A multi-agent optimal bidding strategy in microgrids based on artificial immune system

Xiangyu Kong, Dehong Liu, Jie Xiao and Chengshan Wang

Energy, 2019, vol. 189, issue C

Abstract: The utilization of distributed energy resources (DERs) is growing worldwide, and the commercial prospects of microgrids (MGs) are clear. To optimally coordinate the power outputs of DERs owned by different owners while considering uncertainties in the commercial MG, a multi-agent optimal bidding strategy based on the artificial immune system (AIS) is proposed. The method takes the multi-agent system (MAS) control structure of the MG, distributing the profits of different owners through the market mechanism to conduct the optimization. A novel AIS is established and integrated into the MAS to help DERs participate in the optimal bidding operation of MG. The antigen is transformed by the environmental information, the price of the main grid, other DERs’ bidding strategies, and the predicted deviation coefficient while accounting for the uncertainties of DER facilities, which is solved by AIS to find the optimal bidding strategy. A mixed-integer programming model is solved by the bidding manager agent to get bidding results, which are fed back to the DERs to help them form the next round of strategies until the result reaches the equilibrium. Results show that the proposed method is efficient in coordinating the power generation with uncertainty and maximizing the interests of each investor.

Keywords: Microgrid; Distributed energy; AIS; Bidding; Power market (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:189:y:2019:i:c:s0360544219318493

DOI: 10.1016/j.energy.2019.116154

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