Research On Trading And Optimal Scheduling Strategy Of Integrated Energy System Based On Stochastic Evolutionary Game

Under the “double carbon” target of China,the integrated energy systems improve the utilization rate of new energy through complementary means of energy conversion,effectively alleviating the energy crisis,and have broad development prospects.If the integrated energy system wants to realize multi-energy complementary through the active participation of supply and demand side in energy trading,the formulation of bidding strategy and time-of-use price strategy based on demand response becomes the key.The volatility and intermittence of renewable energy power generation and the diversity and randomness of users’ energy demand will bring great difficulties to the system supply and demand balance.Therefore,it is of great significance to study the trading and optimal scheduling strategies of integrated energy system with stochastic matching of supply and demand.In this thesis,the following aspects are studied on the supply and demand side bidding strategy of the integrated energy system,the optimal time-of-use price of demand response,and the optimal scheduling of the system with stochastic matching of supply and demand:(1)Aiming at the requirements of power demand response and optimal scheduling of integrated energy system,the basic architecture of integrated energy system is constructed,and the demand response mechanism and stochastic evolutionary game are introduced.(2)Aiming at the random interference factors in uncertain environment seriously affects the bidding behavior of power generation and consumption of Wind-Photovoltaic-Hydrogen integrated energy system.So,the random interference term of Gaussian white noise is introduced into the replication dynamic equation,which constructs the stochastic evolutionary game model of Wind Photovoltaic Hydrogen groups under asymmetric information.And the model is solved by using It(?) stochastic differential equation theory.Photovoltaic Hydrogen stochastic evolutionary game system are analysed from three aspects of the quotation strategy,incentive measures and enterprise income.Taking the Wind Photovoltaic Hydrogen groups bidding strategy game as an example,dynamic evolution simulation is carried out.The results show that the stochastic evolutionary game model can more accurately reflect the evolution process of bidding strategy of various groups under the interference of random factors,which can more really reflects the dynamic change process of bidding behavior of power generation enterprises and power purchase enterprises in the real environment.(3)Aiming at the problem that the regulation of time-of-use price in demand response affects the economic operation of integrated energy system,an optimal time-of-use pricing strategy based on stochastic evolutionary game is proposed.Considering the price elasticity coefficient and useing K-means algorithm to divide the peak-flat-valley periods of daily load on the demand side;considering customer satisfaction and power fluctuation cost,taking the maximum revenue on the power supply side and the demand side as the objective function,the stochastic evolutionary game model of optimal time-of-use price is constructed and solved.The example analysis verifies that the proposed optimal time-of-use pricing strategy improves the income of the power supply side and reduces the expenditure of the demand side to a certain extent.(4)Aiming at the randomness and uncertainty of renewable energy output in the integrated energy system,an optimal scheduling strategy of integrated energy system with stochastic matching of supply and demand is proposed.Consider the randomness of the output of renewable energy such as wind and photovoltaic,it is proposed to use Kantorovich distance index to generate the optimal wind and photovoltaic output scenario,which transforms the stochastic optimization problem into a deterministic optimization problem.Considering the impact of the energy storage station on the matching of dispatching supply and demand,taking the minimum system scheduling cost and the minimum environmental pollution cost as the objective functions,the multi-objective optimal scheduling scenario model of integrated energy system is constructed,the stochastic evolutionary game algorithm is used to solve the model.The example analysis verifies that the proposed optimal scheduling strategy can effectively improve the utilization rate of renewable energy and reduce environmental pollution.