Research On The Collaborative Optimization Operation Of Multi-Energy Complementary Combined Cooling Heating And Power System With Schedulable Load

Energy and environmental issues have become key challenges for global sustainable development in the future.Combined cooling,heating and power system has received more and more attention and research due to the environmental benefits brought by its waste heat recovery technology and energy cascade utilization principle.By connecting Renewable Energy Sources such as wind energy and solar energy to the CCHP system to build a Multi-Energy Complementary Combined Cooling,Heating and Power System(Multi-Energy CCHP)system,and we can realize the complement the advantages of multiple energy sources and achieve the goal of energy conservation and environmental protection to a greater extent.This paper has carried out a series of studies on Multi-Energy CCHP system structure analysis,system modeling,optimized operation and other issues,and proposed a Multi-Energy CCHP system collaborative optimization strategy,which can comprehensively consider the system energy supply side and energy consumption side to better realize the source and load matching and improve system performance.The main research contents of this article are as follows:Firstly,the structure of the Multi-Energy CCHP system is analyzed,and the structure and energy flow diagram of the system under cooling and heating conditions are given,and the system energy flow model is established accordingly;the work characteristics of different equipment in the system is analyzed,built a full working condition model for the power generation unit of the core energy supply equipment of the system,established a mathematical model of two renewable energy supply equipment for photovoltaic power generation system and wind power generation system,and gave supplementary energy supply equipment mathematical models in both cooling and heating modes;the characteristics of intelligent electrical equipment are analyzed,and a schedulable electrical load model based on intelligent power device start-stop control is established;according to the relationship between indoor and outdoor temperatures,a schedulable cooling and heating load model based on indoor temperature control has been established.Based on the schedulable electricity,cooling and heating load models established above,the electric,cooling and heating loads can be coordinated without the need for additional equipment,thus achieving demand side management of various types of loads.Secondly,a collaborative optimization operation strategy suitable for Multi-Energy CCHP system is proposed.The load demand side and the energy supply side are included in the collaborative optimization operation strategy to consider the comprehensive evaluation indicators of the three indicators of energy,economy and environment as the optimization goal,the PGU power generation,the start and stop status of smart appliances,and the indoor temperature of the building are the optimization variables of the collaborative optimization operation model.Under the conditions of satisfying the capacity constraints and comfort constraints of each device,the system collaborative optimization operation is established.The model is analyzed,and the model has the characteristics of non-linearity and inequality constraints.The elite reserved genetic algorithm is selected as the optimization problem solving algorithm.The established model and solving algorithm are synthesized to obtain the Multi-Energy CCHP system collaborative optimization framework.Finally,a residential building in Jinan was selected as the simulation implementation object of the Multi-Energy CCHP system collaborative optimization operation strategy.The CCHP system,which is currently studied more,was used as the comparison system of the research system in this paper.By comparing the two systems,the optimization results and performance indicators verify that the proposed strategy can realize the resource scheduling of both supply and demand,alleviate the contradiction between system supply and demand,and improve the performance of the system.In addition,in order to facilitate the promotion of collaborative optimization strategies,the program is organized into Multi-Energy CCHP system operation optimization software,and operation instructions are given.