Bujal, Noor Ropidah (2022) Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network. Doctoral thesis, Universiti Teknikal Malaysia Melaka.
![[img]](http://eprints.utem.edu.my/style/images/fileicons/text.png) |
Text (24 Pages)
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network.pdf - Submitted Version Download (1MB) |
|
Text (Full Text)
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network.pdf - Submitted Version Restricted to Registered users only Download (3MB) |
Abstract
The presence of DG in the electrical distribution network provides some benefits, such as power loss reduction, improvement of voltage profile and voltage stability. There is a need to achieve optimality in allocating and sizing of DG in the distribution system network. Although numerous studies have been conducted regarding this topic, recent trends indicate that further improvements can be achieved using the multi-objective meta-heuristic optimisation method. Hence, this research reviews and analyses different meta-heuristic optimisation techniques to determine an effective approach to locating and sizing the DG based on single and multi-objective functions. In addition, the voltage stability index (VSI) has been considered by researchers as one of the key parameters in analysing voltage stability in this field of study. Therefore, this research also investigates and compares the two different VSIs that are widely used to determine the most suitable VSI that gives much better optimisation results. The objective functions considered in this research are voltage deviation, power loss and voltage stability index. As for multi-objective functions associated with the optimisation problem, a weight-sum method is typically used to determine each objective function's coefficient factors (CF). However, there are no exact calculations behind the weight-sum method. On the other hand, this research proposes an Analytical Hierarchy Process (AHP) for obtaining more reliable weights (w1, w2, w3) or coefficient factors based on priority rank. The simulations of single and multi-objective function optimisations have been carried out using MATLAB for meta-heuristic techniques on the IEEE 33-bus and 69-bus radial distribution networks. The results showed that the Firefly Algorithm (FA) performs much better for the optimal allocation and sizing of DG compared to the other metaheuristic techniques, particularly based on convergence characteristics and standard deviation. Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. In the load flow analysis, the optimisation and development of FAHA was implemented on the IEEE 118-bus radial test network. The optimisation using FAHA was carried out with the regulated voltage at the DG location during the load flow. The AHP was also found to yield accurate weights of the coefficient factors for each objective function compared to the weight-sum method generally used in studies. Moreover, the empirical results obtained showed that incorporating the AHP into Firefly Algorithm improved the accuracy of weight calculations in the multi-objective formulation of the optimisation process. Practically, this FAHA has great potential applications for the optimal allocation and sizing of DG in the radial distribution network.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Distributed generation of electric power, Electrical engineering, Electric power distribution |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Library > Tesis > FKP |
| Depositing User: | F Haslinda Harun |
| Date Deposited: | 16 Oct 2023 11:07 |
| Last Modified: | 16 Oct 2023 11:07 |
| URI: | http://eprints.utem.edu.my/id/eprint/26917 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |