On-grid joint energy management and trading in uncertain environment

Consumers in smart power systems may control and manage the energy consumption of their appliances, minimizing peak-to-average power ratios (PAPR), total peak load demands, and their monthly energy expenditures by utilizing the joint energy management and trading framework (JEMTF). The integrated framework of energy management and trading is critical to the integrity of the distribution power system. The role of JEMTF becomes even more challenging when the model is perturbed. This paper discusses the development of a robust optimization technique for solving uncertainty in JEMTF. The JEMTF pattern is perturbed by a number of practical constraints like human interaction factor, load shedding pattern, peak clipping and consumers preferences pattern. The proposed model considers uncertainty in all these constraints in a JEMTF between nearby microgrids, which allows the distribution system to use power at a lower cost. The proposed model focuses on a two-stage system. The first stage is a distribution system that splits into a number of micro-grids by regulating the power demand of each micro-grid using a novel energy management strategy. While, in the second stage, the locally generated energy is exchanged among the micro grids using energy trading mechanisms that meet the needs of customers without placing undue strain on the utility company. The result shows that the suggested strategy lowers the power costs of micro grids by utilizing a high proportion of self-generated electricity intelligently.