Research And System Development On Joint Dispatching Optimization Of Wind-Light-Fire-Storage

The production and utilization of energy are closely related to human life.In recent years,in the context of energy conservation and emission reduction as well as the proposed dual carbon goals,the transformation and upgrading of the social energy structure is facing more severe challenges.In the process of transforming traditional energy into new energy,incorporating a higher proportion of renewable energy into the grid is a key part.Considering the limitations of wind and light based renewable energy such as randomness,intermittency,and anti peak shaving,unrestricted access to the grid will pose a series of challenges to the stable and safe operation of the grid,as well as peak shaving and frequency modulation.Conversely,restricting the integration of wind and light into the grid will lead to the occurrence of wind and light abandonment.Although traditional thermal power plants have certain peak shaving capabilities,frequent load ups and downs of thermal power units not only increase operating costs but also affect the safe operation of the units.Therefore,peak shaving of thermal power plants cannot meet the growing proportion of renewable energy output.The emergence of a series of energy storage methods can effectively reduce the peak shaving pressure of thermal power,while improving the absorption ratio of wind and light.Therefore,building a joint optimal scheduling model for traditional energy,renewable energy,and energy storage has important reference value for improving the utilization ratio of renewable energy,ensuring the safe operation of production scheduling,and achieving the national dual carbon goal.This article constructs a cogeneration model with wind light fire pumped storage as the main body,and conducts the following research on the absorption process of a given heat and electricity load.1.Based on the idea of modular modeling,the characteristics of each sub module in a distributed energy multi energy complementary system,such as wind power system,photovoltaic system,thermal power plant system,and pumped storage system,were analyzed.The subsystem using modular modeling can more comprehensively reflect the performance status of different units under different operating conditions,as well as the degree of achievement of the objective function under different combinations,and better highlight its flexibility.At the same time,from the perspectives of economy and security,this article proposes an optimization model that considers multi-objective problems,and from the perspective of system efficiency,proposes an optimization model for system exergy efficiency as the focus of research.2.Aiming at the proposed objective function and the established mathematical model,considering their constraints under different combinations,an improved MOPSO-NSGA2 algorithm is used for optimization.Due to the large number of constraints and decision variables contained in the model,in order to avoid dimensional disasters affecting the optimization effect of the algorithm and to reduce excessive time complexity,this paper proposes an evolutionary mechanism based on the synergy of random variable decomposition and result feasibility,which has a good effect on obtaining the optimal solution of the algorithm.3.Based on the multi-objective optimization model established in this article,optimization and empirical analysis were conducted,and the following conclusion was drawn:compared to systems without pumped storage,distributed energy systems with pumped storage machines perform better in terms of revenue,load fluctuations of thermal power units,proportion of wind and solar energy consumption,and source load matching.This fully demonstrates the comprehensive improvement of energy storage devices for multi energy complementary systems.In addition,for optimizing the exergy efficiency model of the system,research has shown that in order to improve the overall exergy efficiency of the system,it is necessary to improve the efficiency of thermal power units and the proportion of renewable energy consumption.4.Based on service-oriented architecture and MVVM design ideas,a software framework with wide applicability and stable performance has been developed.Using this framework and based on the natural conditions of the application site,users select different energy systems,complete the optimal load distribution of the multi-energy complementary cogeneration model through collocation and combination,with the algorithm as the core,and participate in the actual system operation based on the optimization results.