摘要
负荷优化分配是火电厂运行优化的一个重要研究领域,在机组之间合理地优化分配负荷能够提高整个火电厂运行的经济性。针对火电厂实际的运行情况,考虑多个实际约束条件,建立了并行火电机组间连续多时段动态负荷优化分配的数学模型;提出运用新近发展起来的智能算法-粒子群算法来解决动态负荷优化分配问题,详细介绍和研究了该算法的基本原理以及在负荷优化分配问题上的实现过程,并针对原算法的不足,对算法进行了改进;根据负荷分配和算法的特性,对初始种群的生成方法进行了改进,同时对约束条件进行了有效处理。仿真实例表明,该方法收敛性好,收敛速度快,能够有效地达到或接近全局最优,从而为火电厂机组负荷优化分配的求解提供了新的有效算法。
Optimal load dispatch is one of the important research fields in optimization operation of thermal power plant, and optimal load dispatch among the various units can enable the whole power plant to get the best benefit. A dynamic optimal load dispatch mathematical model was constructed considering the practical constraints and sequential optimal load dispatch among parallel thermal power units. A new intelligent approach using particle swarm algorithm to solve the problem of dynamic optimal load dispatch was proposed. The basic theory and the implementation method of the algorithm in optimal load dispatch problem were studied in detail. Some measures were applied to improve the algorithm in order to avoid its weakness; According to the special features of load dispatch and the algorithm, the way of generating the initial generation was improved; at the same time, constraints were processed effectively. The simula tion showed that the method had good convergence high convergence speed, and could achieve the whole optimiza tion more efficiently or could be more close to it. It was a new effective optimization algorithm for solving optimal load dispatch among thermal power units.
出处
《现代电力》
2006年第1期52-56,共5页
Modern Electric Power
关键词
火电厂
运行优化
动态负荷优化分配
粒子群算法
收敛性
thermal power plant
optimization operation
dynamic optimal load dispatch
particle swarm algorithm
convergence
