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An Application of Craziness based Shuffled Frog Leaping Algorithm for Wind-Thermal Generation Dispatch considering Emission and Economy

机译:基于疯狂的混血蛙跳跃算法考虑发射经济的风热发电派遣

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Wind power is developing rapidly all around the world and at present total installed capacity is about 120,000 MW. Due to continuous improvements in turbine efficiency and increasing fuel prices, wind power is becoming economically competitive compared to conventional power generation. Combined economic/emission dispatch (CEED) involves the simultaneous optimization of two conflicting objectives namely fuel cost and emission. This paper proposes an application of four different types of optimization algorithms such as particle swarm optimization based on constriction factor, craziness based particle swarm optimization, shuffled frog leaping and craziness based shuffled frog leaping algorithm (CRSFL) to an environmental and economic dispatch problem considering wind integrated power system. The necessary operating point that gives the best compromise solution between cost and emission is determined for 10-unit and 40-unit system with valve point effect and different penetration levels of wind power. The test results consistently show that the CRSFL algorithm yields best results compared to other evolutionary algorithms.
机译:风力发展迅速全球发展,目前总装机容量约为12万兆瓦。由于涡轮机效率的不断提高,燃料价格越来越大,与传统发电相比,风电变得经济上具有经济竞争力。合并的经济/排放调度(CEED)涉及同时优化两种冲突目标,即燃料成本和排放。本文提出了四种不同类型的优化算法,如粒子群优化,基于收缩因子,基于疯狂的粒子群优化,随着呼吸的环境和经济调度问题,随着疯狂的跨越和基于疯狂的混血青蛙跳跃算法(Crsfl)考虑风的环境和经济调度问题集成电力系统。在具有阀点效应和风电的不同穿透水平的10单元和40单元系统中确定了在成本和发射之间提供最佳折衷解决方案的必要操作点。测试结果始终如一地表明,与其他进化算法相比,CRSFL算法产生最佳结果。

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