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| 摘要: |
| 为提高粒子群优化(PSO)算法搜索精度、加快后期收敛速度,提出一种新的PSO算法,即局部随机搜索PSO算法。该算法用于求解电力系统的短期发电优化调度问题时,不仅要求满足电站实际运行中的系统负荷平衡约束,而且要考虑机组爬坡约束、出力限制区约束等非线性约束。给出了局部随机搜索PSO算法的步骤及短期发电优化调度问题求解方法。通过应用所提出的算法和其他文献提出的PSO算法、改进快速进化规划(IFEP)算法对15机系统的优化调度计算相比,证明所提出的算法最优解的发电费用最低,分别减少了3.8%和1%。 |
| 关键词: 短期发电调度,粒子群优化,局部随机搜索,非线性约束 |
| DOI： |
| 分类号:TM744 |
| 基金项目: |
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| Power station short-term generation optimal dispatch based on local random search PSO algorithm |
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CHEN Gonggui
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| Abstract: |
| Local random search PSO (Particle Swarm Optimization) algorithm is presented to improve searching accuracy and accelerate convergence rate in later period,which considers not only the system load equilibrium constraint but also the non-linear constraints in short-term generation optimal dispatch of power stations,such as unit ramp rate and restricted output zone. Its steps and application to short-term generation optimal dispatch are introduced. Compared with other PSO algorithm and IFEP (Improved Fast Evolutionary Programming) algorithm,the solution of short-term generation optimal dispatch calculation for a 15-unit system using local random search PSO reduces 3.8% and 1% of total generation costs respectively. |
| Key words: short-term generation dispatch,particle swarm optimization,local random search,non-linear constraint |
