In order to solve the problem that the PV power prediction error has a serious impact on the dispatch results

an optimal storageload dispatch strategy for residents considering photovoltaic uncertainty is proposed. The affine algorithm was used to quantify the uncertainty of photovoltaic output

and a storage-load optimization scheduling model was established with the goal of minimizing the daily electricity cost and maximizing the comfort of residents

and the Gurobi solver was used to calculate the micro-energy storage charging and discharging plan and the day-ahead electricity consumption plan of residents. Through simulation verification

the proposed algorithm can fully consider the uncertainty of photovoltaic output

effectively improve the accuracy of the scheduling model

and alleviate the pressure of peak power consumption while ensuring user satisfaction.