考虑不确定性的智能电网多目标机组组合研究

RESEARCH OF MULTI-OBJECT UNIT COMBINATION IN SMART GRID WITH UNCERTAINTY

以含电动汽车、火电、风电和光伏的智能电网为研究对象,综合考虑系统的不确定性、节能减排和电动汽车的智能充放电,建立其多目标节能减排模型。先采用多场景模拟技术将风电场出力、光伏出力和负荷不确定性的随机过程分解为若干典型的离散概率场景,然后将优化问题分解为相互作用的代理优化,控制代理的调度方案由具有自适应交叉变异算子的遗传算法实现,代理间的协同进化过程由自适应协同乘子协调实现。算例表明通过场景缩减的多场景模拟技术可提高计算效率,自适应协同进化实现风电、光伏、火电和电动汽车的有机互补,自适应的协同乘子比传统的次梯度法更新乘子计算效率更高,精度更好。通过电动汽车的智能充放电控制,可以提高系统的旋转备用水平,实现节能减排综合性能好的机组多发电,能耗大或污染气体排放量大的机组少发电;通过权重调节实现节能与减排的折衷,增加系统调度的灵活性。实现最大化利用可再生能源和电动汽车来达到系统的节能减排。

Taking the smart grid with electric vehicles, thermal power generation, vind power and PV power as the research object, considering synthetically the uncertainty of the system, energy conscrvation and emission reduction, intelligent charging and discharging of electric vehicles, the multi-goal energy cot servation and emission reduction model was set up. At first, the multi-scenario simulation technique was used to decorapose the stochastic processes of wind farm output, PV output and load uncertainty into several typical discrete probability scenarios. Then the optimization problem was decomposed into interactive agents＇ optimization. Controlling agents＇ managing scheme was realized by genetic algorithm of adaptive crossover and mutation operators. The co-evolation process between agents was reached by the adaptive cooperative multipliers. The results show that the calculaion efficiency of multi-scenario simulation technique can be improved by cutting scenarios. The mutual complementarily of wind power, PV power, thermal power generation and electric vehicles are realized by the adaptive cooperat ve evolution. The computational efficiency of adaptive cooperative multipliers is more efficient and more exact than tratitional subgradient method. The circumrotating reserve level of system can be improved by the intelligent charge and discharge control of electric vehicles, and the outputs of the units which have good performance with energy conservation and emission reduction are increased, and the outputs of units with large energy consumption or large emission of pollution gas are decreased. The balance in energy conservation and emission reduction can be realized by weight adjustment. The flexibility of the system was also increased. And energy conservation and emission reduction of the system can be reached by maximally utilize renewable energy and electric vehicles.