考虑风电消纳的冷热电联供型综合能源系统多目标日前优化调度

Multi-objective Day-ahead Optimization Scheduling of Integrated Energy System with CCHP Considering Wind Power Consumption

冷热电联供系统因其能源利用率高等特点在综合能源系统中得到广泛应用,但是由于其“以热定电”模式的约束,供热和供电不能解耦,使得大量风电难以消纳。针对我国冬季夜间大量风电未被使用的问题,将热泵及电转气装置纳入综合能源系统,研究二者对于消纳风电的作用。以综合能源系统总经济成本、温室气体排放量及净负荷波动最小为目标函数,计及联络线、储能上下限及功率平衡约束条件,采用帕累托多目标粒子群算法对模型进行求解,并设置四种场景,探究不同场景下热泵及电转气对于系统各个方面的影响。仿真分析了加入热泵及电转气装置前后系统的风电消纳及负荷波动情况,验证了所提方法的有效性。

Combined cooling,heating and power system is widely used in integrated energy system because of its high energy utilization rate.However,due to the constraint of the mode of“power determined by heat”,heating and power supply cannot be decoupled,which makes it difficult to absorb a large number of wind power.In view of the problem that a large number of wind power is not used in winter night in China,especially in the“Three North Area”,the heat pump and power to gas device are incorporated into the integrated energy system to study their role in the absorption of wind power.Taking the minimum fluctuation of the total economic cost,greenhouse gas emissions and net load of the integrated energy system as the objective function,taking into account the tie line,energy storage and power balance constraints,the Pareto multi-objective particle swarm optimization algorithm is used to solve the model,and four scenarios are set to explore the influence of heat pump and electric gas on all aspects of the system in different scenarios.The wind power consumption and load fluctuation of the system before and after adding heat pump and power to gas device are simulated and analyzed,and the effectiveness of the proposed method is verified.