Assessing the flexibility potential of the residential load in smart electricity grids - A data-driven approach

This paper proposes a framework for assessing the sensitivity of the performance of a hypothetical demand response (DR) program to consumers' preferences, should they enable DR and become prosumers. The proposed framework contains a data analytics module and a DR simulation module. The data analytics module, processes the historical data to select informative subsets and define simulation scenarios to investigate the performance of the DR module. The DR module is, in essence, an optimization problem that seeks to meet the objective of the distribution system operator (DSO); it minimizes active power losses, by utilizing the potential flexibility prosumers can provide. The optimization problem is solved subject to physical and economic constraints. It considers the fact that cost of energy for the prosumers, after implementing DR, remains less than or equal to its value before that. We defined six scenarios to investigate the sensitivity of the performance of DR on prosumers preferences, in four representative days (so called case studies). Our results demonstrate the effectiveness of the proposed framework in helping the DSO assessing the potential flexibility of various users, and from there, improving the success rate of implementing DR in energy systems of the future.