基于机会约束规划的风电源与充电站的优化配置

Optimal Allocation for Charging Station and Wind Generation Based on Chance-Constrained Programming

为了改善分布式电源与电动汽车的接入对电网安全性、经济性和电能质量的不良影响。考虑风力资源的随机波动性、电动汽车充电需求、分时电价等,以配电系统投资运行成本、有功损耗和电压质量为规划目标,建立了基于机会约束规划的优化配置模型,采用改进遗传算法进行求解。以IEEE33节点配电系统为例,验证了所提模型和算法的有效性。仿真分析表明,将电压质量纳入规划目标,能够以较小的经济成本保证较好的电能质量,考虑输出功率不确定性等因素,得到的规划方案具有较好的经济性。

To improve the influence of the access of electric vehicles and distributed generator on the safety, economic efficiency and power quality of the power grid, a stochastic chance--constrained optimal programming model is established based on the cumulant method with consideration of the stochastic volatility of wind resources, charging demand of EVs and time- based electricity price. In the model, the cost of the investment and operation of the distribution grid, active power loss and power quality are taken as objectives and the improved genetic algorithm is used to seek solutions. Taking the IEEE 33-bus distribution system as an example for simulation, the paper has verified effectiveness of the model and algorithm. The simulation analyses suggest that better power quality is ensured at the smaller economic costs if power quality is adopted into the planning objective. Given the uncertainty of wind power, the planning scheme obtained in this way can lead to a better economic efficiency.