern 

Analysis” (volumes for Bihar, Damodar Valley Corporation, Delhi, Jharkhand, Odisha, 

Rajasthan, Sikkim, Uttar Pradesh, Uttarakhand, and West Bengal). 

https://posoco.in/reports/electricity-demand-pattern-analysis/.

POSOCO. 2017a. Annual Report, Eastern Regional Load Despatch Centre. New Delhi, India: 

POSOCO.

POSOCO. 2017b. Annual Report, Northern Regional Load Despatch Centre.

SARI/EI and IRADe (South Asian Regional Initiative for Energy Integration and Integrated 

Research and Action for Development). 2017. “Economic Benefits from Nepal-India Electricity 

Trade.” 

Subedi, B. 2017. “Financial closure deadline likely to be extended again.” Kathmandu Post. 

September 16, 2017.

The Independent. 2017. “Power Development Board to sign hydropower import deal with 

Nepal.” July 10, 2017. http://www.theindependentbd.com/home/printnews/103379.

WECS (Water and Energy Commission Secretariat). 2017. Electricity Demand Forecast Report 

(2015–2040). Kathmandu, Nepal: WECS, Government of Nepal. 

World Bank. 2017. “GDP Per Capita (Current US$).” 

https://data.worldbank.org/indicator/NY.GDP.PCAP.CD.
36

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Appendix: Exchange Rates Applied to the Analysis

Indian rupees to U.S. dollar 64.50

Nepalese rupees to U.S. dollar 102.75