# Presentation: 385694

## Modeling Resource ExpansionSSG-WI Transmission Workshop Norm RichardsonDirector, Energy Market Analysis

## Static Techniques for Modeling Resource Expansion

- Use Announced or Planned New Capacity
- Based on press releases, filed resource plans, and interconnection requests, with “gaps” filled in manually
- Reflection of current market conditions on future activity hard to avoid
- Generally, new capacity will only be announced a few years in advance
- Automated Expansion “Rules”
- Use a predetermined ratio of capacity type (60% combined cycle/40% gas turbine) to automatically fill in areas that fall short of required installed reserves
- Ratios could vary by region to reflect projected need or political climate (coal in the Rockies, but not California)
- Methodology responds well to different load scenarios, but needs to be manually adjusted for fuel or emissions scenarios

## Dynamic Techniques for Modeling Resource Expansion

- Market-Driven Equilibrium Approach
- Iterative approach that adds new capacity if energy and capacity prices can cover investment costs
- Can also be used to mothball existing generators which are unprofitable, and restart in the future if market prices improve
- Runtime impacts of iteration require model simplifications
- Dynamic Programming
- Enumerates all possible expansion scenarios, which could include generation and transmission additions
- Runtime impacts are enormous, making the approach only suitable for small systems with model simplifications

## Capacity Markets

- Installed Capacity (“ICAP”) Markets: LSE’s required to purchase forecast peak plus reserves.
- Bilateral Markets: LSE’s acquire firm capacity through bilateral transactions, which often contain both an energy and capacity component.
- Capacity markets allow generators to recover some of their fixed costs, when profits from the energy market are not sufficient:
- Capacity Bid ($/kW-yr) = Fixed Costs ($/kW-yr) – Annual Energy Profits ($000) / Capacity (MW)
- Capacity may be exchanged between areas subject to firm transmission limits and tariffs, but some areas require at least a portion of capacity to be “local”.

## Capacity Expansion & Retirement

- For new construction, the investment costs and operating characteristics for adding each type of technology to each area simulated should be considered.
- At a minimum, at least one of each should be evaluated:
- Peaking resource (simply cycle turbine)
- Intermediate resource (combined cycle plant)
- Base load resource (supercritical coal)
- Unprofitable generators should be mothballed, and repowered in the future if market conditions improve.
- Capacity decisions should be made dynamically based on long term demand and fuel price conditions.

## Capacity Expansion & Retirement

- _Generating Stations:_
- New Capacity Additions
- Mothball Existing Capacity
- Repower Mothballed Capacity

- Price Equilibrium Model

- _Results:_
- New & Existing
- Capacity Profitability

- An iterative approach is needed to determine the amount, type, and location of capacity changes.  As more capacity is added, prices go down and may no longer support the additions.

## Typical Simplifications for Capacity Expansion 

- In order to reduce runtime to reasonable levels, the core simulation model will typically make the following assumptions:
- Aggregation of days to typical weekdays and weekends for each month, with blocks of hours grouped together
- Generator outages are modeled as derations to capacity
- Unit commitment constraints are relaxed or ignored
- Zonal transmission model with “pipeline” and flowgate constraints
- Ancillary services and revenues are rolled into firm capacity requirements
- With an expansion in place, the model should be able to perform a full simulation (without the above simplifications), using the same data for:
- Monthly peak and energy requirements with consistent load shape
- Generator capacity, availability, heat rates, emissions rates, and bids
- Fuel and emission allowance prices
- Limited-use energy (hydro, wind, cogen, etc.)
- Major transmission interface limits and tariffs

## Monte Carlo Approach

- Since fuel and demand forecasts have a high degree of uncertainty, a range of possible price forecasts is more useful than a single “base case” forecast.
- Monte Carlo sampling is used to take representative points on an input distribution, run each point through the model, and produce a set of prices and expansion scenarios, each with equal probability of occurring.

## New Western Capacity Through 2013: Basecase

- Peakers

- Combined
- Cycles

- Coal

- 4,000 MW
- 3,000 MW
- 2,000 MW
- 1,000 MW

- Expansion results from a MarketPower simulation

## New Western Capacity Through 2013: Confidence Intervals 

- Expansion results from a MarketPower simulation

## Investment Decisions Driven By Long-Term Fuel Forecasts

- 30-year net present value of a new combined cycle plant in the West for 100 different draws of gas prices, determined by MarketPower and PROMOD IV.  As gas prices increase, coal plants become the predominant new technology, depressing values of intermediate gas-fired capacity.