Research On The Optimization Of Integrated Energy System In Rural Areas

With the improvement of China’s urbanization level,new rural communities have emerged in large numbers,which has led to the dual pressures of the environment and energy supply,especially in the heating season.The healthy and comfortable indoor environment has become a common appeal of the community residents.The heating problem of the new rural community has risen to the people’s livelihood issue that the government urgently needs to solve.The realization of community heating based on integrated energy systems and modern energy management methods has become a research hotspot.Therefore,this paper takes the demand response as the foothold to study the optimization of the integrated energy system in rural areas from the aspects of heating sector.Firstly,the current status of research on energy management of new heating systems and heating systems in single-family houses are reviewed.Secondly,the simulation software of De ST is used to simulate the heating load of a typical new rural residential building in various heating modes in Harbin,Zhangbei,Lanzhou,Beijing,Shanghai,Nanjing,respectively.Moreover,the load characteristics under different modes are studied,and regional differences were compared.Then,the simulation software of TRNSYS is used to stimulate the heating system of solar-assisted electric heating system,solar-assisted natural gas heating system and wall mounted gas boiler heating system.And the instantaneous operation of each system was simulated under the loads in Beijing,achieved from the De ST simulation results.The ability of demand response under different modes is compared and analyzed in terms of quantity,power transfer capability,and lag time.Meanwhile,economic and environmental analyses of different heating modes are operated.In addition,in order to further study the impact on the regional energy network under the response of large-scale users,this paper takes a community of two thousand heating users as the research object and the aggregation effect of demand response in the community is studied.Finally,based on the above research,the optimization of the integrated energy system in rural areas was proposed from the aspects of physical layer and management of demand response.The results of this paper show that the optimization of the “load” side will profoundly affect the operation of the integrated energy system,and the energy use level will be significantly improved by managing the energy use behavior of residents.Moreover,considering the complexity and diversity of t e data on t e “load” side,it is necessary to introduce a modern management system to scientifically manage the load on the user side.Heating demand has shown a significant downward trend from cold regions,cold regions,hot summer and cold winter regions.And the heat load index and the cumulative heat load during heating season are decreased after considering the different usage characteristics of rooms,however the maximum heat load is increased.And it is indicated that refining the heating time and heating temperature contributes to the improvement of the heating season heat load index and the cumulative heat load,and the maximum heat load can effectively decrease.Compared to mode 6,mode 7,mode 8,and mode 9 further refine the functions of each heating room.As a result,the load quantification indicators in mode 7,mode 8,and mode 9 have been reduced,and the heat load indicator of the heating season of the three modes have been reduced by approximately 11.15%,28.88%,33.46%;the maximum heat load of them were reduced by approximately 13.66%,24.44%,and 28.21%;the cumulative heat load of them were reduced by approximately 11.97%,30.75%,and 35.07%.Generally,by changing the heating behavior of the heating user(indoor heating temperature and heating time),the user’s heating energy consumption will be effectively changed,mainly in terms of energy consumption,power and lag time.Taking solar-assisted electric heating systems as an example,the total energy consumption can reach a maximum of 25880.81,while the minimum of the total energy consumption can only reach 9787.51.From the perspective of large-scale residential user groups,the coordinated demand response in terms of total energy consumption and power will increase significantly,which will have a huge impact on regional energy use.In a case study of the capacity of the demand response of a rural town,it was found that after optimization according to option 1,the community could have the maximum negative response energy of 61730.69,which is a response amount of approximately 12.92% of the total heating energy.And it can provide the power reduction of 2155.10 k W,which is approximately 9.44% of the total power.Hence,by adjusting the heating behavior of the heating users in the area,the energy consumption and energy consumption of the area will be effectively optimized.Meanwhile,regional energy networks will receive greater demand response when users are willing to accept more aggressive adjustments.Considering that the adjustment of the human behavior of the heating user is mainly influenced by subjective factors,the enthusiasm of the market behavior to stimulate the demand response of the user side should be introduced.Additionally,by establishing a self-diagnosis optimization model,the intelligent management level of the integrated energy system will be improved.Through the relevant research in this paper,the effects of demand response in the integrated energy system have been visualized and embodied,which provides significant data support for regional energy dispatching,as a result,the efficient operation of the heating system can be achieved and the operation of the energy internet can be coordinated when needed.Meanwhile,this paper also provides new ideas for solving the extensive energy consumption pattern of the current rural community,and points out a new direction of heating solution for China’s communities.