| Demand response strategy is to enable users to transfer or reduce load in specific periods by means of electricity price and incentive,so as to achieve the purpose of cutting peak and filling valley and improving the stability of power system.However,the relationship between different types of demand response strategies and their impact on power system reliability still need to be explored.According to that,relying on the project "Risk assessment and optimization of active distribution system considering demand side response"(51607051)supported by National Natural Science Foundation of China,this paper studies the relationship between system reliability demand and demand response strategy through progressive structure.Firstly,this paper proposes the method of typical day selection and period partition to lay the foundation for demand response strategy;secondly,this paper studies the relationship between time-of-use(TOU)price and peak incentive to verify the improvement effect on system reliability of the two methods;finally,this paper proposes a price-based demand response decision scheme for different types of users under various reliability requirements,which establishes a direct link between reliability demand and price formulation.The main work and innovation of this paper are as follows:(1)Research on typical day selection and period partition based on fuzzy clustering.The selection of typical days and period partition are the basis of demand response research.The typical daily load curve selected by traditional method is difficult to represent load characteristics of all samples,while the traditional period partition method can not meet the needs of different situations.Therefore,this paper selects the optimal typical daily load curve by fuzzy c-means algorithm(FCM)and proposes three kinds of time division methods with different characteristics based on fuzzy clustering.(2)Research on optimal demand response decision-making considering TOU price and peak incentive.The traditional time-of-use(TOU)scheme is difficult to consider interests of both supply and demand sides,while the traditional peak load control strategy does not take into account the impact of TOU price on load curve.Based on that,this paper establishes the TOU price optimization model considering interests of both supply and demand sides and proposes a simulated annealing particle swarm optimization algorithm(SAPSO)to solve the problem.On the basis of TOU price,according to the principle of power shortage cost and proportional allocation,this paper establishes an incentive based peak load regulation model to further reduce the peak load.(3)Research on the price-based demand response decision scheme for various requirements of power grid reliability.Traditional demand response research evaluates the impact of TOU price on power system reliability by optimizing the TOU price,so it is unable to obtain the corresponding TOU price scheme according to the differentiated reliability demand.Therefore,in this paper,a multi-objective simulated annealing particle swarm optimization algorithm(MO-SAPSO)is proposed to solve the TOU electricity price optimization model considering system reliability.The third-order Hermite interpolation algorithm is used to fit the Pareto front curve of the dual objective function,and the three-layer back propagation back propagation(BP)neural network is trained to obtain TOU price schemes under various reliability requirements.In addition,this paper also uses the SAPSO algorithm to solve the TOU price scheme under optimal reliability level of high reliability demand system through the Bi-level optimization method. |
PDF Full Text Request