计及碳捕集和多能流的虚拟电厂多目标优化调度

Multi-objective optimal scheduling of virtual power plant considering carbon capture and multi-energy flow

虚拟电厂作为多能流互联的综合能源网络,面临实际碳排放量过高、新能源消纳能力不足、多能流优化变量复杂、优化目标非单一等难点。为此,提出一种计及碳捕集和多能流的虚拟电厂多目标优化调度方法,提升多能流虚拟电厂新能源消纳能力的同时降低碳排放量。首先,根据虚拟电厂的实际碳排放量建立基于奖励系数的奖惩阶梯型碳交易机制。然后,以最小化运行成本和碳排放量作为目标函数建立双目标优化调度模型,利用樽海鞘群多目标优化算法进行求解。最后,设置多个调度场景对比分析多目标优化算法的性能,研究结果验证了优化调度模型的可行性及有效性。

As an integrated energy network with multi-energy flow interconnected,virtual power plants(VPPs)face difficulties such as high actual carbon emissions,insufficient new energy consumption capacity,complex optimiza⁃tion variables of multi-energy flow,and non-uniform optimization objectives.To this end,a multi-objective optimal scheduling method for virtual power plants considering carbon capture and multi-energy flow is proposed to improve the new energy consumption capacity of multi-energy flow virtual power plants and reduce carbon emissions.First,a reward and punishment ladder-type carbon trading mechanism is established based on the actual carbon emissions of the virtual power plant.Then,a dual-objective optimal scheduling model is built with the minimization of operat⁃ing costs and carbon emissions as the objective function and solved by using the multi-objective salp swarm algo⁃rithm.Finally,multiple scheduling scenarios are set up to compare and analyze the performance of the multiobjective optimization algorithm.The results verify the feasibility and effectiveness of the optimal scheduling model.