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Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue

Marcos Tostado-Véliz, Hany M. Hasanien, Ahmad Rezaee Jordehi, Rania A. Turky and Francisco Jurado

Applied Energy, 2023, vol. 339, issue C, No S0306261923003240

Abstract: The massive integration of renewable generators, energy storage systems, and demand response requires the development of smart power infrastructures. In this upcoming context, microgrids will be essential for the optimal integration of such assets. When different microgrids are located near each other, they can be centrally coordinated within a novel paradigm called Microgrid Cluster. In such structures, the microgrids involved can collaborate in a cooperative way or compete by developing internal market structures. This paper develops a novel optimal bidding strategy for a demand response-intensive microgrid partaking in competitive clusters. The new proposal is envisaged as a three-stage methodology that aims at reducing the effects of response fatigue. Uncertainties related to inflexible demand and renewable generation are modeled via scenarios, while the risk associated with uncertain parameters is handled by enforcing the Conditional Value at Risk. The resulting computational tool is effective and tractable, as shown in the results obtained on a benchmark three-microgrids cluster. Indeed, the developed methodology is able to reduce the total response signals by 88 % in some cases. Moreover, this case study allows analyzing the effect of response fatigue minimization in the overall cluster performance, showing that the collective welfare can be reduced by 32 % when response fatigue is taken into account.

Keywords: Demand response; Microgrid cluster; Response fatigue; Risk-averse optimization; Stochastic programming (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.apenergy.2023.120960

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