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NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. 

Energy Security:
 

Microgrid Planning and Design
 

World Renewable Energy Forum 2012 

Julieta Giraldez 

May 17, 2012 

NREL/PR 7A30 54985 
Outline

• NREL Approach to Microgrid 

• CORE Microgrid Design Proce• Microgrid Modeling and Sim• Valuing Energy
NREL Approach to Microgrid D

• Continuously Optimized Reliable Energy (C

Microgrids

• Differentiating Characteristics:

– Integrates into 24/7 operations– Can optimize on economics or surety

– Focuses on fuel diversity

– Expands/contracts to provide energy for all

load coverage spheres

– Phased approach can allow for gradual

addition of components over time

Load prioritization and migration with added

generation
Achieving Overarching Goa

• Economic Value ‐ Control system to dispatch bas

structure/generation costs

– Primary driver: Economics of generation in context of ra

• Sustainability – integration of renewable energy 

efficiency technologies

– Primary driver: Carbon savings, fuel diversity, emissions 

• Energy Surety ‐ Start with critical loads and expa

load coverage spheres, diversity of generation an

– Primary driver: Ensure reliable operation under differen

scenarios
Key Benefits of CORE Appro

• Increased energy surety

‐ Diversity of generationassets and fuel sources

‐ Generation assets are used

daily

• Increased economic value

‐ Enhanced economic dispatch

‐ Reduced lifecycle costversus initial installation cost
CORE Microgrid Design Proc

NZEI

Assessment

Existing

Generation

Existing Energy

Management

System

Energy Surety

Plan

Grid

Infrastructure

Generator

Specifications

Load Profiles

Grid

Operations

Data Gathering

Communication/

Cyber security

Detailed

Electrical Model

Design Analysis

Power Flow

Dynamic Stability

Short‐Circuit

Controls
Net‐Zero Energy Installatio

NZEI systems approach is optimal for microgri

facilitation (energy and security nexus).

• Maximizes use of sustainable energy techno

• Supplies local generation to electrical loads• Identifies optimal dispatch opportunities

– Sale of power (arbitrage), demand response, etc.

• Characterizes microgrid (microgrid “baseline

– Base distribution system/grid interface– Distributed energy resources (diesel generators/sto

renewable energy combination)
Key Components of a CORE Mic

Economic

Optimization

Generation

Assessment

Energy Surety

Optimization

Controller

Energy

Management

System

Dispatchable and

Non‐Dispatchable

Generation

Seamless

Transition

Energy

Storage

Load

Shedding

Cyber

Security
CORE Microgrid Modeling and Sim

Why was Modeling and Simulation Necessary?

1) Microgrid design presents unique challenges:

– mix of both traditional and new generation equipme

– grid needs “self‐regulation” (of voltage and frequenc

– advanced controls

2) Traditional power‐flow assessments are inadeq

– detailed response characteristics of engines, regulato

needed

– need to include Renewable technologies

3) Need to analyze detailed start‐up sequence an
CORE Microgrid Modeling and Sim

• Combination of traditional and new generation e

– synchronous machines combined with power electroni– non‐linear sources (e.g., PV, batteries)

– In most cases, no standard models are defined (wind is 

• Traditional power‐flow software typically inade

• Requires breadth and depth of knowledge in:

– power systems– electrical machinery– control systems– power electronic converters– advanced/novel protection schemes

– modeling and simulation
Modeling and Simulation Obje

1) Model

– Electrical system – transformers, cabling, switches, e

– Generation equipment – diesel, land‐fill gas, natural 

controls, PV inverters, etc.

– Controls – supervisory controller, existing controls

2) Predict

– Simulate operating scenarios and predict performanc

3) Recommend

– Generation equipment, supervisory control/operatio
True PV Array 

Model 

Controller

PV Inverter Modeling

An advanced PV Inverter model was developed

following features:• True PV array source

– Can input actual sun (irradiance) curves

• Full reactive power control

– Supports future inverter designs– Allows for arbitrary reactive power command

– Advanced Anti‐Islanding Control– Active feedback method
Energy Storage Model

An energy storage model was developed, with 

features:• Detailed battery model

– Electrical components to represent fast and slow dyna

• Advanced controls

– Fast VAR injection– Anti‐islanding protection– Charge/discharge control
Modeling of Gensets

• The general gen‐set model

consisted of an:

– electrical machine; fuel‐handling

system; governor; voltageregulator/exciter

• Diesel gen‐sets operate differently than Land‐fill 

– diesels have direct fuel injection– land‐fill and natural gas have an air system
15

Supervisory Controller

• Functions

– Select the machine group to maintain the microgrid frequency and 

voltage – the “swing machine.”

