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.

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.

A significant integration of energy storage systems is taking place to offer flexibility to electrical networks and to mitigate side effects of a high penetration of distributed energy resources. To accommodate this, new processes are needed for the design, implementation, and proof-of-concept of emerging storage systems services, such as voltage and frequency regulation, and reduction of energy costs, among others. Nowadays, modern approaches are getting popular to support engineers during the design and development process of such multi-functional energy storage systems. Nevertheless, these approaches still lack flexibility needed to accommodate changing practices and requirements from control engineers and along the development process. With that in mind, this paper shows how a modern development approach for rapid prototyping of multi-functional battery energy storage system applications can be extended to provide this needed flexibility. For this, an expert user is introduced, which has the sole purpose of adapting the existing engineering approach to fulfill any new requirements from the control engineers. To achieve this, the expert user combines concepts from model-driven engineering and ontologies to reach an adaptable engineering support framework. As a result, new engineering requirements, such as new information sources and target platforms, can be automatically included into the engineering approach by the expert user, providing the control engineer with further support during the development process. The usefulness of the proposed solution is shown with a selected use case related to the implementation of an application for a battery energy storage system. It demonstrates how the expert user can fully adapt an existing engineering approach to the control engineer’s needs and thus increase the effectiveness of the whole engineering process.

Due to the increasing power system complexity caused by a higher penetration of distributed energy resources, advanced engineering methods are required which can handle power system aspects together with information and communication technologies and new automation concepts. In order to handle such a complexity, various engineering concepts have been introduced by providing support such as guidelines, code generation, and reasoning for the development of smart grid use cases and applications in the last few years. Nevertheless, none of these approaches covers all phases in the engineering of smart grid solutions and the corresponding requirements. In this paper, two approaches-focusing on rapid development and on the identification of application inconsistencies-are selected and combined to cover a wider scope of the requirements for smart grid automation application engineering. The integration of the two approaches is shown using an example use case, where multiple functions for a battery energy management system are designed, implemented, and validated.