摘要
Abstract
According to the problems of output fluctuation and consumption bottleneck caused by the high proportion of renewable ener-gy grid connection,it proposes a capacity optimal configuration method for virtual power plant energy supply units including wind solar and energy storage.Firstly,it constructs a multi-objective optimization model with annual total cost,annual total carbon emissions,and annual total interaction power as objectives,balancing economic efficiency,environmental protection,and system independence.Secondly,it proposes an innovative hybrid solution strategy.It uses the NSGA-Ⅱ algorithm to generate a Pareto optimal solution set,and combines it with the TOPSIS method based on posterior entropy weighting to objectively assign weights and screen the solution set,addressing the conflicts among multiple objectives and the subjectivity of weights.Finally,simulation results based on 8760 hours of meteorological and load data from a region in Europe show that the optimized virtual power plant has an annualized cost 60.11%higher than traditional grid-connected power purchase,but reduces carbon emissions by 99%.The installed capacities of wind and solar pow-er are 123%and 177%of average load,respectively,while the storage capacity reaches 2.5 times the load,enhancing the utilization rate of renewable energy.Further comparisons of configuration effects across different climate regions reveal that Greece(Mediterra-nean climate)has the best overall performance due to abundant sunlight resources and high load matching,validating the model's uni-versality.Through multi-objective collaborative optimization and adaptation to climate differences,it can provide references for the ef-ficient planning and low-carbon operation of virtual power plants.关键词
可再生能源/虚拟电厂/风光燃储/优化配置/气候适配性Key words
renewable energy/virtual power plant/wind solar and energy storage/optimal configuration/climate adaptability分类
信息技术与安全科学
