Abstract:Energy storage systems will play a major role in the decarbonization of future sustainable electric power systems, allowing a high penetration of distributed renewable energy sources and contributing to the distribution network stability and reliability. To accomplish this, a storage system is required to provide multiple services such as self-consumption, grid support, peak-shaving, etc. The simultaneous activation of controllers operation may lead to conflicts, as a consequence the execution of committed services is not guaranteed. This paper presents and discusses a solution to the exposed issue by developing an engineering support approach to semi-automatically detect and handle conflicts for multi-usage storage systems applications. To accomplish that an ontology is developed and exploited by model-driven engineering mechanisms. The proposed approach is evaluated by implementing a use case example, where detection of conflicts is automatically done at an early design stage. Besides this, exploitable source code for conflicts resolution is generated and used during the design and prototype stages of controllers development. Thus, the proposed engineering support enhances the design and development of storage system controllers, especially for multi-usage applications.
The integration of modern energy storage systems into power grids allows the implementation of different use cases. However, the simultaneous activation of such use cases could lead to potential conflicting behaviour. Hence, this paper assesses the causes of conflicts within multi-functional energy storage systems. A methodology for the identification and handling of conflicts is suggested using a model-driven architecture approach together with the well-known Smart Grid Architecture Model (SGAM). The main goal of this paper is to demonstrate the usability of SGAM for the identification of potential controller conflicts. As a main result of this investigation the SGAM alone does not allow the identification of all possible types of conflicts; it needs to be complemented by other models.
Battery Energy Storage Systems (BESS) are starting to play an important role in today’s power distribution networks. They provide a manifold of services for fulfilling demands and requests from diverse stakeholders, such as distribution system operators, energy market operators, aggregators but also end-users. Such services are usually provided by corresponding Energy Management Systems (EMS). This paper analyzes the complexity of the EMS development process resulting from an evolving power utility automation.
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