The effect of including power converter losses when modelling energy storage systems: a UK domestic study

Panagiotou, Konstantina; Klumpner, Christian; Sumner, M.

Abstract

Energy storage systems (ESS) are seen as an increasingly important technology for managing electrical distribution systems, and there is now much research into both the underlying technologies of these systems, and their “optimum” management especially for applications within a single household. Optimum management usually depends on many factors and assumptions, for example what should be optimized (self-consumption of local renewable resources, consumer cost, peak reduction), prediction of local generation and load patterns, and the assumptions concerning the operation of the ESS itself. This paper aims to quantify one of the usual assumptions made (especially by non-electrical engineers) i.e. that the assumption that the power converter in the ESS is 100% efficient does not lead to substantial errors in the ESS performance and cost-benefit analysis. Three different ESS power converter models have been created and their behaviour as part of a house based ESS management system over a one year period has been analysed using five different control approaches, a variety of battery and solar panel sizes and employing a time of use tariff (Economy 7). By observing the ESS charging pattern through the year and monitoring of the annual electricity cost along with the system’s losses for the household, relationships between the battery and PV size, the control algorithms, the electricity cost and the system losses were created.

Citation

Panagiotou, K., Klumpner, C., & Sumner, M. The effect of including power converter losses when modelling energy storage systems: a UK domestic study. Presented at 18th European Conference on Power Electronics and Applications

• Conference Name: 18th European Conference on Power Electronics and Applications
• End Date: Sep 9, 2016
• Acceptance Date: Mar 1, 2016
• Publication Date: Sep 7, 2016
• Deposit Date: Jun 28, 2016
• Publicly Available Date: Feb 8, 2017
• Peer Reviewed: Peer Reviewed
• Keywords: Battery management systems (BMS), Energy system management, Energy storage
• Public URL: https://nottingham-repository.worktribe.com/output/818787
• Publisher URL: http://ieeexplore.ieee.org/document/7695584/
• Related Public URLs: http://www.epe2016.com/
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• Contract Date: Jun 28, 2016