A combined optimisation and decision-making approach for battery-supported HMGS. Issue 5 (3rd May 2020)

• Record Type: Journal Article
• Authors: Marcelino, Carolina; Baumann, Manuel; Carvalho, Leonel; Chibeles-Martins, Nelson; Weil, Marcel; Almeida, Paulo; Wanner, Elizabeth
• Is Part Of: Journal of the Operational Research Society. Volume 71:Issue 5(2020)
• Page Start: 762
• Page End: 774
• Publication Date: 2020-05-03
• Subjects: Smart grids -- evolutionary optimisation -- decision theory -- battery energy storage systems -- renewable energy; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2019.1582590
• Languages: English
• ISSNs: 0160-5682

Abstract

Abstract: Hybrid micro-grid systems (HMGS) are gaining increasing attention worldwide. The balance between electricity load and generation based on fluctuating renewable energy sources is a main challenge in the operation and design of HMGS. Battery energy storage systems are considered essential components for integrating high shares of renewable energy into a HMGS. Currently, there are very few studies in the field of mathematical optimisation and multi-criteria decision analysis that focus on the evaluation of different battery technologies and their impact on the HMGS design. The model proposed in this paper aims at optimising three different criteria: minimising electricity costs, reducing the loss of load probability, and maximising the use of locally available renewable energy. The model is applied in a case study in southern Germany. The optimisation is carried out using the C-DEEPSO algorithm. Its results are used as input for an AHP-TOPSIS model to identify the most suitable alternative out of five different battery technologies using expert weights. Lithium batteries are considered the best solution with regard to the given group preferences and the optimisation results.