| Energy crises and environmental problems are becoming more and more serious.Traditional energy structures and utilization methods are unsustainable.It is imperative to promote energy structure transformation and develop renewable clean energy sources.The report of the 19th National Congress of the Communist Party of China put forward the strategic layout of "building a socialist ecological civilization concept,adhering to the concept of green development,promoting the revolution of energy production and consumption,and building a clean,low-carbon,safe and efficient energy system",which pointed out the direction for the development of China's energy industry.In 2016,the National Development and Reform Commission,the Energy Bureau,and the Ministry of Industry and Information Technology issued The Guiding Opinions on Promoting the Development of "Internet+" Smart Energy,pointing out that it is necessary to strengthen the construction of multi-energy collaborative distributed energy netwaorks and to strengthen the coupling,interaction and comprehensive utilization of different types of energy such as electricity,gas,heat and cooling.In traditional energy systems,different energy systems are relatively independent and overall energy efficiency is low.How to break the independence between various energy systems,build an integrated and Multi-energy hybrid system and achieve coordinated optimization of multiple resources,becomes a major trend in the energy field.At the same time,China's resource and environmental constraints have been continuously strengthened.Centralized energy development has been difficult to meet the requirements of transmission loss,utilization efficiency,environmental pollution,etc.Distributed energy with advantages of being close to users and high energy efficiency will become a new main stream of energy structure transformation.The 13th Five-Year Plan for Energy Development proposes that by 2020,distributed natural gas power generation and photovoltaic installations will reach 15 million kilowatts and 60 million kilowatts,and actively develop distributed wind power.In the future,China's energy development model will present a centralized and distributed situation.Therefore,focusing on centralized and distributed energy development,this paper constructs a clean energy collaborative scheduling optimization model considering multi-energy hybrid system,and proposes a multi-type main part benefit dynamic equilibrium mechanism.The main research contents are as follows:(1)The results and theories of multi-energy hybrid and clean energy synergy utilization are sorted out,and the feasibility and necessity of the research are demonstrated,which highlights the background and significance of the research.Firstly,from the research status of multi-energy hybrid system,the research status of clean energy synergy optimization and the research status of benefit evaluation system,this paper suumarizes the research status at home and abroad related to the research content of the paper,and introduces the basic meaning and related policies of multi-energy hybrid.Then,it clarifies the multi-energy hybrid operation modes,including centralized and distributed operation modes.The centralized type includes the cooperative operation of large-scale energy bases of wind power,solar photovoltaic power,hydro power,thermal power and energy storage,and the integrated energy system of electric,heat,cooling and gas,while the distributed includes the virtual power plant scheduling optimization model and micro-energy station operation optimization model.Finally,the article compares and analyzes the status quo of multi-energy hybrid practice at home and abroad,and gives corresponding experience and enlightenment.(2)A collaborative scheduling optimization model for wind power,solar photovoltaic power,hydro power,thermal power and energy storage considering multi-energy hybrid is proposed.Firstly,based on the wind power-solar photovoltaic power-pumped storage power cooperative operation problem,the system output power model and the conventional scheduling optimization model are established.In order to solve the impact of wind power and solar photovoltaic power uncertainty on the stable operation of the system,a stochastic scheduling optimization model is constructed by means of robust stochastic optimization theory.Furthermore,for the optimization problem of wind power-solar photovoltaic power-hydro power-thermal power-energy storage coupling system operation,the basic structure of the coupled system is introduced,and the multi-objective scheduling model and solving algorithm are constructed by maximizing operating income,minimizing the cost of abandoning energy and minimizing the fluctuation of output.(3)A cooling,heat,electricity and gas coordinated scheduling optimization model for integrated energy system considering multi-energy hybrid is constructed.Firstly,the basic composition of the electrothermal interconnection system,the electrical interconnection system,and the cold and heat electrical interconnection system are designed layer by layer,and the functional characteristics of the energy equipment are clarified.Then,based on the influence of wind and solar uncertainty on the operation of the system,the CVaR method and the robust stochastic optimization method are used to construct the electrothermal coupling scheduling model,the electrical interconnection multi-objective scheduling model and the heat and cold electrical interconnection coordinated scheduling optimization model.Finally,the validity and applicability of the proposed model are verified by a case study of the above related models.(4)A distributed energy aggregation micro-energy station scheduling optimization model considering multi-energy hybrid is created.For the distributed development of energy sources,the issue of multi-type distributed energy aggregation utilization is discussed.On the one hand,the distributed power source aggregation virtual power plants such as wind power,solar photovotiac power and gas turbine are discussed,and the virtual power plant risk avoidance scheduling optimization model and low carbon scheduling optimization model are constructed.On the other hand,the system structure of the electrothermal coupling micro-energy station and the electrothermal gas coupling micro-energy station is introduced.Then,the output power model of different types of distributed energy sources is established,and then the risk avoidance optimization model of electrothermal micro-energy station and the multi-objective scheduling model of electrothermal gas micro-energy station are constructed,and the nonlinear objective function and constraints in the proposed model are linearized.(5)A multi-attribute decision-making evaluation method and balanced mechanism for different main part benefits of clean energy systems considering multi-energy complementarity is designed.First of all,based on the principle of index system construction,efficiency evaluation index of clean energy system is established from the four dimensions of economic benefit,technical benefit,environmental benefit and social benefit.And by combing the traditional evaluation method and using the cloud model to improve the traditional fuzzy comprehensive evaluation method,comprehensive evaluation model of clean energy system considering multi-energy complementarity is formed.Thus,it provides theoretical basis and decision support for the project evaluation and selection of clean energy system.Based on the above clean energy system efficiency evaluation system,the role relationship of the participants in the multi-type energy coupling system is analyzed from the inter-regional and inter-regional perspectives respectively.The benefit relationship of different types of participants is clarified along the energy transfer chain.Then,the optimal effect of integrated energy operation system is analyzed,and the benefit optimization analysis model is constructed.Finally,based on the typical benefit allocation method,a multi-agent benefit equilibrium model is constructed by using the kernel method and the Sharpe value method.And,the validity and applicability of the proposed model are verified by an example. |
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