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An Improved Binary Particle Swarm Optimization For Unit Commitment Problem

机译:机组组合问题的改进二进制粒子群算法

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This paper proposes a new improved binary PSO (IBPSO) method to solve the unit commitment (UC) problem, which is integrated binary particle swarm optimization (BPSO) with lambda-iteration method. The IBPSO is improved by priority list based on the unit characteristics and heuristic search strategies to repair the spinning reserve and minimum up/down time constraints. To verify the advantages of the IBPSO method, the IBPSO is tested and compared to the other methods on the systems with the number of units in the range of 10-100. Numerical results demonstrate that the IBPSO is superior to other methods reported in the literature in terms of lower production cost and shorter computational time.
机译:本文提出了一种新的改进的二进制PSO(IBPSO)方法,用于解决单元承诺(UC)问题,该方法是将Lambda迭代方法与二进制粒子群优化(BPSO)集成在一起。通过基于设备特性和启发式搜索策略的优先级列表对IBPSO进行了改进,以修复纺纱储备和最小的上/下时间限制。为了验证IBPSO方法的优势,对IBPSO进行了测试,并将其与系统上其他方法(单位数量在10-100之间)进行了比较。数值结果表明,IBPSO在降低生产成本和缩短计算时间方面优于文献中报道的其他方法。

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