Optimal Configuration And Operation Strategy Of User Energy System

The user energy system is a kind of micro multi-energy system near the user side.As the terminal network of the energy Internet,it can realize extensive access to renewable energy.With the development of the energy Internet and user terminal smart devices,multiple types of heterogeneous energy in the user energy system show strong coupling and complementary characteristics,the two sides of supply and demand have the characteristics of multi-interaction,but the randomness and volatility of renewable energy and the multi-interaction mode of supply and demand also increase the complexity and uncertainty of system planning and operation.In the new generation of energy Internet environment,how to optimize the capacity configuration of each unit and equipment and operation strategy in the user energy system is the key to improve the energy utilization rate and realize the green,economic and reliable operation of the system.In this dissertation,the user energy system is taken as the research object,and the capacity configuration and operation strategy of the user energy system are studied around multi-energy complementarity,supply-demand collaboration,renewable energy consumption and uncertainty of the system.The main research work is as follows:(1)In the user energy system,there are multiple energy flows such as gas,electricity,cooling and heating,and the coupling relationship between the energy flows is complex.In order to analyze the coupling relationship between the energy flows of the system,the power models of the key units and equipment in each subsystem are established and studied,and two modeling methods for analyzing energy flows of the system are presented.The first method takes the electrical energy flow and thermal energy flow in the system as the research object,and establishes the electrical energy flow and thermal energy flow hubs.Through the collection and distribution of electrical and thermal energy flow by the electrical and thermal energy flow hubs,the analysis of the system energy flow can be simplified.The second method is based on the energy hub model,and a hierarchical method is proposed to divide the system into the energy distribution layer and the energy conversion layer,which can clarify the relationship between the energy flows,and the energy flow coupling matrix can be quickly established through the cascade relationship between layers.These two energy flow modeling methods provide the basis for subsequent user energy system capacity configuration and operation.(2)For the independent user energy system,the reliability index of power supply and heating supply based on energy flow has been established,considering the complementary characteristics of multiple energy sources in the user's energy system,the operation strategy of considering multiple energy complementarities,promoting the consumption of renewable energy and improving energy efficiency is put forward,and a model of optimal capacity configuration of user energy system considering the comprehensive evaluation indicators of system investment costs,primary energy consumption,carbon dioxide emissions,and energy supply reliability is established.The proposed method for optimizing the capacity configuration of user energy systems for multi-energy complementarities gives full play to the complementary roles of source-source,source-charge and electricity-heat in the system,promotes the consumption of renewable energy and improves the economy of system allocation on the premise of ensuring the reliability of system energy supply.(3)Based on the coupling,complementation,mutual substitution,and interaction between different forms of energy such as gas,electricity,cooling,and heating in the user energy system,the integrated demand response mechanism is introduced into the capacity configuration and operation optimization model,and the model of the integrated demand response resources to participate in the internal and external interaction of the system are established,and the two-layer optimization model for the capacity configuration of user energy hub considering the coordination of supply and demand is established.The upper model optimizes the capacity of each unit and equipment in the user energy hub,while the lower model optimizes the operation strategy of the system on typical days in different seasons.The upper and lower layers are solved by improved particle swarm algorithm and mixed integer linear programming method.The implementation of integrated demand response realizes load peak clipping and valley filling,promotes the consumption of renewable energy and improves the economics of system planning and operation.(4)Aiming at the problem of consumption of renewable energy in user energy system,the main measures of consumption of renewable energy and the influence of uncertainty of renewable energy on system planning and operation are analyzed,and a two-stage adjustable robust optimization model of capacity configuration for user energy system considering consumption of renewable energy is established.In the first stage,the consumption of renewable energy is considered,and the economy of the system is taken as the goal to optimize the capacity configuration of the main units and equipment of the system in the worst scenario.In the second stage,the uncertainty of renewable energy power generation is considered,the worst scenario of the system is searched,and the operation strategy under the worst scenario is optimized.Strong dual theory and column constraint generation algorithm(C&CG)are used to transform and solve the robust optimization problem of min-max-min structures.The algorithm can solve the two-stage robust optimization model quickly and effectively.The impact of renewable energy consumption measures and costs on the renewable energy consumption and economy of the system is analyzed,and appropriate suggestions are provided for decision makers.(5)Further considering the uncertainty on both sides of the supply and demand of the user energy system,based on the flexible interaction and complementary characteristics of the integrated demand response in the user energy system,the integrated demand response mechanism is introduced into the system multi-stage scheduling,and a two-stage robust-stochastic scheduling optimization model considering integrated demand response for day-ahead scheduling and intra-day real-time regulation of user energy systems is constructed.In the day-ahead stage,the worst-probability scenario is considered,and the output power of each power generation,heating unit,energy storage equipment,etc and the interactive mode,response capacity and time,etc.of integrated demand response are determined.Based on the optimization results of the day-ahead stage,the worst-probability scenario is searched,and the regulation scheme of the system under the worst-probabilistic scenario are determined.Through the integrated demand response resources to participate in the multi-stage scheduling of the system,the interaction flexibility of the integrated demand response is improved,and the economy and self-sufficiency of the system are improved.The robust-stochastic optimization model can improve the ability to resist uncertain risks of the system on both sides of supply and demand,and the worst-probability scenario it seeks has strong robustness and effectiveness.