Design Of Electricity Plans And Energy Imbalance Settlement Mechanism To Active Demand Response Of Power Demand Side

Demand response(DR)is regarded as one of the most important solution to the increasing peak-valley differences,renewable energy sources and transformation of energy structure.Before the establishment of the spot electricity market in China,the DR mechanism and the Energy Imbalance Settlement(EIS)mechanism play a crucial role in stimulating demand side participation in load management and promoting a smooth transition to market-oriented reforms.The main contributions of this work are summarized as follows:(1)A novel DR plan is proposed,which is named as electricity plans for industrial and commercial customers.The design of electricity plans is studied in depth.In order to obtain market segmentation,pattern index clustering is used to identify the load characteristics of industrial and commercial customers.Taking customer satisfaction with electricity bills and the way of electricity consumption into account,a customer choice behavior model based on multinomial logit model(MNL)is built.To measure the economic value of electricity plans,a comprehensive evaluation model for electricity plans is proposed based on cost-benefit analysis.On this basis,an optimization model for designing electricity plans is established,in which maximizing the benefit cost ratio is taken as the optimization objective.At last,a case is studied to verify the economic value and the role of the active participation in load management of electricity plans.(2)A novel EIS mechanism with a piecewise linear penalty pricing scheme is proposed,learning from the performance-based regulation(PBR)in distribution systems.For optimizing the parameters in the proposed EIS mechanism,a stochastic bilevel model is presented considering two kinds of stakeholders involved,namely the Power Exchange(PX)and retailers.In the upper-level model,an optimal parameter setting model for policymakers to minimize the variance of deposit in the balancing account of PX is presented.On the other hand,a decision-making tool for retailers under the Renewable Portfolio Standard(RPS)is developed in the lower-level model.As a self-balance measure of retailers,flexible demands are incorporated into the lower-level problem.Consumer psychology is applied to quantify customer consumption adjustments in response to the financial incentives given by retailers.The risk faced by the retailers is modeled using conditional value-at-risk(CVaR),taking into account the uncertainties associated with renewable energy production and customer demand.Simulation results of a provincial electricity market in China show that the proposed method can effectively motivate retailers to improve their imbalance management capability and assist policymakers in determining the parameters of the EIS mechanism.Besides,the proposed method provides insights into the impacts of parameter setting of the EIS mechanism on the behavior and performance of retailers.