关键词: 虚拟电厂, 电转气, 区间优化, 多目标优化调度, 非支配排序遗传算法

Abstract:

The gas-electricity interconnected virtual power plant can promote the efficient use of distributed energy. An effective dispatch strategy that takes into account many uncertain factors is the key to ensuring its operational quality. On the base of the construction of a gas-electric interconnected virtual power plant including electric vehicles, wind power, photovoltaics, gas turbines, electric-to-gas equipment and electric vehicles, describing the uncertainty of wind power, photovoltaic power output, electrical load, and gas load in the virtual power plant by use of the interval optimization theory; Taking operating economic benefits, user comfort and carbon dioxide emissions as the optimization targets, and considering constraints such as power balance and equipment operating characteristics, an interval optimal scheduling plan for the gas-electricity interconnected virtual power plant is constructed, and designing an improved non-dominated sorting genetic algorithm to solve the scheduling scheme of gas-electric interconnection virtual power plant. An analysis of a case study is selected for the winter heating scenario of a gas-electricity interconnected virtual power plant in a certain area. The results show that the charging behavior of cluster electric vehicles increases the electric load during the dispatch period, and the output of gas turbines in each optimization target scheme is generally higher. The temperature is higher than the set value of 22; Considering the uncertain factors of scheduling, the interval width of the optimization results under each objective is different, which verifies that the interval optimization scheduling scheme is more authentic and more robust in terms of ensuring thermal comfort.

Key words: virtual power plant, electricity-to-gas, interval optimization, multi-objective optimization scheduling, non-dominated sorting genetic algorithm