摘要：In order to promote the coordination of various forms of energy resources such as electric energy, heat energy, and cold energy, and to achieve complementary and efficient use of different energy sources, a method for optimizing the allocation of the capacity of a regional comprehensive energy system that takes into account the trading of electric and thermal energy is proposed. The energy interaction costs of the system and the grid heat network are included in the total cost. The optimization goal is a multi-objective function that comprehensively considers system economics, environmental protection, reliability, and interactive power fluctuations. Based on the energy hub, the capacity of each energy supply equipment in the area is optimized. Time-sharing electricity price and typical daily system economic operation are solved by genetic algorithm. Finally, an example of a park is used to verify its effectiveness. The results show that the proposed method can effectively reduce the system cost and reasonably avoid the limitations caused by the single decision factors in the system planning stage, thus providing a reference for the actual system planning and design.
其他摘要：In order to promote the coordination of various forms of energy resources such as electric energy, heat energy, and cold energy, and to achieve complementary and efficient use of different energy sources, a method for optimizing the allocation of the capacity of a regional comprehensive energy system that takes into account the trading of electric and thermal energy is proposed. The energy interaction costs of the system and the grid heat network are included in the total cost. The optimization goal is a multi-objective function that comprehensively considers system economics, environmental protection, reliability, and interactive power fluctuations. Based on the energy hub, the capacity of each energy supply equipment in the area is optimized. Time-sharing electricity price and typical daily system economic operation are solved by genetic algorithm. Finally, an example of a park is used to verify its effectiveness. The results show that the proposed method can effectively reduce the system cost and reasonably avoid the limitations caused by the single decision factors in the system planning stage, thus providing a reference for the actual system planning and design.
