中文摘要：

以坑口电厂厂级监控信息系统的机组负荷在线优化分配功能模块为应用背景,针对模块所运用的基本粒子群优化算法在优化过程中容易陷入局部收敛、收敛速度慢的缺点,提出一种基于惯性权重非线性减小策略的改进粒子群优化算法,使惯性权重呈对数减小;测试函数仿真结果表明,改进粒子群优化算法在收敛速度和寻优精度方面,优化性能均优于基本粒子群优化算法;通过MATLAB与Visual C＋＋混合编程,开发了机组负荷在线优化分配功能模块,提高了算法的计算效率和工程应用价值.

英文摘要：

This paper took function module of online unit load economic dispatch in plant level supervisory information system for pithead power plant as application background,and an improved particle swarm optimization algorithm was proposed based on strategy of nonlinear reduction in inertia weight for the drawbacks of falling into local convergence easily and slow convergence rate compared to the basic particle swarm optimization algorithm.This improved particle swarm optimization algorithm could make the inertia weight show a logarithmic decrease.Simulation result of test function showed that the improved particle swarm optimization algorithm was better than basic particle swarm optimization algorithm in aspects of convergence rate and accuracy of researching optimal solution.Through admixture programming with MATLAB and Visual C＋ ＋,the function module of online unit load economic dispatch was developed,and this improved computational efficiency and engineering application value.