Framework for smart grid to implement a price elasticity-based peak time rebate demand response program - Puppala, Rajendhar; Jeyaraj, Belwin Edward; Isaac, Jacob Raglend; CH, Hussaian Basha (Frontiers in Energy Research, 2023)
The smart grid model is developed with some changes to help in implementing a demand response program which was initially developed for a Pecan Street project. Correspondingly, the real-time solar and load data are collected from the data port for the city of Austin. A single day is selected for our analysis of all four seasons of the year. The flat rate, and real-time and day-ahead pricing information are collected from ComEd. The key challenge for addressing business problems is the flexibility of consumption. However, without considering the properties of loss aversion, the system would not be a practical solution. So, in this article, a dynamic demand response program based on price elasticity that integrates loss aversion characteristics is proposed. The proposed system is compared for all pricing schemes and all seasons. Four scenarios are created for peak time rebate with different combinations of loss aversion factor values and all the possible combinations of rebates. This article directs how these combinations could change the demand curve and how the utility can make a decision about the specific importance of the criteria, such as the total demand carrying capacity, peak demand reduction, and in obtaining optimum profit for utility and the consumer.