Abstract
The use of renewable energy sources is increasing worldwide to achieve energy production sustainability. To reach this goal and mitigate against climate changes all energy resources must be optimally managed. In this paper, an innovative multi agent-based heuristic optimisation system is developed to address renewable energy systems’ challenges associated with the management of renewables including storage devices, planning of energy distribution, and consumption flexibility. A new heuristic algorithm is developed to introduce an efficient and sustainable storage strategy of surplus energy generated by different renewable resource options. This leads to archiving optimised storage levels of energy across different located storage devices in order to face risk of production shortages due to weather conditions. In order to test the behaviour of the developed system and address its benefits, a case study in the Republic of IRAQ is developed. Twelve major cities (in order of population size) distributed in 5 main regions including North, South, East, West and Middle parts of the country are selected, and hybrid renewable power generation sources such as Wind, PV-solar and Hydro are implemented based on weather changes. The results highlight the effect of high suppliers’ rate on electricity exchange and production planning from differently used renewable technologies. A sensitivity analysis is conducted to verify the behaviour of the developed model on different demand behaviour types.
Original language | English |
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Pages (from-to) | 509-520 |
Number of pages | 12 |
Journal | Renewable Energy |
Volume | 164 |
Early online date | 15 Sept 2020 |
DOIs | |
Publication status | Published - Feb 2021 |
Bibliographical note
NOTICE: this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy, 164, (2021) DOI: 10.1016/j.renene.2020.08.159© 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
- Renewable energy sources (RES)
- Energy production management
- Storage devices
- Energy distribution planning
- Agent-based modelling
- Heuristics optimisation
- Renewable energy sources
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment