| Author: | Niu, Ming |
| Title: | Advanced heuristic optimization algorithms for optimal reactive power planning and dispatch in power systems |
| Advisors: | Xu, Zhao (EE) |
| Degree: | Ph.D. |
| Year: | 2020 |
| Subject: | Electric power distribution -- Mathematical models Electric power systems -- Management Mathematical optimization Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Electrical Engineering |
| Pages: | xi, 94 pages : color illustrations |
| Language: | English |
| Abstract: | This thesis develops three advanced heuristic optimization algorithms (HOAs) for power system reactive power planning and dispatch. Firstly, a comprehensive overview of the state-of-the-art HOAs applied for reactive power planning (RPP) and optimal reactive power dispatch (ORPD) is presented. It covers a number of HOA variants in the research field of RPP and ORPD problems, including genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), and evolutionary programming (EP), etc. A modified quantum-inspired differential evolutional algorithm (MQDE) with a novel reset strategy is developed for optimal RPP. The proposed MQDE is based on quantum mechanics combining with a competitive DE mutation scheme, i.e. DE/best/1/bin. It overcomes a major difficulty of DE techniques in ensuring the search diversity of the population when the algorithm is approaching the region of local optimum in the later stages of iteration process. A novel HOAs-adaptive range composite differential evolution (ARCoDE) algorithm is developed for ORPD that is one of the critical components in optimal power flow (OPF) study. Due to the nature of power dispatch, the ORPD problems need to be solved in a timely manner. This imposes a limitation on number of function evaluations. The proposed ARCoDE algorithm utilizes the concept of compositing different types of trial vector generation strategies, which makes possible a decent balance between the exploration and exploitation capabilities in the solution. In addition, a novel control parameter range adaptation mechanism is proposed to enable a highly efficient adaptive tuning of control parameters. These novelties support ARCoDE to deliver satisfactory solutions while fulfilling the stringent time requirements. Finally, an efficiency ranking-based evolutionary algorithm (EREA) is proposed aiming at directly obtaining the most efficient DMUs. A slacks-based measure (SBM) of efficiency and its super efficiency pattern are applied to yield a full ranking of relative efficiency of DMUs in each evolving generation, based on which the most efficient DMUs can be eventually found for the multi-objective formulation of ORPD problem. |
| Rights: | All rights reserved |
| Access: | open access |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/11033