This paper presents the requirements and a concept for a modular Smart Grid simulation framework based on an automatic composition of existing, heterogeneous simulation models. The composition problem is broken down into different layers, for each of which first concepts for solving the problem are presented. A prototype showing the feasibility of the presented concept has been developed. First simulation results of a Smart Grid scenario including electric vehicles as well as renewable energy sources are presented. Finally, the limitations of the prototype and possible improvements are discussed.
Unlocking and managing flexibility is an important contribution to the integration of renewable energy and an efficient and resilient operation of the power system. In this paper, we discuss how the potential of a fleet of battery-electric transportation vehicles can be used to provide frequency containment reserve. To this end, we first examine the use case in detail and then present the system designed to meet this challenge. We give an overview of the tasks and individual sub-components, consisting of (a) an artificial neural network to predict the availability of Automated Guided Vehicles (AGVs) day-ahead, (b) a heuristic approach to compute marketable flexibility, (c) a simulation to check the plausibility of flexibility schedules, (d) a multi-agent system to continuously monitor and control the AGVs and (e) the integration of fleet flexibility into a virtual power plant. We also present our approach to the economic analysis of this provision of a system-critical service in a logistical context characterised by high uncertainty and variability.
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