Efficient demand response location targeting for price spike mitigation by exploiting price-demand relationship

Yufan Zhang, Honglin Wen, Tao Feng and Yize Chen

Applied Energy, 2024, vol. 376, issue PA, No S0306261924015241

Abstract: Demand response (DR) leverages demand-side flexibility, offering a promising approach to enhance market conditions like mitigating wholesale price spikes. However, poorly chosen DR locations can inadvertently increase electricity prices. For that, we introduce a method to rigorously select DR locations and corresponding demand reductions. We formulate a bilevel program where the upper level determines the DR locations and demand reductions while ensuring the average nodal prices meet a predetermined target. The lower level tackles an economic dispatch (ED) problem and feeds the resulting nodal prices back to the upper level based on post-DR demands. This bilevel formulation presents challenges due to the lower-level non-convexity affecting the upper-level constraints on average nodal prices. To address this, we propose to replace the lower level with a piecewise linear function representing the price-demand relationship, solving iteratively for each linear segment. This results in a tractable mixed-integer linear program. An acceleration strategy is proposed to further reduce the computation time. Numerical studies demonstrate the ability of the proposed approach to reduce prices to a desired level. Besides, we empirically show that the proposed approach is robust against inaccurate system parameters and can reduce computation time by over 50%.

Keywords: Demand response; Price spike; Price-demand relationship; Multi-parametric programming (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.124141

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