Optimal allocation of microgrid considering economic dispatch based on hybrid weighted bilevel planning method and algorithm improvement

• We searched for the optimal allocation of a microgrid considering economic dispatch.
• A hybrid weighted method for solving the different objective functions is proposed.
• An improved adaptive genetic algorithm was applied to solve the objective function.
• The results under different scheduling strategies were analyzed and discussed.

During the microgrid search process, optimal allocation and economic dispatch are very important and are interrelated, having interaction and mutual checks. In this paper, we adopt a bilevel planning method to search for the multi-objective optimal allocation of a microgrid, considering economic dispatch. The upper level is the optimal allocation, which aims at minimizing the daily fixed cost of investment (DFCI), load loss probability (LLP), and excess energy rate (EER), with which it determines the capacity of each power supply. The lower level is the economic dispatch, which aims at minimizing the cost of operation and management (COM) and cost of pollutant disposal (CPD), with which it determines the output power of each distributed generator (DG). Considering the different dimensions of multi-objective functions of the upper level, a hybrid weighted method based on the judgment matrix method and variation coefficient method is proposed. For the objective function of the lower level, the penalty function method is adopted to handle the unbalanced active power. We propose an improved adaptive genetic algorithm (IAGA), which can avoid premature phenomena and local convergence and can find the global optimal solution more quickly and stably. We also discuss the two different scheduling strategies of the microgrid. With the example system, the correctness and effectiveness of the model and algorithm are verified. The simulation results show that the hybrid weighted bilevel planning model can efficiently realize the optimal allocation of DGs, reasonably schedule the output power of DGs, and eventually achieve optimal multiple objectives, considering optimal allocation and economic dispatch. The presented research can provide some reference information for microgrid applications.