Coverage optimization of UK renewable energy sources: GA based approach

Nouri, Hassan

Abstract

Worldwide demand for energy continues to grow
each year, while at the same time, concerns about climate change are leading to stricter emissions regulations. Renewable energy sources and distributed generation will play an increasing role in current and future electric power systems. In this research an attempt is made to use the Genetic Algorithm based optimization method to calculate the percentage coverage of distributed
generation farms considering a set of constraints formulated to maintain balance between cost and demand. In addition, the distances between farms and dispersed population constraints are also taken into account.

• Presentation Conference Type: Conference Paper (unpublished)
• Start Date: Aug 28, 2017
• End Date: Aug 31, 2017
• Acceptance Date: May 12, 2017
• Publication Date: Mar 17, 2017
• Deposit Date: Sep 12, 2017
• Peer Reviewed: Peer Reviewed
• Pages: 1-6
• Keywords: distributed generation, electric power systems, genetic algorithm, optimal location and size, power coverage, renewable energy
• Public URL: https://uwe-repository.worktribe.com/output/896710
• Publisher URL: http://www.UPEC2017.com
• Related Public URLs: http://people.uwe.ac.uk/Pages/person.aspx?accountname=campus%5Ch-nouri
• Additional Information: Title of Conference or Conference Proceedings : 52nd International Universities Power Engineering Conference UPEC2017
• Contract Date: Sep 14, 2017