Incorporating Non-Convex Operating Characteristics into Bi-Level Optimization Electricity Market Models

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Bi-level optimization constitutes the most popular mathematical methodology for modeling the deregulated electricity market. However, state-of-the-art models neglect the physical non-convex operating characteristics of market participants, due to their inherent inability to capture binary decision variables in their representation of the market clearing process, rendering them problematic in modeling markets with complex bidding and unit commitment (UC) clearing mechanisms. This paper addresses this fundamental limitation by proposing a novel modeling approach enabling incorporation of these non-convexities into bi-level optimization market models, which is based on the relaxation and primal-dual reformulation of the original, nonconvex lower level problem and the penalization of the associated duality gap. Case studies demonstrate the ability of the proposed approach to closely approximate the market clearing solution of the actual UC clearing algorithm and devise more profitable bidding decisions for strategic producers than the state-of-theart bi-level optimization approach, and reveal the potential of strategic behavior in terms of misreporting non-convex operating characteristics.
Original languageEnglish
JournalIEEE Transactions on Power Systems
Number of pages13
ISSN0885-8950
DOIs
Publication statusAccepted/In press - 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Bi-level optimization, Electricity markets, Non- convexities, Strategic bidding, Unit commitment

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