Research On Dynamic Pricing Strategy Of Electricity Retailers Considering New Energy Consumption

With the deepening of China’s power system reform and the rapid development of new energy,the increasingly perfect renewable energy quota system has carried out the explicit allocation of renewable energy consumption weight to the main body of the power market.Under the framework of the new electricity market,as the intermediary body connecting the power generation side and the user side,the electricity retailers not only face the pressure of bearing the consumption responsibility of renewable energy,but also need to further optimize the electricity purchase and sales transaction decision to maximize the operating benefits.Therefore,the thesis focuses on the optimal electricity purchase strategy and dynamic pricing scheme of electricity retailers that take into account the consumption of new energy,taking the electricity retailers of self-owned wind power and photovoltaic power units as the subject.In terms of the uncertainty of new energy output,considering that the randomness and volatility of new energy output will seriously affect the electricity purchase trading decision of electricity retailers,this thesis adopts the scenario analysis method to describe the uncertainty of the new energy output represented by wind power and photovoltaic power,and establishes a scenario generation model based on Latin Hypercube Sample.A synchronous back reduction method considering distribution probability is proposed to absorb a large number of new energy output scenarios.The simulation results show that the proposed method can accurately obtain the probabilistic information of uncertain scenarios,and effectively help electricity retailers avoid market risks caused by uncertain factors on the basis of grasping the probability of typical scenario sets.In terms of electricity purchase strategy,in addition to facing uncertain factors such as new energy output and spot price,electricity retailers also need to reasonably allocate the electricity purchase proportion of various energy sources to meet the requirements of renewable energy consumption responsibility.In this thesis,conditional value-at-risk is used as a measure to establish a risk-based electricity purchase decision model for electricity retailers under the renewable energy consumption responsibility system.With the goal of minimizing conditional risk cost,the optimal electricity purchase allocation strategy of electricity retailers in the multi-energy market is obtained through numerical simulation.Furthermore,the influence of different degree of risk preference,weight of consumption responsibility and price of green certificate on the electricity purchase decisions of electricity retailers is further analyzed.In terms of dynamic pricing of electricity retailers,this thesis proposes an optimal decision-making method of dynamic time-of-use electricity price of electricity retailers considering user demand response.It combines demand-side response with electricity retailers’ business,and establishes a user demand response model based on demand price elasticity.At the same time,taking into account the characteristics of typical daily load curve of users,the fuzzy K-means clustering algorithm is used to dynamically divide the time-sharing period.On this basis,a day-ahead dynamic time-of-use electricity price optimization model of electricity retailers based on chaotic particle swarm optimization algorithm is constructed.The rationality of the proposed method to formulate the time-of-use electricity price is proved by an example,which solves the problem that the existing static time-of-use electricity price mechanism is difficult to give full play to the adjustable flexibility of the user-side load,realizes the optimal allocation of power resources,and improves the operating income of electricity retailers.The topic of this thesis is selected from the scientific research project of a provincial power trading center,which can provide reference for the decision making on purchasing and selling electricity and risk avoidance of electricity retailers,so as to improve their commercial competitiveness.