skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Energy storage arbitrage under day-ahead and real-time price uncertainty

Abstract

Electricity markets must match real-time supply and demand of electricity. With increasing penetration of renewable resources, it is important that this balancing is done effectively, considering the high uncertainty of wind and solar energy. Storing electrical energy can make the grid more reliable and efficient and energy storage is proposed as a complement to highly variable renewable energy sources. However, for investments in energy storage to increase, participating in the market must become economically viable for owners. This paper proposes a stochastic formulation of a storage owner’s arbitrage profit maximization problem under uncertainty in day-ahead (DA) and real-time (RT) market prices. The proposed model helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage. Finally, case study results on realistic market price data show that the novel stochastic bidding approach does significantly better than the deterministic benchmark.

Authors:
ORCiD logo [1]; ORCiD logo [2];  [2];  [2];  [2]
  1. Argonne National Lab. (ANL), Lemont, IL (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Argonne National Lab. (ANL), Lemont, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
Argonne National Laboratory - Laboratory Directed Research and Development (LDRD); USDOE
OSTI Identifier:
1358239
Grant/Contract Number:
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: PP; Journal Issue: 99; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; battery storage; plants; energy storage; markets; price arbitrage

Citation Formats

Krishnamurthy, Dheepak, Uckun, Canan, Zhou, Zhi, Thimmapuram, Prakash, and Botterud, Audun. Energy storage arbitrage under day-ahead and real-time price uncertainty. United States: N. p., 2017. Web. doi:10.1109/TPWRS.2017.2685347.
Krishnamurthy, Dheepak, Uckun, Canan, Zhou, Zhi, Thimmapuram, Prakash, & Botterud, Audun. Energy storage arbitrage under day-ahead and real-time price uncertainty. United States. doi:10.1109/TPWRS.2017.2685347.
Krishnamurthy, Dheepak, Uckun, Canan, Zhou, Zhi, Thimmapuram, Prakash, and Botterud, Audun. Tue . "Energy storage arbitrage under day-ahead and real-time price uncertainty". United States. doi:10.1109/TPWRS.2017.2685347. https://www.osti.gov/servlets/purl/1358239.
@article{osti_1358239,
title = {Energy storage arbitrage under day-ahead and real-time price uncertainty},
author = {Krishnamurthy, Dheepak and Uckun, Canan and Zhou, Zhi and Thimmapuram, Prakash and Botterud, Audun},
abstractNote = {Electricity markets must match real-time supply and demand of electricity. With increasing penetration of renewable resources, it is important that this balancing is done effectively, considering the high uncertainty of wind and solar energy. Storing electrical energy can make the grid more reliable and efficient and energy storage is proposed as a complement to highly variable renewable energy sources. However, for investments in energy storage to increase, participating in the market must become economically viable for owners. This paper proposes a stochastic formulation of a storage owner’s arbitrage profit maximization problem under uncertainty in day-ahead (DA) and real-time (RT) market prices. The proposed model helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage. Finally, case study results on realistic market price data show that the novel stochastic bidding approach does significantly better than the deterministic benchmark.},
doi = {10.1109/TPWRS.2017.2685347},
journal = {IEEE Transactions on Power Systems},
number = 99,
volume = PP,
place = {United States},
year = {Tue Apr 04 00:00:00 EDT 2017},
month = {Tue Apr 04 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share:
  • This paper presents a residential thermostat design that enables accurate aggregate load control systems for electricity demand response. The thermostat features a control strategy that can be modeled as a linear time-invariant system for short- term demand response signals from the utility. This control design maintains the same comfort and demand response characteristics of existing real-time price- responsive thermostats but gives rise to linear time-invariant models of aggregate load control and demand response, which facilitates the design of highly accurate load-based regulation services for electricity interconnections.
  • This study investigates the representation of battery degradation in grid level energy storage applications. In particular, we focus on energy arbitrage, as this is a potential future large-scale application of energy storage and there is limited existing research combining the modelling of battery degradation and energy storage arbitrage. We implement two different representations of battery degradation within an energy arbitrage model, and show that degradation has a strong impact on battery energy storage system (BESS) profitability. In a case study using historical electricity market prices from the MISO electricity market in the United States, we find that the achievable netmore » present value (at an interest rate of 10%) for a battery system with a C-rate of 1C dropped from 358 /kWh in the case considering no degradation to 194-314 /kWh depending on the battery degradation model and assumptions for end of life (EOL) criteria. This corresponds to a reduction in revenue due to degradation in the 12-46% range.Furthermore, we find that reducing the cycling of the bat-tery via introducing a penalty cost in the objective function of the energy arbitrage optimization model can improve the profitability over the life of the BESS.« less
  • The volatility of electricity prices is attracting interest in the opportunity of providing net revenue by energy arbitrage. We analyzed the potential revenue of a generic Energy Storage System (ESS) in 7395 different locations within the electricity markets of Pennsylvania-New Jersey-Maryland interconnection (PJM), the largest U.S. regional transmission organization, using hourly locational marginal prices over the seven-year period 2008–2014. Assuming a price-taking ESS with perfect foresight in the real-time market, we optimized the charge-discharge profile to determine the maximum potential revenue for a 1 MW system as a function of energy/power ratio, or rated discharge duration, from 1 to 14more » h, including a limited analysis of sensitivity to round-trip efficiency. We determined minimum potential revenue with a similar analysis of the day-ahead market. We presented the distribution over the set of nodes and years of price, price volatility, and maximum potential arbitrage revenue. From these results, we determined the break even overnight installed cost of an ESS below which arbitrage would be profitable, its dependence on rated discharge duration, its distribution over grid nodes, and its variation over the years. We showed that dispatch into real-time markets based on day-ahead market settlement prices is a simple, feasible method that raises the lower bound on the achievable arbitrage revenue.« less