对于含电动汽车和风电机组的虚拟发电厂,由于可调度充放电的电动汽车数量和风电机组出力均存在明显的不确定性,这样虚拟电厂在电力市场中参与竞价时就必须考虑这些不确定性。在此背景下,计及上述不确定性因素的影响,并在下述假定的基础上研究了含电动汽车和风电机组的虚拟发电厂竞价策略:风机出力的上下限为随机变量;日前能量市场和调节市场电价均为波动区间已知的随机变量;虚拟电厂中可调度充放电的电动汽车数量足够大,能够在平抑虚拟电厂内的风电机组出力波动的同时参与调节市场竞价。在同时考虑电动汽车电池放电损耗成本以及调节备用被实际调用比例的情形下,构建了虚拟电厂参与日前能量市场和调节市场的联合竞价策略的鲁棒优化模型。之后,采用IBM公司开发的高效商业求解器CPLEX 12.2对模型进行了求解。最后,通过算例对所构建的模型和采用的方法进行了验证,算例结果表明了所建立模型的合理性和求解方法的有效性。
The output of a virtual power plant(VPP)with wind power and dispatchable plug-in electric vehicles(EVs)included fluctuates as the result of the intermittence of wind power and uncertain number of EVs.Thus,in participating the competition in an electricity market,a VPP must address its output uncertainty.Given this background,the problems of developing a joint optimal bidding strategy for a VPP in the day-ahead spot market and regulation market are examined,with a special focus on the impacts of uncertain factors.Some assumptions are made:(1)the up and low limits of the wind power output are modelled as stochastic variables;(2) the electricity market prices in the day-ahead spot market and regulation market are modeled as stochastic variables with given intervals;(3) the number of EVs is huge,and could mitigate the output intermittence of wind power and at the same time participate the regulation market.Under these assumptions,a joint bidding strategy model for a VPP participating in the day-ahead spot and regulation markets is presented based on the robust optimization theory,with the battery discharging cost and the expected percentage of the bidded reserve capacity dispatched in each bidding period taken into account.Then,the commercial solver CPLEX 12.2 is next used to solve the developed robust optimization model.Finally,a sample example is employed to demonstrate the feasibility and efficiency of the developed model and algorithm.