Research on Energy Community Planning Based on Bi-Level optimization

With the development of economy, how to use energy efficiently and reduce the cost of energy has become an urgent problem. Different energy systems are planned and operated separately without coordination and linkage. Although cogeneration technology improves the energy efficiency of power plants, it also restricts the power output regulation capacity of thermal power units. In order to ensure heating in winter in northern China, the lack of flexibility of thermal power units hinders the large-scale access of renewable energy, resulting in a serious problem of wind curtailment. In this paper, the energy community with combined heat and power supply as the core can effectively improve the energy utilization rate and energy supply flexibility, while considering the planning economy and minimum wind curtailment rate. Aiming at the minimum annual total cost of investment cost, operation cost, operation and maintenance cost and wind curtailment penalty cost of the energy community, and considering the balance constraint of power supply and heat supply in the energy community. A multi-objective bi-level optimization model of energy community including CHP unit, wind power generation, heat storage, electric boiler and heat pump is established. The upper level takes the lowest annual cost as the goal, the installation capacity of each equipment as the optimization variable, the lower level takes the lowest annual operation cost as the goal, and the scheduling value of each period of equipment as the optimization variable. In the process of planning and solving, the elite retention strategy genetic algorithm is used to solve the upper model, and the lower model is solved by the function fmincon in the MATLAB optimization toolbox. The results of an energy community in North China show that the energy community planning can effectively reduce the operating cost and the wind curtailment rate, improve the utilization rate of renewable energy, bring obvious economic benefits, and verify the effectiveness and rationality of the planning method proposed in this paper.