Impact of Parametrization of Battery Energy Storages on Multi-AgentEnergy Systems with a High Share of Renewable Energy Sources

Abstract

With the increasing share of distributed renewable energy sources not only the need for distributed energy storages rises, but also the need to coordinate those storages in the context of their local micro-grid. This publication illustrates the impact of battery energy storages on the overall performance of a district energy system. The energy system is controlled in a distributed way by using a multiagent approach that is scheduled by a market-mechanism. This market-mechanism allows to coordinate many individual agents with only few restrictions. The individual agents are flexible in the internal approach to forecast power supply or demand, allowing easy development of agents using individual algorithms.Besides pure consumer or producer agents, the battery storage forms a prosumer agent that can consume energy in some time-steps while supplying energy in others. By this, battery agents provide flexibility to the micro-grid while also aiming to generate profit for the owner. This approach is therefore attractive to both, the district energy system and the battery storage operator. The presented battery agents use model predictive control to determine the optimal operation strategy/bid for the upcoming time horizon. The determination of optimal strategy does not only assume losses but also takes the resulting degradation of the battery-cells into account. In a case study, we show the impact of battery storages on the overall system performance. As a main part of the publication, a sensitivity study reveals the importance of the individual parameters and how the revenue of the storage agent is affected. By adapting the charging and discharging power by 20 %, the profit can be increased by 33 % for the presented case