Universität zu Köln

Naseri, Nastaran, Ghiassi-Farrokhfal, Yashar, Ketter, Wolfgang and Collins, John ORCID: 0000-0002-7881-4595 (2023). Understanding and managing the participation of batteries in reserve electricity markets. Decis. Support Syst., 165. AMSTERDAM: ELSEVIER. ISSN 1873-5797

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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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Naseri, Nastaran UNSPECIFIED UNSPECIFIED UNSPECIFIED Ghiassi-Farrokhfal, Yashar UNSPECIFIED UNSPECIFIED UNSPECIFIED Ketter, Wolfgang UNSPECIFIED UNSPECIFIED UNSPECIFIED Collins, John UNSPECIFIED orcid.org/0000-0002-7881-4595 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-678682
DOI:	10.1016/j.dss.2022.113895
Journal or Publication Title:	Decis. Support Syst.
Volume:	165
Date:	2023
Publisher:	ELSEVIER
Place of Publication:	AMSTERDAM
ISSN:	1873-5797
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language ENERGY-STORAGE SYSTEMS; OPERATION; SERVICES; MODEL Multiple languages Computer Science, Artificial Intelligence; Computer Science, Information Systems; Operations Research & Management Science Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/67868