基于NSGA-Ⅱ-WPA的综合能源系统多目标优化调度

Optimal scheduling of integrated energy systems based on NSGA-Ⅱ-WPA

针对复杂多能流综合能源系统(IES)运行调控难以兼顾经济性与低碳性的问题,提出了结合非支配遗传算法Ⅱ(NSGA-Ⅱ)与狼群算法(WPA)的NSGA-Ⅱ-WPA算法,以实现IES在多目标条件下的优化调度。首先依据IES多能流的系统特性建立具有强耦合关系的运行调度模型,主要包括电能供应子系统、热能供应子系统以及制冷供应子系统;其次,构建IES的多目标运行策略,包括实时电价下的电池储能运行策略、分层能源供应策略以及碳排放权交易策略,以实现多目标因素影响下的IES协同运行控制调度优化模型;最后,提出了基于NSGA-Ⅱ-WPA的多目标优化求解算法,实现对多能流IES的优化调度。通过仿真试验对IES运行成本以及碳排放量进行评估,试验结果证明该算法能切实提高IES的综合能效,并且结果优于一般的NSGA-Ⅱ算法。

Since the optimal scheduling on integrated energy systems(IES)with complex multi-energy flows can hardly balance the economy and low-carbon operation,an NSGA-Ⅱ-WPA algorithm based on non-dominant genetic algorithm(NSGA-Ⅱ)and wolf pack algorithm(WPA)is proposed.The proposed algorithm can realize the multi-objective optimization.Firstly,an IES scheduling model of strong coupling relationship is established considering the characteristics of the IES with multi-energy flows which integrates a power supply subsystem,a heat supply subsystem and a cooling supply subsystem.Secondly,the basic IES operation strategies are designed which includes the battery storage operation strategy under real-time pricing mechanism,layered energy supply strategy and carbon emission trading strategy.The strategies aim to realize the collaborative control optimization on the IES influenced by the multiple factors.Finally,the multi-objective optimization for the IES with multi-energy flows is completed based on the NNSGA-Ⅱ-WPA algorithm.The operational cost and carbon emissions of the IES are evaluated by simulation experiments,and the experimental results prove that the improvement on comprehensive energy efficiency of the IES provided by the proposed algorithm is better than that by NSGA-Ⅱalgorithm.