Day-ahead operation strategy for a multi-timescale integrated photovoltaic storage and charging station considering carbon emission stratification
In the context of"dual carbon"goal,integrated photovoltaic storage and charging station(IPSCS)can effectively solve the problem of independent operation of multiple types of flexible resources.To enhance the collaborative consumption capacity of source load and reduce carbon emissions,this paper proposes a multi-timescale day-ahead operation strategy for IPSCS that considers carbon emission stratification and source load interaction.Firstly,hybrid prediction model and Monte Carlo method are applied to historical data to derive typical photovoltaic output and electric vehicle load scenarios,respectively.Secondly,the objective function of the mathematical model of the operation strategy of the integrated station is minimum comprehensive planning cost,minimum carbon emission,and maximum utilization of new energy.The model is solved using an improved whale optimization algorithm(IWOA)incorporating an opposition-based learning strategy and diversity variation processing.Finally,the rationality and effectiveness of the proposed strategy are verified through case analysis.
integrated photovoltaic storage and charging station(IPSCS)carbon emissionsmulti-timescaleimproved whale optimization algorithm
万方数据
维普