– Select other generation assets required to support the load.

– Restore loads following priority and timing requirements.

– Control curtailment or restoration of loads using BEMS or load 

shedding.

– Manage adjustment of protection settings for island versus gridconnected operation.

– Pre-programmed contingency responses
Coordination with Baseload Gen

Black-Start: Sequential Addition of All Feed

Note: NG operates in baseload mode 

P1 P2 P3 1.20 

1.00 0.80 Diesel 

0.60 NG 0.40 0.20 0.00 

-0.20 
Natural Gas Sensitivity Stu

Transient Excursions vs Load Step 

0.035 0.07 

 1.0 MW 2.5 MW 3.5 MW 

0 0.2 0.4 0.6 0.8 1

0 0.2 0.4 

0.03

0.025

0.02

0.015

0.01

0.005

0.06 

Frequency Deviation (pu) 0.05 0.04 0.03 0.02 0.01

0 0 

Step Size (MW) Step Siz

Voltage Deviation (pu)
Valuing Energy Security

• Macroscopic approach:

– Based on Gross National Product or Gross Domestic Pr

Outagecost

• Microscopic approach (Customer Damage Funct

– Based on customer survey of outage and cost informat

Depends on duration of interruption, situation in which 

occurs, customer activity

• Analytical approach:

– Based on generation, load and cost models– Calculate Expected Energy Not Supplied and Outage Co

 $  GNP(or GDP)in 

= kWh Totalannualenergyconsum
CDF Approach

• Microscopic approach – Customer Damage Func

developed survey

– Surveys exist for residential, commercial, and industria

exist for military bases

• Chose hypothetical scenarios that vary in durati

situation in which interruption occurs (emergen

– Scenario A

There is a power outage and the lack of power supply la

hours, 8 hours or 24 hours. The base is not in an emerge

– Scenario B

There is an outage and a natural disaster or terrorist atta

simultaneously going on in the area. The lack of power shour, 4 hours, 8 hours, or 24 hours and the base is unde

situation and has to remain operational.
CDF Approach

• Survey: NREL‐designed survey assesses cost

failure

– Suspended mission critical and

non‐critical operations

– Impact on relief and rescue

missions

– Personnel sent home from work– Overtime for emergency workers

– Base security impacts

– Infrastructure impacts (heat,

water, sewer, traffic lights)

– Delays or failure

generation

– Fuel for backup 

– Equipment dam– Human lives pu– Food spoilage– Residential imp– Curtailing comm

operating hours

• Costs vary depending on scenario and outag
CDF Approach

• Once survey completed the data has to be proce

to create a Customer Damage Function (CDF)

• Results: substantial cost difference between Sce

– Fewer personnel sent home– Risk increases: communications, human life put to risk

$/kW peak Customer Damage Function 600

500400

300200100

0

1 4 7 10 13 16 19 22 
CDF to Support Financing Energy S

• How to use the CDF?

– What duration of interruption to prepa– What duration of interruption should b

justify Energy Security projects?

– How unreliable is the grid?– What are the statistics of large outage 

the grid?
CDF to Support Financing Energy S

• Utility distribution system reliability indices

– Consumer or end‐user oriented indices– Utilities report to Public Utility Commissions (PUCs) re

performance indices

• 3 most popular customer‐oriented indices

Sum of customer interruption du

SAIDI = 

Total number of customer

Total number of customer interru

SAIFI = 

Total number of customers se

Customer hours of available servi

ASAI = 

Customer hours demanded 
CDF to Support Financing Energy S

• Example utility SAIDI and SAIFI over 20 years:

– Highly variable and no tendency

350300250200150100

50

0

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

SAIDI (min) SAIFI (outage)
CDF to Support Financing Energy S

• Average metrics may not capture key criteria fo

security planning in installations?

– Annual average duration and customers affected in the 

# Customers
 

annual events

600005000040000300002000010000

0

2001 2002 2003 2004 2005 2006 2007 2008 20

Average customers affected Average customer interruptio
   

CDF to Support Financing Energy S• Outage duration frequency distribution of exam

10 largest annual events over 10 years

– What is the risk to be assumed?

0%5%

10%15%20%25%

Frequency in%

Statistical analysis of 100 la

the last ten year

Duration of interruption in hours
CDF to Support Financing Energy S

$/kW peak Customer Damage Function

600500400300200100

0

?

? Longe

1 4 7 10 13 16 19 22
Thank you!

Questions?

Julieta Giraldez

julieta.giraldez@nrel.gov

303‐275‐4483