Research On Uncertainty In Energy Dispatching Process Based On Fuzzy Theory

Energy is an important material basis for the operation and development of human society,Human beings use energy to vigorously develop production.However,the current global energy supply model is single,each energy system operates independently of each other,the effective utilization of renewable energy is low,and the related environment problems brought by energy consumption is also getting worse.The rise of the concept of the energy Internet provides new ideas for optimizing the layout of the power grid,promoting the active consumption of renewable energy,and improving the ability to optimize the allocation of energy resources.However,the uncertainty in the process of energy optimization and dispatch has become a major influencing factor restricting the optimization of energy structure and the improvement of system economic benefits.Therefore,this paper starts from improving the stability and economy of the energy dispatch process,and focuses on the uncertainty factors and uncertainty optimization methods in the energy dispatch process.Mainly completed the following research work:First,it briefly introduces the global energy consumption,energy development trends,and the influencing factors of energy optimization scheduling,and in-depth analysis of new energy consumption technologies,multi-energy complementary integrated energy systems,and the current research status of uncertain optimization problems at home and abroad;The related principles of the uncertainty problem,the current methods of solving and analyzing the uncertainty problem,and the advantages and disadvantages,briefly describe the application of Fuzzy theory in the energy dispatching process.Second,in the power system,take the regional distribution network that takes into account the uncertainty of demand response as an example.Establish a user load characteristic model by analyzing user load characteristics.use triangular fuzzy numbers to describe the uncertainty of demand response and establish a price-based demand response uncertainty model.A Stackelberg game economic model of the distribution network is established with the goal of minimizing the operating cost of the distribution network on the distribution network side,maximizing wind power consumption,and minimizing the user's electricity bill on the load side,The two achieve game equilibrium by optimizing the quasi-real-time electricity price strategy set on the distribution network side and the demand response strategy set on the load side.Taking the modified IEEE 30-node system as an example,an improved teaching and learning optimization algorithm is used to obtain the equilibrium solution of the Stackelberg game model.Third,in the multi-energy complementary integrated energy system,take the electricity-gas interconnected integrated energy system of an industrial park that takes into account the uncertainties of source and loads as an example.Firstly,an IENGS model of the park's electricity-gas interconnection considering P2 G technology is established.Secondly,starting from both the source and the loads,the fuzzy membership parameters are used to characterize the uncertainty of new energy and load,and the establishment of wind power and electricity,The credibility fuzzy opportunity constraint model of air load uncertainty solves the fuzzy scheduling problem through clear equivalence class conversion.