Energy Management Framework for Transactive Energy Communities

Transactive Energy Communities (TECs) are in a crescent evolution, being one of the most promising solutions for integrating renewable generation and managing energy flexibility in communities. Renewable energy solutions, like photovoltaic, are very important to the planet but bring new problems to the grid, since they are variable, non-dispatchable and present a strong mismatch with the demand in most buildings. Therefore, the management of flexible resources at the community level, namely using energy storage, is crucial to ensure the matching between local generation and demand in such communities. This work proposes a framework that optimizes the energy selling prices to the community and the use of an energy storage unit by the buildings. Such a framework optimizes the energy transactions of a transactive energy community composed of four buildings, and an energy storage unit at the community level. To ensure, three different algorithms are used: (i) fuzzy logic, (ii) reinforcement learning, and (iii) a management system with the gurobi optimizer. The fuzzy logic algorithm computes the energy tariff price between a building and the community. Using such a price, the management system will optimize the use of an energy storage unit to minimize the total energy cost of the community. The reinforcement learning will ensure the connection between the management and fuzzy logic systems. The results showed that by assembling a dynamic tariff system, using a fuzzy algorithm, it is possible to potentiate the transactions between buildings. In future transactive communities, with energy storage units, this system ill potentiate collaboration between buildings, which can consequently represent economic benefits for the buildings.