An incentive-based policy on minimization of GHG emissions and loss using adaptive group search multi-objective optimization algorithm

A transactive strategy for purposeful pricing of Distributed Energy Resources (DERs) in distribution networks is proposed in this paper. This strategy is presented as a novel heuristic optimization approach. Reduction of both total network loss and released greenhouse gases (GHGs) emissions can be considered as the intended objective functions. In addition, Locational Marginal Pricing (LMPs) and power factors associated with DERs are considered as decision variables. Each DER, which is more involved in the mitigation of the aforementioned objectives, gives rise to greater benefits in the long term. Therefore, such a contribution to greater generation on a large scale leads to the higher price of using DER bus than substation market price. Also, the benefits earned from loss/emission mitigation are allocated to DERs directly. The fairness of this pricing process is supervised by the Independent Distribution System Operator (IDSO). Given that the problem has two contradictory objective functions, a reliable Multi-objective Group Search Optimization utilizing Covariance matrix and Chaotic search (MGSOACC) is proposed to solve the problem. To evaluate the viability of the proposed method, the pricing procedure is applied to modified IEEE-33 and IEEE-69 bus test networks. Furthermore, to validate the proper functionality of the proposed optimization method, result-oriented comparisons between four conventional multi-objective optimization methods and the proposed optimization method are made. (C) 2022 Sharif University of Technology. All rights reserved.