Intelligent Computations in an Agent-Based Prosumer-Type Electric Microgrid Control System

The growing number of small prosumers, progress in construction of the renewable energy sources and opening of the energy markets lead to development of the concept of a microgrid. To increase efficiency of electricity consumption, production, and trading, energy managing systems (EMS) are being developed. In this paper we present a project of a complex EMS that will combine load scheduling, power balancing and smart trading methods to optimize electric energy costs of running a simulated research and education center. We present a concept of a distributed Agent-based Power Balancing System that controls the power flow in a microgrid by decentralized and distributed decision making. The program optimizes the operating (exploitation) cost of the devices in the microgrid by internally balancing, as much as possible, the produced and consumed power and by trading the remaining energy excesses or deficits on the external market. Agents associated with the devices cooperate using communication protocols. Their aim is to use the energy from renewable energy sources whenever it is only available, and at the same time limit use of the energy from the sources that are more expensive and less environment friendly.