Research On Multi-Objective Coordinated Optimization Operation Of Integrated Electric Power And Natural Gas System To Improve Wind Power Consumption

As a key area of the energy development strategy,power industry will develop in the direction of clean,efficient,and renewable energy as mainstay at the present and the future.With the acceleration of power reform process,the Integrated Electric Power and Natural Gas System(IEGS)has become an important development direction for improving energy utilization efficiency,reducing energy costs,enhancing renewable energy consumption,and promoting multi-energy complementarity.Power to Gas(P2G)is one of the new technologies that have emerged in recent years.By converting wind energy into natural gas,it provides new ideas for the consumption of wind power and will become one of the important technologies in the IEGS.In response to the current severe problem of wind curtailment in our country,this article considers the improvement of the renewable energy consumption capacity and operating cost of the IEGS,conducts the following research:First introduced the regional IEGS system,the mathematical models of the power system,natural gas system and coupling components,and the energy hub(EH)model is further introduced.Then,analyzed the operating cost of P2G,considering the impact of P2G operating costs on the dispatch and operation of the IEGS,it is found that there is a contradiction between the operating economy of the system and the capacity of wind power when the P2G operating cost is high.Establish a multi-objective day-ahead optimal scheduling model.The improved multi-objective particle swarm algorithm is used to deal with the multi-objective coordination optimization problem,so that P2G can be more flexibly applied to the IEGS to absorb wind power.The improved MOP SO and the traditional MOPSO algorithm are compared and analyzed,and the results prove that the improved MOPSO has higher convergence speed and accuracy,and can quickly and accurately converge to the real Pareto frontier.In the end,the simulation calculation using a calculation example shows that the necessity of considering the operating cost of P2G in the IEGS and the feasibility of considering the economy and the capacity of wind power are proved.The improved multi-objective particle swarm optimization algorithm used to deal with multi-objective optimization problems can not only improve the system’s wind power receiving capacity,but also ensure the economy of system operation effectively,and provide scheduling decision-makers with choices.