Batteries in Electricity Markets: Economic Planning and Operations

Abstract

Batteries have been storing electricity for mankind since 1800, while it is till recently that grid-scale battery energy storage become commercially viable and are seeking merchant opportunities in electricity markets. Battery energy storage have faster ramp speed compared to other types of generation units, and are extremely valuable for facilitating the integration of renewable energy resources. Battery energy storage can provide arbitrage and ancillary services in the electricity market. However, even though nowadays battery energy storage systems are constructed and operated with mature technologies, it remains an open question on how to operates them economically in electricity market to maximize the investment profit. This dissertation covers the optimal planning, scheduling, and operation for battery energy storage in electricity markets. It shows that the degradation mechanism of electrochemical battery cells must be considered in market bidding and operation strategies to maximize the participant's operating profit, and proposes optimal methods to incorporate the cost of battery degradation into different participation stages and markets. For frequency regulation markets, this dissertation proposes a real-time control policy that optimally trades-off the performance penalty and the degradation cost in frequency regulation operations. A optimal bidding policy is designed based on the proposed control policy to maximize participant's market profit while maintaining satisfactory operation performance. For energy markets, this dissertation designs a piece-wise linear model that accurately incorporates battery degradation cost into dispatch optimization and bidding strategies. Finally, this dissertation proposes a bi-level planning model to optimize the location and rating of battery energy storage systems considering both energy and reserve markets. This model ensures the profitability of investments in energy storage by enforcing a rate of return constraint. This model is tested on a 240-bus model of the Western Electricity Coordinating Council (WECC) system, and the result analyzes the effects of different storage technologies, rate of return requirements, and regulation market policies on ES participation on the optimal storage investment decisions.