Study On Coupled Dynamic Simulation And Synergistic Operation Optimization Of Integrated Energy System Based On Intelligent Algorithm

As the physical carrier of the energy Internet,regional integrated energy system is capable of improving the utilization efficiency of primary energy,increasing the consumption of renewable energy,as well as reducing the emission of greenhouse gases and air pollutants through realizing the cascade utilization of energy and synergistic operation of multi-energy system,and is advantageous in solving energy shortage crisis,mitigating air pollution,adapting to climate change as well as ensuring energy-supply security.Therefore,many researchers have focused on the synergistic operation optimization of integrated energy system(IES),which is one critical technology to realize the above advantages of integrated energy system.However,there are still some urgent problems affecting synergistic operation of IES such as how to improve the precision of equipment simulation modeling,describe the correlation of renewable energy power generation,identify the uncertain parameters involved in the system,assess the impact of climate change on the energy supply and demand,and generate the operation scheme for adaptation to climate change.In this paper,aiming at providing theoretical support and practical basis for the formulation and implementation of operation scheme,the integration of mechanism modeling theory,BP neural network algorithm,copula theory,uncertainty optimization algorithm,regional climate model and support vector regression algorithm are used to realize the dynamic simulation and synergistic operation optimization of IES.Meanwhile,the impact of climate change on IES is deeply analyzed.The main contents include:(1)Study on dynamic simulation and synergistic operation optimization of customer-type IES.Based on neural network algorithm and mechanism modeling theory,an intelligent fusion simulation model of gas turbine is established firstly,which not only is capable of describing the energy transfer and conversion processes in system operation,but also correcting the submodules with insufficient dynamic knowledge and data associated with the mechanism model.The results demonstrated that the mean absolute error(MAE)and root mean square error(RMSE)of intelligent fusion simulation model are obviously better than those of simple mechanism model.Then,the intelligent fusion simulation model is innovatively incorporated into the operation optimization model of IES through replacing oversimplified linear equation as operational constraint of gas turbine.Finally,a customer-type integrated energy system operation optimization model is formulated for realizing the minimal system cost and improving the energy exploitation and utilization efficiency.To solve this optimization model,an improved genetic algorithm is proposed,which combined the adaptive crossover and mutation probabilities and penalty function for handling the complexity associated with intelligent fusion model and enhancing the accuracy of simulation results.Finally,a variety of optimal operation strategies of ES were obtained,which are capable of revealing the transmission rules of cooling,heating and power among a year,and helping local managers gain in-depth insights into cooperative scheduling of many types of energy forms.(2)Study on synergistic operation optimization of community-type IES.Based on the integration of Copula algorithm,birandom chance-constrained programming and interval linear programming,a CIBCCP(Copula-based interval birandom chance-constrained programming)model was developed for determining the optimal operation strategies of IES for an industrial park in Tianjin,China.The CIBCCP model has two advantages as follows:(i)recognize the correlation between wind and solar power generation;(ii)identify the birandomness in users’ energy demand and the fluctuations in economic and engineering factors.A variety of system scheduling schemes are obtained,which indicated that CIBCCP model is useful in understanding the dynamic characteristics of renewable energy power output under various probability-violation levels and helping the managers make a tradeoff between system economy and reliability.(3)Study on synergistic operation of community-type IES under the impact of climate change.Based on the PRECIS(Providing regional climate for impacts studies),the weather elements,including temperature,wind speed and radiation,are firstly predicted under two climate change scenarios(RCP4.5 and RCP8.5)and four periods(2018,2025,2050 and 2100).Next,the renewable energy generation prediction model and users’ load prediction model based on support vector regression algorithm are developed.Then,predicted meteorological parameters values under climate change are determined as the input parameters of above two models for identifying the impacts of climate change on the supply and demand side of community-type IES.The obtained results demonstrated that with the increasing trend of global warming,the wind energy output and heat requirement exhibit a downward trend.Conversely,an upward trend is reflected in the solar power generation and cold demand.Meanwhile,the electric demand has a decreased trend in winter and an increased trend in summer and transitional seasons.Finally,an operation optimization model of community-type IES concerning for the impact of climate change is established.Based on multi-scenario analysis method,the optimal operation strategies adapted to climate change is generated.The results show that the proposed model could avoid the imbalance of energy supply and demand caused by climate change,reasonably generate the reserve and utilization schemes of primary energy for decision makers adaptation to climate change,realize the effective distribution of energy,greatly improve the system economy and ensure energy-supply security in the future.In this research,a variety of stable and reliable operation strategies with maximal efficiency and minimum cost for IES are obtained,which could provide the technical support for realizing the efficient energy allocation and maximize utilization of the renewable energy.Meanwhile,it is useful in identifying the dynamic change characteristics of energy requirement and renewable energy generation and revealing the variation trend of system operation strategy under climate change,which is advantageous to solve the blindness in planning the reserve and utilization schemes of primary energy and improving system economy and security.