Multi-stage Smart Grid Optimisation with a Multiagent System

Increasing the usage of renewable energy and electromobility are high priority goals for several countries and organisations. Energy from renewable energy sources, like wind and solar, have disadvantages of being highly variable and volatile. Furthermore, the occurrence of renewable energy and energy demand is asynchronous. This aggravates any successful integration of renewable energy sources into today’s energy infrastructures. For this reason smart grid solutions became an appropriate approach for integrating renewable energy resources [2]. According to Gharavi [1] a smart grid can be defined as a electric system that uses information, two-way, cybersecure communication technologies, and computational intelligence in an integrated fashion across electricity generation, transmission, substations, distribution and consumption to achieve a system that is clean, safe, secure, reliable, resilient, efficient, and sustainable. In general smart grids are leading to the goal of more environment-friendly energy production. Moreover they allow the integration of electric vehicles as mobile energy storages that gives rise to less expensive transportation by using electromobility concepts at the same time. The problem domain was investigated in several applied research projects [4]. In this work we focus on the experience made in three German research projects from the Electromobility Showcase initiative Berlin-Brandenburg or ”Schaufenster Elektromobilität Berlin-Brandenburg”.