Abstract
Battery storage is considered as crucial for the safe operation and design of hybrid micro-grid systems (HMGS) by balancing load and generation from renewable energy sources. However, several battery technologies are available for this purpose, with different greenhouse gas emissions associated with their production. This paper applies a canonical differential evolutionary particle swarm algorithm for optimizing HMGS design and operation. Optimization goals are minimization of electricity costs and loss of power supply probability and maximization of renewable shares. The global warming potential of the obtained HMGS supported by different battery technologies is then determined via life cycle assessment. Results indicate that all the considered battery types lead to environmental benefits when compared with a HMGS without storage. Lithium iron phosphate and sodium nickel chloride batteries show favorable results whereas lead acid and lithium manganese oxide batteries are ranked last.
Original language | English |
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Title of host publication | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
Volume | 2018-January |
ISBN (Electronic) | 9781538619537 |
DOIs | |
Publication status | Published - 16 Jan 2018 |
Event | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Torino, Italy Duration: 26 Sept 2017 → 29 Sept 2017 |
Conference
Conference | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 |
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Country/Territory | Italy |
City | Torino |
Period | 26/09/17 → 29/09/17 |
Keywords
- Batteries
- Electrochemical devices
- Environmental management
- Evolutionary computation
- Global warming
- Hybrid power systems
- Micro-grids
- Particle swarm optimization
- Renewable energy sources