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Unit Commitment Using Particle Swarm-Based-Simulated Annealing Optimization Approach

机译:基于粒子群模拟退火优化方法的机组组合

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In this paper, a new approach based on hybrid particle swarm-based-simulated annealing optimization (PSO-B-SA) for solving thermal unit commitment (UC) problems is proposed. The PSO-B-SA presented in this paper solves the two sub-problems simultaneously and independently; unit-scheduled problem that determines on/off status of units and the economic dispatch problem for production amount of generating units. Problem formulation of UC is defined as minimization of total objective function while satisfying all the associated constraints such as minimum up and down time, production limits and the required demand and spinning reserve. Simulation results show that the proposed approach can outperform the other solutions.
机译:本文提出了一种基于混合粒子群模拟退火优化(PSO-B-SA)的新方法来解决热机组承诺(UC)问题。本文提出的PSO-B-SA可以同时且独立地解决两个子问题。决定机组开/关状态的机组调度问题和发电机组生产量的经济调度问题。 UC的问题表述被定义为在满足所有相关约束(例如最小上,下限时间,生产限制以及所需需求和旋转储备)的同时,使总目标函数最小化。仿真结果表明,该方法优于其他方法。

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