促进用户负荷特性优化的分时电价机制设计方法OA

Under the background of changes in supply and consumption patterns of power system,this paper proposes a design method for a time-of-use(TOU)tariff mechanism to encourage coordination between user and power grid and promote peak-shaving and valley-filling.Based on the analysis of load distribution characteristics for three types of users(industrial,commercial,and residential users),the paper employs the hierarchical clustering method to optimize peak and valley periods for different seasons.By introducing deep valley periods to solve the problem of pricing inaccuracy in the original TOU tariff mechanism.Taking user elasticity and the generation costs as constraint,the paper aims to reduce user electricity costs and widen the peak-to-valley price difference to promote user participation in grid interaction.The paper utilizes the quantum genetic algorithm to solve the optimization problem of TOU pricing periods division.Through case studies,the peak-shaving and valley-filling effects of the improved TOU tariff mechanism were evaluated.The results validate that the proposed mechanism can not only reduce user electricity costs but also effectively shift the load during peak periods,and then alleviate the problem of periodic and seasonal power supply pressure.