计及风力发电风险的电力系统多目标动态优化调度

为解决风电的随机性给电力系统调度带来的问题，引入负荷预测误差和风速的概率分布函数来建立负荷及风电功率的随机性模型。基于对负荷及风电功率随机性模型的深入分析，对风电接入将导致系统维持稳定运行的成本增加风险加以考虑。并在约束条件中引入失负荷及风电浪费风险指标，构建计及风力发电风险的电力系统多目标优化调度模型，以实现系统总污染排放量最少和运行成本最低的综合优化目标。采用一种新颖的蝙蝠算法对模型进行求解，并对蝙蝠算法的不足之处进行了改进，有效地解决了该算法迭代后期收敛慢、易陷入局部极值等问题。以含大规模风电并网电力系统为例进行环境经济调度仿真，验证了所提模型及算法的有效性，并进一步分析了相关参数对含风电并网电力系统优化调度的影响。

Multi-objective dynamic optimal scheduling of power system considering wind power risk

In order to solve the problem caused by the randomness of the wind power system, the load forecasting error and the probability distribution function of wind speed are introduced to establish the stochastic model of the load and wind power. Based on the in-depth analysis of the load and the random model of wind power, the cost of the wind power access to the system to maintain the stable operation of the cost of the risk is considered, and the risk of wind power loss and risk indicators are introduced. A multi-objective optimization scheduling model for power system with wind power generation risk is constructed in order to achieve the overall optimization of the system total pollution emissions and the lowest operating cost. The model is solved by using a novel bat algorithm, and the shortcomings of the algorithm are improved. The algorithm can effectively solve the problems such as slow convergence and easy to fall into local extremum. Taking large-scale wind power system as an example, the environmental and economic dispatch simulation is carried out to verify the effectiveness of the proposed model and the algorithm.