Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration
Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration
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DOI：
10.1016/j.ijepes.2012.06.049
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发表时间：
2013
影响因子：
5.2
通讯作者：
Soumitra Mondal;A. Bhattacharya;S. Dey
中科院分区：
文献类型：
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作者：
Soumitra Mondal;A. Bhattacharya;S. Dey
在本文中，经济排放负荷分配（EELD）问题的解决，以尽量减少氮氧化物（NOX）的排放量和燃料成本，同时考虑火电机组和风力发电机组。本文还研究了风力发电对NOx排放的影响。为了找到最佳的排放分配，最佳的燃料成本，最佳的妥协排放和燃料成本，一个新开发的优化技术，称为引力搜索算法（GSA）已被应用。GSA是基于牛顿定律的重力和质量的相互作用。在GSA中，粒子群是一组质量的集合，它们利用重力和牛顿运动定律相互作用。IEEE 30节点系统有六个传统的热发电机已被视为测试系统。在系统的两个弱负荷母线上还布置了两台额外的风力涡轮机。两个弱负载总线已被选择的基础上，他们的L指数值。在放置风力发电电源后，这些母线被视为发电机母线。最小燃料成本，最小排放量和最佳折衷的解决方案，GSA与基于地理的优化（BBO）进行了比较。结果表明，GSA在解的质量和计算效率方面优于其他可用的技术。
In this paper an economic emission load dispatch (EELD) problem is solved to minimize the emission of nitrogen oxides (NOX) and fuel cost, considering both thermal generators and wind turbines. The effects of wind power on overall NOXemission are also investigated here. To find the optimum emission dispatch, optimum fuel cost, best compromising emission and fuel cost, a newly developed optimization technique, called Gravitational Search Algorithm (GSA) has been applied. GSA is based on the Newton’s law of gravity and mass interactions. In GSA, the searcher agents are collection of masses which interact with each other using laws of gravity and motion of Newton. IEEE 30-bus system having six conventional thermal generators has been considered as test system. Two extra wind turbines are also placed at two weak load bus of the system. Two Weak load buses have been selected based on their L-index value. After placing the wind power sources, those buses have been considered as generator bus. Minimum fuel cost, minimum emission and best compromising solution obtained by GSA are compared with those of biogeography-based optimization (BBO). The results show that the GSA surpasses the other available techniques in terms of solution quality and computational efficiency.