An efficient bi-objective approach for dynamic economic emission dispatch of renewable-integrated microgrids

Abstract

To overcome the challenges of conventional power systems, such as increasing power demand, requirements of stability and reliability, and increasing integration of renewable energy sources, the concept of microgrids was introduced and is currently one of the most important solutions for solving the mentioned problems. Generally, microgrids have two operating modes, namely grid-connected and islanded modes. Based on the literature and its unique characteristics, the islanded mode is more challenging than the other one. In this paper, a new self-adaptive comprehensive differential evolution (SACDE) algorithm is proposed for solving economic load dispatch (ELD) and combined economic emission dispatch (CEED) problems, achieving optimal power consumption in isolated microgrids. Initially, SACDE is employed for solving the ELD problem as a single-objective function, meaning that the operational cost is just considered as the objective function, and thereby, the resources are scheduled accordingly. Then, a multi-objective platform based on SACDE is also proposed to solve the CEED problem. It means two objective functions, including operational cost and emission, are simultaneously optimized. For evaluating the performance of the proposed method, three different scenarios under various cases are considered. According to the results, when SACDE is employed to solve the single objective function (cost minimization) problem, it has better performance than other methods. In terms of the bi-objective scheme (cost and emission minimization), SACDE is significantly superior to the price penalty factor technique which is frequently used in previous studies.

A Multiobjective Evolutionary Approach for Solving the Multi-Area Dynamic Economic Emission Dispatch Problem Considering Reliability Concerns

“…An adaptive fuzzy particle swarm optimization (AFPSO) algorithm was proposed for the ED problem in two large systems such as 118 and 354 generation units with the aim of reducing loss and generation costs [2]. A new selfadaptive comprehensive differential evolution (SACDE) algorithm was presented for the ED problem to minimize emissions and generation costs [12]. The grasshopper optimization (GO) algorithm was used separately and combined with the Harris Hawks algorithm to solve the combined heat and power ED problems, respectively [3,13].…”