A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization. (15th March 2019)
- Record Type:
- Journal Article
- Title:
- A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization. (15th March 2019)
- Main Title:
- A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization
- Authors:
- Nguyen, Thang Trung
- Abstract:
- Abstract: The paper proposes a novel improved social spider optimization algorithm (NISSO) for solving optimal power flow (OPF) problem to independently optimize electricity generation fuel cost, power loss, polluted emission, voltage deviation and L index. The proposed NISSO method is first developed in the paper by performing three modifications with intent to improve optimal solution quality and speed up convergence of conventional social spider optimization (SSO). The first and the second modifications are to focus on new solution generation by changing the movement strategy of female spiders and male spiders while the third modification is to fix the female spider rate to an appropriate ratio. The performance of the proposed method is evaluated by testing on three IEEE systems with 30, 57 and 118 buses. As a result, the proposed method has advantages over SSO such as simpler application, fewer number of control parameters, spend less time tuning control parameter values, faster convergence to optimal solutions and more stable search ability. In addition, the proposed method's results are also compared to other existing methods and the indications are that the proposed method can find better optimal solutions, use lower number of generated solutions and faster convergence. Highlights: Novel Improved Social Spider Optimization (NISSO) is first proposed in the paper. Optimal power flow (OPF) problem is one of the most complicated problems. NISSO is executed for OPF problemAbstract: The paper proposes a novel improved social spider optimization algorithm (NISSO) for solving optimal power flow (OPF) problem to independently optimize electricity generation fuel cost, power loss, polluted emission, voltage deviation and L index. The proposed NISSO method is first developed in the paper by performing three modifications with intent to improve optimal solution quality and speed up convergence of conventional social spider optimization (SSO). The first and the second modifications are to focus on new solution generation by changing the movement strategy of female spiders and male spiders while the third modification is to fix the female spider rate to an appropriate ratio. The performance of the proposed method is evaluated by testing on three IEEE systems with 30, 57 and 118 buses. As a result, the proposed method has advantages over SSO such as simpler application, fewer number of control parameters, spend less time tuning control parameter values, faster convergence to optimal solutions and more stable search ability. In addition, the proposed method's results are also compared to other existing methods and the indications are that the proposed method can find better optimal solutions, use lower number of generated solutions and faster convergence. Highlights: Novel Improved Social Spider Optimization (NISSO) is first proposed in the paper. Optimal power flow (OPF) problem is one of the most complicated problems. NISSO is executed for OPF problem with three IEEE systems with 30, 57 and 118 buses. NISSO can find high quality solutions of OPF problem with fast search ability. NISSO is superior to approximately all compared methods for all study cases. … (more)
- Is Part Of:
- Energy. Volume 171(2019)
- Journal:
- Energy
- Issue:
- Volume 171(2019)
- Issue Display:
- Volume 171, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 171
- Issue:
- 2019
- Issue Sort Value:
- 2019-0171-2019-0000
- Page Start:
- 218
- Page End:
- 240
- Publication Date:
- 2019-03-15
- Subjects:
- Social spider optimization -- Optimal power flow -- Convergence speed -- IEEE power systems -- Fitness function -- Transmission power network
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2019.01.021 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9655.xml