Optimized Operation Of Cogeneration System Based On New Energy Consumption

With the rapid development of economy,China is facing the dual pressure of energy shortage and environmental pollution.Therefore,in recent years,new energy power generation has attracted extensive attention.However,due to the intermittency and instability of new energy power generation,its utilization efficiency and system absorption capacity need to be improved.Especially in northern China,the operation of thermal power plants in winter heating period must be subject to the rigid constraint of thermoelectric coupling to ensure the heating demand of users,and the situation of wind abandon and power limit is severe.In order to improve the given amount of new energy,wind power,for example,this paper established a cogeneration system model,established meet economy and amount of wind power given optimal scheduling optimization scheme,and through a variable time scale optimal scheduling policy in order to improve the flexibility and accuracy.In order to improve the consumption level of new energy,this paper established the overall structure framework of a new type of cogeneration system including electric energy storage,heat pump and hot water accumulator,and carried out a detailed analysis of the output characteristics and operating costs of each unit.At the same time,it verified that each controllable unit in the system proposed in this paper has the ability to absorb new energy.Taking wind power as an example,the consumption capacity of wind power in different unit combinations was simulated and compared.It is verified that the new cogeneration system proposed in this paper has good wind power absorption capacity.In order to ensure the economic operation of the system while accepting more abandon the wind power,this paper established a day-ahead scheduling optimization model aiming at achieving the lowest operation cost for the above cogeneration system.And according to the characteristics of the model,Introducing the levy flight to improve the traditional particle swarm optimization(pso)algorithm,Through the improved particle swarm algorithm the optimal solution of the economic operation,compared with traditional particle swarm and other improved intelligent algorithms,it has been verified by the example simulation in this paper,the improved algorithm has obvious advantages on CHP optimization model;In this paper,optimization model and other models.With the modified algorithm,the proposed optimization model is verified with better economy and consumption effect of wind power.Dispatching difficulties caused by uncertainty of new energy and load.In this paper,a rolling scheduling strategy with variable time scale is proposed,which refines the time scale and reallocates the intraday scheduling time scale according to the historical data.Taking wind power as an example,based on the accuracy of wind power forecasting and load forecasting,the time period of real-time dispatching and the starting time of rolling dispatching are improved respectively.The simulation results show that the proposed variable time scale dispatching strategy can meet the load demand in real time,further improve the system's capacity to accept wind power,and reduce the impact of wind power forecasting error and load fluctuation on dispatching plan formulation.