Optimal Dispatch Of Integrated Energy System Considcring Source-Load Uncertainty

In recent years,energy problems have become increasingly serious in China,and the problems of low energy utilization and aging energy structure have made the development and utilization of new energy sources and the establishment of new energy systems a consensus of the whole society.In this context,integrated energy system(IES),which integrates power,heating and cooling,came into being.IES is based on smart grid,which can greatly improve the energy utilization rate.However,the internal uncertainty of the system makes its optimal dispatch face some problems.On the one hand,due to the influence of weather conditions and natural conditions,the output of renewable energy is of highly uncertainty.With the continuous improvement of the penetration of renewable energy in the system,the risk of system operation will gradually increase.On the other hand,there are many types of user load in IES and it is difficult to accurately predict.Under the uncertainty of source and load,how to realize the coordinated utilization of multiple energy sources is a key issue for IES optimal dispatch.Therefore,this paper studies the optimal dispatch of IES considering the uncertainty of source and load on the basis of stochastic theory.First of all,in view of the problems of the randomness and mismatch of cooling,heating and power load,considering that human has a certain adaptability to the temperature.This paper combines wind power,photovoltaic and gas turbine combined cooling heating and power(CCHP),and proposes a source-load coordinated CCHP system based on demand response.Using the typical scene to consider the uncertainty of new energy output,an optimal dispatch model is established.The model aims to minimize the economic cost,and solved by immune genetic algorithm.The relationship between dispatch cost and different demand response modes,temperature deviation is discussed,and the introduction of electric heating equipment into the system is also discussed.The analysis of the example shows the CCHP system optimal dispatch method based on demand response and multi-energy coordination can effectively reduce cost and has significant economic and social value.Secondly,in view of the large number of load resources in the business park and the problems that are easily affected by the user’s energy use law.Firstly,the business park IES model is constructed.Then,based on the modeling of energy conversion of various device in the system,the uncertainty of the roof photovoltaic output and the user’s cooling,heating and electricity load is considered.and the energy optimization dispatch model of business park IES based on chance constrained programming(CCP)is established.The model aims to minimize the economic cost,and is solved by a hybrid algorithm based on improved immune genetic algorithm and stochastic simulation.Corresponding quantitative indicators are established for the accompanying imbalance risk in the CCP model.The dispatch results of different demand response modes,confidence levels and prediction accuracy are analyzed in order to provide reference for the IES operation that balances economy and reliability.Finally,on the basis of the idea of robust optimization,the optimal dispatch strategy of IES is designed by using the minimum robust regret criterion with less conservatism.Firstly,the interval model is used to express the uncertainty of photovoltaic output and cooling load.Secondly,the day-ahead energy market and real-time energy market are combined to establish the economic optimal dispatch model.Considering the regret psychology of decision makers,the integrated energy system optimal dispatch model based on robust regret degree is established and solved.The case study shows that the optimal dispatch scheme can effectively reduce the regret of decision-makers,and obtain a decision-making scheme that not only guarantees the robustness of the system,but also makes the decision-making scheme less conservative.