Research On Optimal Scheduling Of CCHP AC/DC Microgrid

In modern society,industrial production and human life not only have a large demand for power,but with the progress of society and the improvement of human quality of life,the demand for cold and heat energy is also increasing.The traditional centralized heating and cooling system has greater energy loss in the process of energy transportation.The proposed distributed energy reduces the space distance between source and load,reduces the cost of energy transportation,reduces energy loss,and improves the consumption of renewable energy generation.In order to solve the energy demand with the above advantages,the combined cooling,heating and power supply(CCHP)microgrid emerged as the times require.CCHP microgrid has many advantages,but its internal equipment includes not only traditional power equipment,but also cold and heat energy equipment.It is difficult to optimize dispatch while satisfying the internal constraints and mutual constraints among various devices.The traditional CCHP microgrid production modes of " following the thermal load" and " following the electric load" may have problems of high discarding rate of wind and waste heat of gas turbine,respectively.Therefore,in the process of optimal dispatch for CCHP microgrid,this paper fully considers the operation mode of each device,improves the algorithm to improve the optimization calculation efficiency,and improves the shortcomings of the production modes of "following the thermal load" and "following the electric load",in order to improve the energy utilization rate and new energy generation penetration in CCHP microgrid,and to improve the environmental protection and operation economy of the system.The main contents of this paper are as follows:Firstly,the research status of CCHP-type microgrid at home and abroad is deeply studied,the concept and specific structure of CCHP-type microgrid are introduced,the energy production modes of " following the thermal load" and " following the electric load" are elaborated in detail,and the shortcomings of the two modes are analyzed.The network connection,islands and other operation modes of CHP-type microgrid are described.For the specific structure of CCHP microgrid,the physical model and mathematical model of cold energy equipment,heat energy equipment and power equipment are established respectively,which lays a model foundation for the subsequent optimal dispatch of CCHP microgrid.Secondly,the CCHP microgrid optimal scheduling model is established,which takes into account the cost of current exchange,equipment maintenance,energy storage loss,electricity sales and purchase,gas costs,environmental protection costs,waste heat penalty costs.For the cold,heat and electric energy equipment,the internal constraints and constraints among the equipment are established,and the constraints of cold energy balance,heat energy balance and electric energy balance are met.Then the gray wolf algorithm is introduced in detail.Aiming at the problem that the initial population distribution of the gray wolf algorithm is not uniform,the logistic chaos map is proposed to improve the algorithm,and the initialization simulation of single,two and three independent variables verifies that the initial population distribution of the chaos Gray Wolf algorithm is relatively uniform on the one-dimensional,two-dimensional and three-dimensional levels.Finally,in view of the shortcomings of the energy production mode of " following the thermal load " and " following the electric load ",the energy production mode of the comprehensive mode is proposed.The three production modes are simulated and analyzed through practical examples,and the comparison shows that the daily operation cost of the comprehensive production mode proposed in this paper is the lowest,and the energy utilization rate is higher,and the environmental benefit is better.Then the gray wolf algorithm(GWO),particle swarm optimization(PSO),chaos particle swarm optimization(CPSO)and the chaos Gray Wolf algorithm(CGWO)are used to analyze the same practical example,which verifies the superiority of the algorithm in the optimization results and convergence performance.