Dynamic Economic Emission Dispatch problem with valve-point effect

C. Rani, D. Kothari
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引用次数: 5

Abstract

The advancement in power systems has led to the development of Dynamic Economic Emission Dispatch (DEED)that is difficult to solve by classical optimization method. The proposed paper work is to evolve a simple and effective method for an optimum generation dispatch to minimize the fuel cost and emission of power networks. This paper presents a Chaotic Self Adaptive Particle Swarm Optimization (CSAPSO) algorithm to solve DEED problem. Many non-linear characteristics of the generator such as value point effect, non smooth cost functions of fuel and emission and ramp rate limits are considered in this proposed method. The cost function of the generator exhibits the non convex characteristics, as the valve point effects are modeled and imposed as rectified sinusoid components. The velocity, which is popularly known as sensitive parameter of CSAPSO is adjusted dynamically in order to increase its precision. A chaotic local search operator is introduced in the proposed algorithm to avoid premature convergence. The effectiveness of the proposed optimization is verified in simulation studies using MAT LAB software. In this proposed work, fuel cost and emission are treated as competing objectives. The applicability and high feasibility of the proposed method is validated on 10 unit test systems. Results of the application of the proposed method are presented in this reported work.
具有阀点效应的动态经济排放调度问题
随着电力系统的发展,传统优化方法难以解决的动态经济排放调度问题得到了发展。提出了一种简单有效的优化发电调度方法,使电网的燃料成本和排放最小化。提出了一种混沌自适应粒子群优化算法(CSAPSO)来解决契约问题。该方法考虑了发电机的许多非线性特性,如值点效应、燃料和排放的非光滑成本函数以及斜坡速率限制。当阀点效应被建模并作为整流正弦分量施加时,发电机的成本函数表现出非凸特性。为了提高CSAPSO的精度,对通常被称为敏感参数的速度进行动态调整。为了避免算法过早收敛,在算法中引入了混沌局部搜索算子。利用MAT LAB软件进行了仿真研究,验证了该优化方法的有效性。在这项拟议的工作中,燃料成本和排放被视为竞争目标。在10个单元测试系统上验证了该方法的适用性和高可行性。本文给出了该方法的应用结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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