Study On Operation Optimization Of Integrated Energy System Considering Multiple Load Coupling

With the continuous and rapid development of China’s economy,China has entered a critical period of energy production and consumption pattern transformation.Energy crisis and environmental problems have become important issues restricting the development of the energy industry,and energy transformation is imperative.Integrated energy system(IES)integrates various types of energy supply equipment,energy conversion equipment and energy storage devices,which can realize the coupling and complementarity of multiple energy sources and the coordination and optimization of multiple energy markets.The emergence of IES breaks the current situation of the independence of various energy systems,and provides new technical means to alleviate the energy crisis.In IES,the fluctuation of renewable energy output,the coupling effect of multiple loads and the comprehensive demand response cause the fluctuation of IES source and load levels,which poses challenges to the optimal operation of IES.This paper takes IES as the research object,proposes an energy prediction model considering multiple load coupling characteristics.On this basis,the operation optimization of IES considering multiple market coupling is studied in depth.The main research work of this paper is as follows:Firstly,the CNN-BiLSTM integrated energy system energy prediction model based on improved adaptive noise ensemble empirical mode decomposition is constructed.The energy prediction is completed in three steps:data processing,model optimization and simulation analysis.Data processing is the screening of influencing factors by calculating the maximum information coefficient of related influencing factors(multiple load coupling factors and calendar factors)after completing a series of operations of abnormal data processing,normalization and modal reconstruction for the predicted data.Model optimization based on the difference between the supply side data and the demand side data,the hyper-parameter optimization of prediction model is carried out according to supply side and demand side respectively.The simulation analysis adopts the optimized LSTM,BiLSTM and CNN-BiLSTM three prediction models to carry out energy prediction simulation for the processed data.The results show that the CNN-BiLSTM combined neural network prediction model considering multiple load coupling factors has better prediction accuracy.Then,this paper constructs and introduces the basic framework of IES including electricity,gas,cold and heat energy,and analyzes the operation mode of IES including trading center and dispatching center under the coupling of natural gas market and power market in three time dimensions of medium and long-term,day-ahead and real-time.Based on the basic structure of IES,the output of basic equipment in IES is modeled and analyzed,and the user-side comprehensive demand response model considering user utility is established.Taking the maximum daily operation income of IES as the objective function,the economic dispatch optimization model of comprehensive energy system considering the operation constraints of each equipment in the system and the balance constraints of energy supply and demand of electricity,gas,cold and heat is established.Finally,the improved particle swarm optimization algorithm is used to simulate the IES economic dispatch optimization model proposed in this paper.Compared with the economic benefits of IES under different prediction accuracy,it is found that is the higher IES the energy prediction accuracy,the higher economic benefits of IES can be obtained;The energy prediction data with the highest economic benefit of IES are selected,and the comprehensive demand response simulation is carried out with the maximization of user utility as the objective function.The results show that the energy consumption of users after demand response tends to be more stable.With the data after demand response as the terminal load data,various scenarios are formed by adjusting the purchase strategy of IES in various energy markets.By comparing the optimal scheduling and profit of IES in different scenarios,the real-time optimal operation results of IES are obtained to optimize the operation of IES.