Integrating decision matrix and mind mapping for optimal residential battery storage solutions

Document Type

Conference Proceeding

Publication Title

2024 International Conference on Sustainable Technology and Engineering

Publisher

IEEE

School

School of Engineering

RAS ID

82162

Comments

Ghahramani, M., Habibi, D., Ghamari, S., & Aziz, A. (2024). Integrating decision matrix and mind mapping for optimal residential battery storage solutions. In 2024 International Conference on Sustainable Technology and Engineering (i-COSTE) (pp. 1-8). IEEE. https://doi.org/10.1109/i-COSTE63786.2024.11024695

Abstract

The rapid advancement of residential battery energy storage systems is reshaping consumer energy management and grid interaction. However, selecting an optimal battery solution remains challenging due to financial, operational, and environmental complexities. This paper introduces a comprehensive decision-making framework that integrates mathematical modeling, a decision matrix, mind mapping, and correlation analysis to aid consumers in selecting suitable battery storage options. The framework systematically evaluates critical factors such as capital expenditure (CAPEX), operational costs (OPEX), payback periods, and battery sizing, enabling consumers to assess economic and non-economic drivers. By incorporating tailored guidance for varied consumer profiles and addressing factors like government incentives, tariff structures, and battery degradation, the framework is particularly relevant for markets like Australia. Practical tools and accessible takeaways ensure this methodology is userfriendly for consumers without technical expertise, helping them make more informed decisions. Our proposed framework supports the adoption of broader battery energy storage systems, contributing to energy resilience and sustainability in an evolving energy landscape.

DOI

10.1109/i-COSTE63786.2024.11024695

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Link to publisher version (DOI)

10.1109/i-COSTE63786.2024.11024695