Data Acquisition Systems for Battery Energy Storages : An alternative DAS implementation for improved performance, security, and cost

During recent years, battery energy storage systems (BESS) have become significantly essential as they help the energy transition. Not only do they reduce the dependence on fossil fuels, but they also play a vital role in the transition to electric vehicles and the use of energy during peak periods. Despite the many benefits of BESS, they also come with various challenges. To be able to manage parameters such as temperature, voltage or current, BESS is dependent on Supervisory Control and Data Acquisition (SCADA). This system is then often relying on Data Acquisition Systems (DAS) which handles the data collection as well as the data transfer to a storage system. This set-up often involves some operational and cybersecurity risks, along with some cost aspects. The purpose of this thesis is therefore to analyze the separation of DAS from SCADA and the associated advantages and disadvantages. It will involve suppliers and their proposed DAS solutions by focusing on data extraction, compatibility to storage systems, security, costs and scalability. The goal is to determine whether the DAS solutions can retrieve large volumes of data from the BESS without affecting the operational part of the SCADA system. From the analyses, recommend the best solution for BESS. The study contains a literature study including definitions of DAS and SCADA, DAS technologies as well as a description of the current set-up used by Vattenfall. The subsequent chapter describes the separation of DAS from SCADA. It includes an analysis about operational risks, cybersecurity and the cost. Three solutions along with their respective architecture are presented. A case study was also conducted. It explains the comparison of three file format, CSV, JSON and XML. The file formats were also compared using the bandwidth rate fiber (1000 Mbit/s), Ethernet (100 Mbit/s) and mobile broadband (50 Mbit/s). The results present three different solutions: solutions 1, 2 and 3. While all three solutions have direct sensor input, are compatible with cloud storage and has fast sampling rate, only solution 2 and 3 have a high scalability. This means that new units can be added when needed. Solution 3 offers per-channel pricing, while solution 2 includes a built-in storage and the centralized setup is the most economical. Therefore, solution 2 and 3 are best suited for the purpose. When it comes to determining the bandwidth of the battery park, the case study shows that if fiber connection is available, then the choice of file format does not matter. However, as all solutions use Ethernet to transmit data, CSV is the most suitable file format. This is as CSV does not occupy as much of the bandwidth as the other two format when transmitting data to the storage.