| 引用本文: | 李 勇,王建君,曹丽华.基于繁殖粒子群算法的火电厂负荷优化分配[J].电力自动化设备,2012,32(4): |
| LI Yong,WANG Jianjun,CAO Lihua.Optimal load dispatching based on breeding particle swarm optimization algorithm for thermoelectric power plant[J].Electric Power Automation Equipment,2012,32(4): |
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| 摘要: |
| 针对目前火电厂负荷优化分配的问题，提出了负荷优化分配总时间的概念，并给出了具体计算公式。在标准粒子群优化算法中引入遗传算法中的杂交思想，提出了基于繁殖粒子群优化算法的负荷优化分配方法，并引入自适应惯性权重对算法进行了改进，避免了标准粒子群算法易陷入局部最优及遗传算法优化计算时间长的缺点。对算法应用在负荷优化分配中的具体问题进行了分析处理，缩短了优化计算时间，提高了算法精度。实例分析进一步验证了所提方法的有效性以及现场实用性，能够同时满足火电厂对降低成本及电网调度对负荷优化分配总时间的硬性要求。 |
| 关键词: 火电厂 负荷分配 优化 繁殖粒子群优化算法 遗传算法 实例分析 降低成本 |
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| 基金项目:吉林省科技发展计划资助项目（20080523） |
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| Optimal load dispatching based on breeding particle swarm optimization algorithm for thermoelectric power plant |
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LI Yong, WANG Jianjun, CAO Lihua
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School of Energy and Power Engineering，Northeast Dianli University，Jilin 132012，China
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| Abstract: |
| The concept of total optimal load dispatch time is proposed for the optimal load dispatch of power plant and its calculation formula is presented. The optimal load dispatch based on BPSO（Breeding Particle Swarm Optimization） algorithm is proposed，which combines the interbreeding of GA（Genetic Algorithm） with the standard PSO（Particle Swarm Optimization） algorithm and applies the adaptive inertial weight to avoid the local optimum of PSO and heavy calculation load of GA. Its application issues in optimal load dispatch is analyzed and treated to reduce the calculation time and improve the algorithm accuracy. Its effectiveness and on-site applicability are further verified by a case study,?meanwhile,?it?can?meet?the?needs?of cost?reduction?for?power?plant?and?the?demand?of?total?time?of?optimal?load?dispatching?for?power?network?dispatching. |
| Key words: thermoelectric power plants electric load dispatching optimization BPSO algorithm genetic algorithms example analysis cost reduction |
