Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin

Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. 2011-XXXXP

Maximizing Revenue of ES in MISO Energy & Frequency Regulation Markets

Tu Nguyen, Ray Byrne

Energy Storage AnalyticsEquitable Regulatory Environment Thrust Area

▪ Goals: Lower barriers to widespread deployment of energy storage by identifying new and existing value streams, quantifying the impact of policy on deployment, and developing new control strategies

▪ Objectives:▪ Project case studies

▪ Tools for storage valuation

▪ Identify new and existing value streams

▪ Control strategies to maximize

revenue/grid benefit

▪ Assess policy impact on storage

▪ Develop policy recommendations

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Energy Storage Applications

▪ Storage can provide many grid services:▪ Resiliency and reliability

▪ Transmission and Distribution (T&D) upgrade deferral

▪ Balance the variability of renewable generation

▪ Behind the meter savings for commercial and industrial customers

▪ Ancillary services (frequency regulation, spinning reserve, black start, etc.)

▪ Peaker plant replacement

▪ Voltage support

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MISO Frequency Regulation Market

▪ In 2011 FERC issued Order 755 which requires RTOs/ISOs to compensate the frequency regulation resources based on the actual regulation service provided.

▪ In order to comply with FERC Order 755, in December 2012 MISO began performance-based compensation for frequency regulation services.

4Image credit: MISO Image credit: Sunverge

MISO Performance Tests

▪ Instructed mileage [MW]:

▪ Desired mileage [MW]:

▪ Target mileage [MW]:

▪ Actual mileage [MW]:

▪ 5-min performance test:

▪ Hour performance test:

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MISO Performance-based Compensation▪ Pre-payment covers the capacity payment and the mileage

payment based on the regulation market clearing price the average deployment ratio α.

▪ Payment for additional mileage:

▪ Charge for undeployed mileage:

▪ Total payment:

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Problem formulation

▪ The problem of maximizing revenue from an EES is formulated as an LP optimization problem.

▪ For arbitrage:

▪ For arbitrage and regulation:

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A Case Study

▪ The maximum revenue for arbitrage and frequencyregulation of the 20MW/MWh Li-ion BESS located atHarding Street Generation Station of Indianapolis PowerLight is evaluated.

▪ The optimization problems were formulated using Pyomooptimization modeling language.

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Results

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• The revenue from arbitrage

combined with regulation is much

higher than from arbitrage only.

• The optimal policy is to participate in

regulation market the majority of the

time while maintaining the SOC by

arbitrage.

Conclusions

▪ MISO regulation market has been reviewed.

▪ An LP approach has been used to estimate the revenues of an EES system in MISO for arbitrage only and arbitrage combined with frequency regulation.

▪ Future work would consider the uncertainties of the forecast data and non-linear energy storage model.

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Acknowledgment

▪ We would like to thank Dr. Imre Gyuk, the manager of Energy Storage Program, U.S. Department of Energy for funding this research.

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Questions

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