Abstract
The increasing penetration of distributed renewable generation and the electrification of end uses are making flexibility procurement a critical requirement for distribution system operators (DSOs). This has led to the emergence of local flexibility markets (LFMs) across several countries, where DSOs procure active power regulation services through technology-neutral competitive auctions. This paper presents an optimization framework based on mixed-integer linear programming to determine the optimal power capacity that a user should reserve when participating in a LFM. The model explicitly accounts for the electricity bill structure and enables the joint provision of explicit and implicit flexibility. The proposed approach is applied to a real multi-energy microgrid participating in the LFM established by Unareti within the MiNDFlex pilot project, where the DSO conducts monthly forward auctions to secure upward flexibility capacity. Results show that, in the absence of a battery energy storage system, participation in the market is not economically viable, as the revenues from flexibility services fail to offset the increase in electricity consumption and associated bill components. Conversely, when storage is available, participation becomes profitable: under average October 2025 auction prices for reserve availability (475.5 k€/MW/y) and service activation (57.6 €/MWh), the configuration with storage achieves a net economic gain of 31.8 k€ per month. These findings highlight the importance of accounting for implicit flexibility signals embedded in electricity tariffs and the pivotal role of storage in enhancing the economic profitability of participation in LFMs.
Keywords local flexibility, optimization, scheduling, distributed energy resources, microgrid, bidding strategy
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Energy Proceedings