Optimising flexibility procurement in local flexibility markets under stochastic availability of participants

Essayeh, C ORCID: https://orcid.org/0000-0002-4649-4267, Savelli, I and Morstyn, T, 2025. Optimising flexibility procurement in local flexibility markets under stochastic availability of participants. Sustainable Energy, Grids and Networks, 44: 102061. ISSN 2352-4677

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Abstract

Local flexibility markets offer a cost-effective solution to overcome the increasing stress on distribution networks by procuring flexibility from distributed energy resources. However, the assets at the distribution level generally have a certain degree of uncertainty and varying costs for operating flexibly. Therefore, distribution system operators will need new mechanisms to structure flexibility procurement, enabling them to manage the risks associated with uncertain resources effectively. This paper proposes an optimisation-based strategy for the optimal selection of flexibility service providers (FSPs) to contract with for mid- to long-term flexibility provision. The strategy alleviates the conservatism of considering individual uncertainties by condensing all FSPs uncertainties into a single uncertainty constraint at the DSO level. The test cases selected electric vehicles and heat, ventilation and air conditioning systems as examples to demonstrate the effectiveness of the strategy. The optimal selection returns the combination of service providers that will ensure the delivery of the needed flexibility at the least cost, given a desired confidence level. The simulation results demonstrate the effectiveness of the strategy in returning the combination of the most beneficial offers that fulfil the trade-off between costs and reliability while ensuring its robustness in uncertain environments; for all test cases, the actual violation level never exceeds the targeted level, and the DSO consistently procures the required flexibility at the lowest available cost.

Item Type:	Journal article
Publication Title:	Sustainable Energy, Grids and Networks
Creators:	Essayeh, C., Savelli, I. and Morstyn, T.
Publisher:	Elsevier
Date:	17 December 2025
Volume:	44
ISSN:	2352-4677
Identifiers:	Number Type 10.1016/j.segan.2025.102061 DOI 2682700 Other
Rights:	© 2025 the authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	30 Apr 2026 16:07
Last Modified:	30 Apr 2026 16:07
URI:	https://irep.ntu.ac.uk/id/eprint/55631

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