Multi-objective day-ahead optimal scheduling model of active distribution network based on improved uncertain boundary

In order to solve the problem of too many core targets and unreasonable power scheduling caused by the uncertainty of distributed power supply, a multiobjective day-ahead optimal scheduling model of active distribution network based on improved uncertain boundary is proposed, which fully considers the uncertainty of the output of renewable energy generation (REG) in active distribution network, takes the economy and security of optimal scheduling as the objective function, and takes network structure adjustment, reactive voltage equipment control, REG output and power balance as the uncertain constraints. A new multi-objective day-ahead scheduling model of active distribution network is constructed. The linear duality theory and Lagrange transform are used to deal with the uncertain variable constraints in the model, improve the conservative degree of uncertain boundary, adjust the model, and use the ideal point method to efficiently deal with the multi-objective optimization problem. The genetic algorithm is used to solve the model, and the multi-objective best-day-ahead optimal scheduling of active distribution network is realized. The experiment shows that the model can reduce the risk of voltage overtripping and improve the safety of active distribution networks. The model has strong solving and convergence ability. It can effectively reduce the operating cost of active distribution networks and reduce network loss.