Coordinated Operation of the Constituent Components of a Community Energy System to Maximize Benefits while considering the Network Constraints

Abstract

Smart community with locally generated renewable energy is a new paradigm that leads to a system that is more sustainable, secure, and cost-effective to the community while enabling connection of more distributed energy resources. In this paper, a method to maximize the utilization of the renewables while maximizing the profit of a smart community within system constraints was suggested by introducing an optimum schedule of smart appliances in the community. Further dynamic line rating of the network connection is considered to investigate the advantage of using the dynamic rating against static rating. Different operating modes based on the variations of available renewable energy generation, wind speed, tariff, grid curtailment, and user preferences were investigated. A modified genetic algorithm-based optimization was implemented to obtain the optimum smart community's appliance schedule. The optimum appliance schedules were obtained considering different case studies representing possible operating modes of the system. The simulations show that the use of dynamic line rating and optimum appliance schedule provide higher profit to the community. The algorithm managed to run the optimization with 12,500 controllable entities within an average execution time of 2000s.