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fitness
- 基于粒子群算法的微电网优化调度，在运行成本最小，环境友好的条件下，优化发电单元的出力-Based on Particle Swarm Optimization microgrid scheduling, running costs are minimized, environmentally friendly conditions, optimize power generation unit output
MATLABIEEE33PSO
- 用于实现IEEE33节点配电网系统中接入5个微电网的最优注入功率优化，使用粒子群算法实现。-Used to achieve access to the IEEE33 5 node distribution network system in micro grid optimal injection power optimization, using particle swarm algorithm
liziqun.
- 基于粒子群算法，实现一个微电网多目标优化运行-Based on particle swarm algorithm, a micro-grid multi-objective optimization operation is realized
2
- 配电网采用二进制粒子群算法进行重构，同时使用普通粒子群算法对接入的DG注入功率进行优化(The distribution network adopts binary particle swarm algorithm to refactor, and the DG injection power is optimized by using the general particle swarm algorithm)
micro-grid based on CSO
- 本文分析微网中微电源包括光伏发电、风力发电、微燃机、柴油发电机和燃料电池的电气特性，构建微电网优化运行的模型，以微网的经济成本和环境成本最小为目标函数，充分考虑了电压越限、功率平衡、微电源出力限制等约束条件，应用鸡群算法进行求解。 解决了粒子群算法易早熟、易陷入局部最优解的问题。并通过典型的微网系统进行仿真分析，仿真结果验证了该算法的有效性。(In this paper, the electrical characteristics of micro-power sources in micro
微电网容量优化
- 用蒙特卡洛算法模拟风机及光伏出力，并用粒子群算法加以分配优化。(Monte Carlo algorithm is used to simulate the output of wind turbine and photovoltaic, and particle swarm optimization algorithm is used to optimize the distribution.)