Research on Pricing Mechanism of Time-of-Use Electricity Price Based on Multiple Cost Structure
The construction of a new type of power system puts forward new requirements for improving the time-of-use electricity pricing mechanism.Aiming at the current research on time-of-use electricity prices that mostly focus on market mechanisms,and insufficient attention to the relationship between the electricity price setting menu and the actual power supply cost structure,this paper proposes a time-of-use electricity price model based on diversified power supply costs and demand response.The model takes into account economy and reliability,establishes a load slicing and cost pricing mechanism that considers demand reduction,clarifies the diversified cost structure of power supply configuration,and defines the variable cost,fixed cost and reliability loss cost of various power sources.Fundamental research is carried out on the analysis of electricity sales revenue,the actual variable cost of the power supply,the loss of power supply reliability and the recovery of fixed costs.Through the verification of related calculation examples,the influence of various power accident rates on the surcharge rate in the model,as well as the correlation between various power accident rates,fluctuations of different load levels,and time-of-use electricity pricing,are studied.The model established in this paper is effective in improving the adaptability of time of use electricity prices,correctly guiding users'electricity consumption behavior and promoting peak-shaving and valley-filling.At the same time,the model can optimize the capacity management of various power sources in a diverse new energy grid-connected environment to ensure the cost recovery of peak power sources,thereby effectively balancing the interests of the power source and the user side,and taking into account the adequacy of power supply,reliability and economic goals.
demand responsetime-of-use price mechanismfixed costvariable costreliability costpeak shaving and valley filling
NETL
NSTL
万方数据
维普
