Research On Capacity Configuration And Dispatching Of Multi Energy Microgrid Considering Hydrogen Energy

With the rapid development of society,the depletion of fossil energy and environmental damage has seriously endangered the development of energy.Nowadays,using clean and renewable energy to replace traditional fossil energy has become a key research object for scholars from all walks of life.At present,a single energy source is no longer able to meet multiple load demands,and multiple complementary energy sources can provide users with more energy options.Therefore,it is urgent to reform the energy structure.Hydrogen energy,as a new and clean energy source,plays an important role in energy reform.Using hydrogen energy for energy storage or generation is also in line with China’s energy-saving and emission reduction policies,and is an inevitable choice for building a clean and low-carbon society and achieving sustainable development.Therefore,in order to meet the various load requirements of electric heating hydrogen,considering the advantages of flexible storage of hydrogen energy and low-carbon cleaning,coupled with thermal and electrical energy,this thesis constructs a multienergy microgrid system that takes into account hydrogen energy,and conducts the following research on the capacity optimization configuration and scheduling of the system:Firstly,based on the structural characteristics of a multi-energy microgrid system that takes into account hydrogen energy,the overall physical framework of the system is constructed from the energy input side,energy conversion and utilization side,and energy output side.Research and analysis were conducted on the characteristics of wind turbines,photovoltaic panels,electric energy storage,cogeneration units,gas boilers,electrolytic tanks,hydrogen storage tanks,and fuel cells in the system.Corresponding mathematical models were established based on the equipment principles,providing a theoretical basis for subsequent research.Secondly,in response to the issue of incomplete consideration of capacity allocation in traditional single objective functions,this thesis establishes a multiobjective capacity optimization configuration model based on the model establishment,with the goal of minimizing system economic costs,reliability costs,and carbon trading costs,and formulates relevant constraints and output strategies.In response to the shortcomings of conventional sparrow search algorithms in terms of convergence performance and search speed,the Piecewise chaotic initialization strategy,a fusion of differential evolution ideas and adaptive search strategies,as well as Cauchy and Gaussian mutation strategies,are introduced to improve the algorithm.The improved multistrategy sparrow search algorithm is used to solve the capacity optimization configuration model.The example results show that the improved algorithm can obtain the system’s capacity configuration with fewer iterations and higher convergence accuracy,the multiobjective capacity optimization configuration model established can effectively reduce the overall cost and carbon emissions of the system,considering the reliability and low-carbon advantages of hydrogen energy in capacity configuration,it reduces the rate of wind and light abandonment,Increasing the load interruption coefficient can effectively reduce the amount of system load interruption and improve energy consumption rate.Finally,in response to the uncertainty in a multi-energy microgrid system that takes into account hydrogen energy and the inability of conventional prediction data to meet optimal scheduling,this thesis comprehensively considers the source load uncertainty and scenario probability uncertainty of each scenario in multiple scenarios,and proposes a multi scenario multi-uncertainty robust optimization(RO)scheduling model.Establish relevant objective functions in three stages to minimize daily operating costs,and constrain the source load and scenario probability fluctuations of each scenario through uncertainty sets.Using column and constraint generation algorithms,the RO scheduling model is decomposed into a mixed integer form of the main problem and sub problems.Combining KKT conditions and the large M method,the nonlinear model is transformed into a linear model,and the model is solved using simulation software.The results of the example show that considering the uncertainty of various scene source loads and scenario probabilities in multiple scenarios comprehensively improves the robustness and conservatism of the system,avoiding overly optimistic RO.Taking into account hydrogen energy can effectively reduce daily operating costs in system scheduling.