火电厂机组负荷优化分配的混沌粒子群算法分析

摘要

Thermal power plant,according to the performance of the per unit consumption of optimal load distribu-tion,can directly reduce the plant power consumption, effectively meet the needs of enterprise competition and energy-saving emission reduction. Based on this,the verification of the decision algorithm analysis,considering the constraints of the valve point effect and the actual unit,the generating unit load optimization distribution of penalty function mathematical model is established;combining the chaos optimization algorithm and dynamic inertia weight method and particle swarm optimization algorithm,form a more scientific and effective chaotic particle swarm optimi-zation algorithm;using a power plant 3 units of historical data analysis,coal consumption is the biggest decrease of 0.8 t/h,proved the feasibility of the algorithm.%火电厂根据每台机组煤耗性能进行最优负荷分配,能够直接降低全厂供电煤耗,有效适应企业竞争和节能减排的需求。基于此,研究验证其中起决定意义的算法分析,考虑阀点效应和实际机组的约束条件,建立了发电机组负荷优化分配的罚函数数学模型；将混沌优化算法和动态惯性权重法与粒子群算法相结合,形成更为科学有效的混沌粒子群算法；运用某电厂3台机组的历史数据进行验证分析,煤耗最大降低0.8 t/h,证明了算法的实际可行性。