Minimum emission dispatch in an integrated thermal and wind energy conservation system using self-adaptive differential evolution

S. S. Reddy, J. Momoh
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引用次数: 4

Abstract

This paper solves an optimization problem to minimize the emission due to carbon oxides, nitrogen oxides and sulfur oxides with cost as a constraint for a wind-solar-thermal power system. Wind and solar energy can reach significant penetration in modern power system and they will introduce additional uncertainties. Market price is mainly influenced by the generating fuel cost, as the wind and solar power being environmental friendly need to be utilized in optimum. But, the intermittency of wind and solar power affects the system operation. In such uncertain environment, the decision to be taken should be reasonable, economical and not risky. Under this regime the System Operator should be aware of wind and solar uncertainty and schedule the renewable power accordingly. This paper depicts the trade-off between the cost and emission minimization objectives for the wind-solar-thermal power system using the Self Adaptive Differential Algorithm (SADE). The effectiveness of the proposed approach is tested on IEEE 30 bus test system with wind farms located at different buses.
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基于自适应差分进化的热风集成节能系统最小排放调度
本文以成本约束为约束条件,解决了以最小化碳氧化物、氮氧化物和硫氧化物排放为目标的风-光热发电系统优化问题。风能和太阳能在现代电力系统中具有重要的渗透作用,同时也会带来额外的不确定性。市场价格主要受发电燃料成本的影响,因为风能和太阳能是环保的,需要得到最优的利用。但是,风能和太阳能发电的间歇性影响了系统的运行。在这种不确定的环境下,所做的决定应该是合理的、经济的、没有风险的。在这种制度下,系统运营商应该意识到风能和太阳能的不确定性,并相应地安排可再生能源。本文用自适应微分算法(SADE)描述了风-光热发电系统成本与排放最小化目标之间的权衡。在IEEE 30总线测试系统上对该方法的有效性进行了测试,并对不同总线上的风电场进行了测试。
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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