Optimization Model on PeakValley Time Electricity Consumption Based on the satisfaction degree of residential electricity demand and the result of peakvalley time division, this paper designs a peakvalley power dispatching optimization model. Firstly, in order to analyze the daily electricity consumption of residents under the current ladder price environment in Macau SAR, the paper team visited the residents of a community in Wanzai, Macau, and obtained the data needed for the paper. Secondly, based on the existing ladder price situation in Macau SAR, the paper simulated the peakvalley instant electricity price model by integrating the factors of residentsu0027 satisfaction, and built a model through MATLAB software. Calculating and analyzing the electricity consumption of the community; The simulation results show that setting the peak and valley time reasonably on the basis of the ladder price can effectively smooth the residential load curve while fully guaranteeing the functions of the original ladder price, thus further achieving the purpose of guiding the residential users to consume electricity reasonably and filling in peak and valley, which has certain significance for practical application.

A Stochastic DecisionMaking Model for an Electricity Retailer with Intermittent Renewable Energy and Shortterm Demand Response This paper presents a shortterm decisionmaking model for an electricity retailer with selfproduction of renewable energy. In the proposed model, a new trading mechanism for shortterm demand response (DR) between retail customers equipped with smart grid technology and an electricity retailer is presented. Through the proposed trading mechanism, retail customers submit shortterm DR offer curves to the retailer in order to increase or decrease their energy consumption for a given time period at favorable prices. On the other hand, the retailer decides its involvement in the shortterm DR market for every time period to avoid unfavorable prices in the realtime market and, thus, maximize its profit. The stochastic nature of dayahead and realtime prices, renewable energy production, electricity demand, and DR participation of retail customers is taken into account in the formulation of this work. The resulting model is a mixedinteger linear programming (MILP) which can be solved by existing commercial solvers. Case studies using realworld data are performed to demonstrate the effectiveness of the proposed model.