Research On Source Load Storage Collaborative Optimization And Benefit Evaluation Model For Park Integrated Energy System

In traditional energy systems,each energy subsystem has a monotonous operational structure and no tight coupling relationships with others,and the energy loss is serious,which reflects the conflict among energy,environment and society in China and boosts the proposal of new energy system.Integrated energy system(IES),as an energy system integrating energy production,energy transmission,energy conversion,energy storage and energy consumption,effectively promotes the coordinated and complementary usage of source,load and storage,enhances of comprehensive usage efficiency of each energy,and reduces the operational cost of the system.However.there is a lack of research on coordinated optimization for the IES in the process of source,load and storage.In the context,it is necessary to conduct relevant research on park IES.First,The necessity and urgency of this paper is pointed out,based on the analysis of the previous research on park integrated energy systems and relevant theories.Firstly,current research on the development,influences,coordinated optimization model,and benefit assessment model of integrated energy systems are summarized.Secondly,basic theories on the systems are combed out from concept,characteristics,and development process.Thirdly,implementation status at home and abroad is deeply analyzed,and useful experience is pointed out.Finally,three coordinated modes,i.e.power-heat,power-heat-cooling,and power-heat-cooling-gas,are compared to lay a foundation forthe following study.Second,A multi-load joint prediction model for integrated energy systems is constructed,based on strong coupling relationships among each energy subsystems.Firstly,the strong coupling relationships among power,heat,cooling,and gas subsystems are deeply analyzed.Secondly,the multi-load joint prediction model is constructed by using multi-task learning theory and least square support vector machine algorithm;the two methods can recognize the input variables of the model,and form the computing process of the model.Finally,a park integrated energy system is selected for a case study,where the power,heat,cooling,and gas load demands are predicted,and the results demonstrate the proposed model's effectiveness and superiority in prediction accuracy and training time.Third,A load-load coordinated optimization model is constructed with multi-energy conversion,since energy conversion and usage cannot be performed among independent energy subsystems.Firstly,the characteristics of CCHP combined units,P2G converters,and other energy conversion equipment are analyzed,and then the load-load joint operation structure is introduced based on the characteristics.Secondly,aiming at the maximum system net revenue and the minimum renewable energy curtailment rate,multi-objective load-load coordinated optimization model for integrated energy systems is constructed,with the jointly-predicted load data as basic parameters,and the corresponding multi-objective coordinated optimization solving algorithm is proposed.Finally,a park integrated energy system is introduced to carry out a case study with four different scenarios,and the results verify the advantage that the proposed model with multiple energy conversion equipment is conducive to improving comprehensive usage of each energy.Fourth,A bilevel optimization model of source-load coordination is constructed based on risks caused by uncertainties of wind power,photovoltaic power and load.Firstly,uncertain characteristics of wind power,photovoltaic power and load are analyzed,and source-load coordinated operation structure is built.Secondly,the bilevel optimization model of source-load coordination is constructed aiming at the minimum operational cost and the maximum renewable energy consumption.Thirdly,robust optimization theory and stochastic chance-constrained programming theory are respectively introduced to construct the upper model and lower model for uncertainty modelling of wind power,photovoltaic power and load.Fourthly,firefly algorithm is used to solve the bilevel programming optimization model of source-load coordination,and its computing steps are detailed.Finally,a case study with multi-scenario comparison is carried out based on a park integrated energy system demonstration base,effectively increasing renewable energy consumption rate and reducing system's total operational cost.Fifth,A source-load-storage coordinated optimization model is constructed with multiple demand response which can effectively encourage users to change their energy consumption habits and load curves.Firstly,the characteristics of demand response are analyzed,including interruptible load,transferable load,and adjustable load,and then the source-load-storage operation structure of integrated energy system is built.Secondly,according to interactions between output exchange power and demand response adjustment of each unit,a two-stage source-load-storage optimization model for integrated energy systems is constructed with the solving algorithm and computing process proposed.Finally,a case study is carried out for multi-scenario comparison and discussion,thus verifying the demand response strategy for source-load-storage coordinated operation can make the system more flexible and stable.Sixth,A multi-dimension source-load-storage benefit assessment model is built based on the complexity and multi-agent of integrated energy systems.Firstly,influences between different participants in the process of source-load-storage in a park integrated energy system are analyzed from 3 aspects of relevant policies,external markets,and end users.Secondly.a benefit assessment system including 24 indicators for source-load-storage process are built from 4 dimensions of externality,economy,environment,and society.Thirdly.multi-level fuzzy comprehensive assessment model based on the improved cloud model is constructed based on the advantage of multi-level fuzzy comprehensive assessment methods in solving uncertainty and randomness.Finally,a case study with four coordinated optimization modes is carried out,and the results verify the effectiveness of the proposed model on highlighting advantages of the source-load-storage coordinated optimization model.