Ivelin Andreev
Ivelin Andreev has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Georgios Gkoumas
Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece
1 shared publication - Marian Graurov
Upkip AS, Industrial IoT, Cloud & AI Systems, 3616 Kongsberg, Norway
1 shared publication - Panagiotis Stavropoulos
Laboratory for Manufacturing Systems and Automation (LMS), Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patra, Greece
1 shared publication - Panagis Foteinopoulos
Laboratory for Manufacturing Systems & Automation (LMS), Mechanical & Aeronautical Engineering Department, University of Patras, 26504 Patras, Greece
1 shared publication
Latest Publications
- Open Access
Industrial Energy Storage System Selection: A Decision Framework and Digital Implementation Demonstrated Through a Peak-Shaving Case Study
The increasing demand for energy, rising electricity costs, and the growing need to reduce carbon emissions have driven industries toward the adoption of Renewable Energy Sources (RES) and Energy Storage Systems (ESS). However, selecting the most suitable ESS for industrial peak-shaving applications remains a complex decision involving technical, economic, and operational considerations. This paper proposes a practical and structured methodology for ESS selection that integrates conventional performance criteria with Industry 5.0 (I5.0) requirements, emphasizing sustainability, resilience, and human-centric industrial operation. Unlike existing multi-criteria decision-making approaches, the proposed framework reduces reliance on expert-based weighting, improving transparency and reproducibility. The methodology is implemented in two stages: initial KPI-based shortlisting of technologies, followed by detailed comparative performance analysis. A case study conducted in a European tire manufacturing plant compares lithium-ion batteries and flywheel energy storage systems under different peak-shaving strategies. Lithium-ion batteries demonstrated superior performance, covering approximately 80% of demand peaks compared with the 73% achieved by the flywheel system, confirming the effectiveness of the proposed methodology for practical industrial ESS selection.
Open AccessIndustrial Energy Storage System Selection: A Decision Framework and Digital Implementation Demonstrated Through a Peak-Shaving Case Study
The increasing demand for energy, rising electricity costs, and the growing need to reduce carbon emissions have driven industries toward the adoption of Renewable Energy Sources (RES) and Energy Storage Systems (ESS). However, selecting the most suitable ESS for industrial peak-shaving applications remains a complex decision involving technical, economic, and operational considerations. This paper proposes a practical and structured methodology for ESS selection that integrates conventional performance criteria with Industry 5.0 (I5.0) requirements, emphasizing sustainability, resilience, and human-centric industrial operation. Unlike existing multi-criteria decision-making approaches, the proposed framework reduces reliance on expert-based weighting, improving transparency and reproducibility. The methodology is implemented in two stages: initial KPI-based shortlisting of technologies, followed by detailed comparative performance analysis. A case study conducted in a European tire manufacturing plant compares lithium-ion batteries and flywheel energy storage systems under different peak-shaving strategies. Lithium-ion batteries demonstrated superior performance, covering approximately 80% of demand peaks compared with the 73% achieved by the flywheel system, confirming the effectiveness of the proposed methodology for practical industrial ESS selection.