Energy storage (ES) is playing a vital role in providing multiple services in several electricity markets. However, the benefits and risks vary across markets and time, which justifies the importance to optimize ES capacity share in different markets. In this paper, a novel portfolio theory-based approach is proposed for optimally managing ES in various markets to maximize benefits and reduce the risk for ES owners. Three markets are considered, which are energy arbitrage, ancillary services, and distributed network operator's market. They are modeled based on energy cost, frequency response cost, and system congestion cost. Portfolio theory is utilized to quantify ES capacity allocated to each market over time for various levels of risk aversions. The relation between risks and expected return of different markets is efficiently reflected by the portfolio theory, providing implications to storage operation. The extensive demonstration illustrates that the markets that storage can participate in are fundamentally different regarding to its risk aversion. In addition, the optimum portfolio of the markets for storage is on the efficient frontier, providing the maximum return at a certain risk aversion level. This study is particularly useful for guiding market participation and operation of ES to gain maximum economic return at minimum risk.
- Ancillary market
- distributed network operator's (DNO's) market
- electricity market
- energy storage (ES)
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
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- Department of Electronic & Electrical Engineering - Professor
- Centre for Sustainable Power Distribution
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Doctoral Training in Decarbonisation of the Built Environment (dCarb)
Person: Research & Teaching