Use this URL to cite or link to this record in EThOS:
Title: Optimal sizing of standalone hybrid energy system using a novel multi-objective evolutionary algorithm
Author: Basarudin, Hanim
ISNI:       0000 0004 8506 6171
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2020
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Many remote areas are subjected to lack of electricity access thus affecting a nation's growth. Building standalone hybrid energy systems (HES) have been proven to be the most feasible solution. The inclusion of supercapacitor in HES aids in prolonging battery lifespan, reducing the overall system costs. To optimally size the system, genetic algorithm (GA) is initially chosen as the optimization tool with the first objective to minimize cost. Since real problems such as this often have multiple objectives that conflict one another, multi-objective evolutionary algorithm (MOEA) is preferred, which is a solver developed from GA itself. The second objective function is formulated to minimize unmet load, for which when the cost increases, the unmet load decreases, and vice versa. However, MOEA has its own conflicting goals in balancing between a trade-off's convergence and diversity. Many MOEAs are designed to overcome the issue but each has their own pros and cons. Therefore, a new MOEA approach is proposed in this research to combine the convergence and diversity evaluations into one to eliminate goal bias. The experiments in this thesis include load profile generation for HES sizing, comparison between HES with and without supercapacitor, GA's multiple runs to find minimum cost for fixed percentage of unmet load, the proposed MOEA's test for functionality and robustness, and finally the comparison between GA's and the proposed MOEA's solutions to the HES optimal sizing problem. The results prove the supercapacitor's advantage in reducing cost, the proposed MOEA's reliability, and the unmet load minimization function's practicability. This thesis concludes with summary and future work of this research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TK Electrical engineering. Electronics Nuclear engineering