基于JAYA算法的微电网排放约束经济负荷调度问题求解

Motilal Bhoye, M. Pandya, S. Valvi, I. Trivedi, Pradeep Jangir, Siddharth A. Parmar
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引用次数: 38

摘要

在这项工作中,分布式能源(DERs)被用于一个特定的小区域,即微电网。微电网由配电发电机组、太阳能发电机组、风力发电机组等微源和不同负荷组成。针对微电网中能源管理系统存在的联合经济排放调度问题,采用元启发式技术对其进行优化。CEED是调度发电机组在其范围内,同时最小化燃料成本和排放值的过程。在MATLAB环境下,应用JAYA算法求解CEED问题。对包括在内的所有源,总成本和总排放量均达到最小。结果表明,在无排放和有排放两种情况下,JAYA算法与梯度法(GM)、蚁群优化(ACO)和粒子群优化(PSO)技术进行了比较。计算了24小时不同的电力需求。与遗传算法、蚁群算法和粒子群算法相比,JAYA算法的成本降低效果较好,表明了该算法的有效性。本文的主要目标是解决CEED问题,以获得最优的系统成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An emission constraint Economic Load Dispatch problem solution with Microgrid using JAYA algorithm
In this Work, the Distributed Energy Resources (DERs) are used in a specific small area which is known a microgrid. Microgrid consists of microsources like distribution generator, solar and wind units, etc., and different loads. In the microgrid, the energy management system (EMS) having a problem of Combined Economic Emission Dispatch (CEED) and it is optimized by meta-heuristic techniques. The CEED is the procedure to scheduling the generating units within their bounds together with minimizing the fuel cost and emission values. The JAYA Algorithm is applied for the solution of CEED problem in the MATLAB environment. The minimization of total cost and total emission are obtained for all sources included. The result shows the comparison of JAYA Algorithm with the Gradient Method (GM), Ant Colony Optimization (ACO) and Particle Swarm Optimizer (PSO) technique for the two different cases which are Economic Load Dispatch (ELD) without emission and with emission. The results are calculated for different power demand of 24 hours. The results obtained with JAYA Algorithm gives comparative better cost reduction as compared to GM, ACO and PSO which shows the effectiveness of the given algorithm. The key objective of this work is to solve the CEED problem to obtained optimal system cost.
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