Salt River Project 2015-2016: Quantifying the Benefits and Optimal Use of Battery Storage for SRP and Solar Customers with Demand Charges

Project Description:

In this project, we determine the value of battery storage to SRP and to SRP solar customers subject to demand charges. For customers, we compute the optimal charge/discharge profiles and calculate the net economic benefit of battery storage - illustrating how demand charges increase the economic benefit of battery storage for solar customers. For SRP, we develop a unified economic model detailing how battery storage affects the costs of daily power generation, including spinning reserves, frequency regulation, market pricing/arbitrage, unit commitment, and deferral of investments. Using optimization algorithms, market prediction, load projections, and weather forecasts, we determine the optimal daily charge/discharge profile of the battery and the associated economic benefit of the battery. Finally, we integrate these algorithms into software for use at SRP in planning and operation of battery storage devices.

Project Duration:


Project Personnel:

Matthew M. Peet (PI), Arizona State University
Reza Kamyar (PhD), Arizona State University

SRP Collaborators:

Robert Hess, Power Generation Services (SRP)
Brady Conrad, Power Generation Services (SRP)

Software Products:

Optimal Battery Programmer for Consumers with Support for Demand Charges. (Self-Installing Executable)

Introduction: A Self-installing Utility for determining the optimal charge-discharge plan for a residential customer possibly subject to demand charges using customizable historic monthly usage data, pricing information, and battery specs. See Readme.pdf for installation instructions.

[Optimal_Battery_Programmer] - Self-Installing executable. Email for source code.

Utility Battery Programmer (Self-Installing Executable)

Introduction: A self-installing executable for determining the optimal charge-discharge plan using customizable load data and cost estimates. See Readme.pdf for installation instructions.

[] - Access Restricted to academic use. Email for availability.

Associated Publications at ASU:

Student Theses:

Reza Kamyar (PhD), Arizona State University
Parallel Optimization of Polynomials for Large-Scale Problems in Stability and Control
Defended January, 2016.
Thesis - [arXiv:math] [.pdf] [.ps]

Defense Talk -
[.pdf] [.ps]

Journal Publications:

R. Kamyar and M. M. Peet
Optimal Thermostat Programming for Peak and Time-of-Use Pricing Plans with Thermal Energy Storage and Implications for Regulated Utilities
Submitted to IEEE Transactions on Power Systems.
[arXiv] [.pdf] [.ps]

CDC/ACC Conference Publications:

R. Kamyar and M. Peet
A Multi-objective Approach to Optimal Energy Storage for Residential Customers in The Presence of Demand Charges
Submitted to the 55th IEEE Conference on Decision and Control. Las Vegas, NV. December 12-14, 2016.
[arXiv] [.pdf] [.ps] [slides]

R. Kamyar and M. Peet
The effect of Distributed Thermal Storage on Optimal Pricing and Optimal Thermostat Programming in a Regulated Smart Grid
American Control Conference. Chicago, IL. July 1-3, 2015.
[arXiv] [.pdf] [.ps] [slides]