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A novel metaheuristic strategy for energy pricing in active distribution networks and microgrids

机译:主动配电网和微电网中能源定价的新型元启发式策略

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A fair energy pricing method in distribution networks using distributed energy resources (DERs) is presented in this paper. The pricing procedure is modeled in the form of the optimization problem. The objectives of this problem are total emission and network loss. The feasible region of the problem is determined with the aforementioned objectives, locational marginal prices and power factors of DERs as decision variables. In the recommended method, the loss/emission reduction is implemented by the generation of the DERs. furthermore, the profits of loss/emission reduction are allocated between DERs. In this way, more contribution consequent to more production leads to a higher price for DERs in comparison to the predefined market price. Given the nature of the problem, which has two objectives, a Group Search Optimization is employed with Chaotic search and Covariance matrix as a Multi-Objective problem (MGSOACC) to solve the pricing problem. Due to the validation of the proposed algorithm, a comparison between MOPSO, MOPSO-DFR, MOGA, and NSGA-II is applied consequently. In addition, the proposed method allows the decision-makers to apply their preferences among loss/emission reduction and IDSO's benefit. Additionally, in order to evaluate the proposed method, the pricing procedure is implemented on IEEE-32 bus test network.
机译:本文提出了一种使用分布式能源(DER)的配电网络中公平的能源定价方法。定价过程以优化问题的形式建模。此问题的目标是总发射和网络损耗。问题的可行区域由上述目标,位置边际价格和DER的功率因数作为决策变量来确定。在推荐的方法中,损耗/排放的减少是通过生成DER来实现的。此外,减少损失/排放的利润在DER之间分配。以这种方式,与预定的市场价格相比,由于产量增加而产生的更多贡献导致DER的价格更高。考虑到具有两个目标的问题的性质,采用混沌搜索和协方差矩阵作为多目标问题(MGSOACC)的组搜索优化来解决定价问题。由于该算法的有效性,因此对MOPSO,MOPSO-DFR,MOGA和NSGA-II进行了比较。另外,所提出的方法允许决策者在减少损耗/排放和IDSO的收益中应用他们的偏好。此外,为了评估所提出的方法,在IEEE-32总线测试网络上实施了定价程序。

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