Understanding and managing the participation of batteries in reserve electricity markets

Nastaran Naseri, Yashar Ghiassi-Farrokhfal, Wolf Ketter, John Collins

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The proliferation of variable renewable energy increases the significance of reserve markets, which provide energy flexibility to compensate for supply–demand mismatches on short notice. Accordingly, market regulators in different locations have been continuously adopting different mechanisms to attract flexible sources, such as batteries to participate in reserve markets. While these mechanisms are different and sometimes contradictory, there is no consensus on their effectiveness. Therefore, there is a dire need to examine their effectiveness systematically. This paper proposes a model-driven decision support system, focusing on regulators’ perspectives, assisting them in evaluating the effectiveness of different market mechanisms for attracting batteries in reserve electricity markets. We formulate the problem as a stochastic Mixed-Integer-Linear-Program, incorporating practical restrictions and applicable to many electricity markets. As an example, we apply our model to the case of the German electricity market to evaluate some market mechanisms. We find that although some reserve markets do not allow separate bidding in charging and discharging directions (asymmetric bidding), this seems to be an effective mechanism to attract battery operators. When asymmetric bidding is allowed, battery operators often optimally choose to reserve their capacity only in the charging direction and use the discharging direction in energy markets, taking opposite seller/buyer roles in energy and reserve markets. Our results also advocate mechanisms such as remunerating the activated energy and shifting the gate closure closer to the time of operation. In contrast, some existing rewarding mechanisms designed for flexible resources do not seem to be very effective.
Original languageEnglish
Article number113895
JournalDecision Support Systems
Volume165
DOIs
Publication statusPublished - Feb 2023

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© 2022 Elsevier B.V.

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