Abstract
This paper proposes the artificial intelligence technique based on hybrid optimization phasor particle swarm optimization and a gravitational search algorithm, called PPSO-GSA for optimal allocation of renewable energy-based distributed generators (OA-RE-DGs), particularly wind and solar power generators, in distribution networks. The main objective is to maximize the techno-economic benefits in the distribution system by optimal allocation and integration of RE-DGs into distribution system. The proposed PPSO-GSA is implemented and validated on 94-bus practical distribution system located in Portuguese considering single and multiple scenarios of RE-DGs installation. The results reveal that optimizing the location and size of RE-DGs results in a substantial reduction in active power loss and yearly economic loss as well as improving system voltage profile and stability. Moreover, the convergence characteristics, computational efficiency and applicability of the proposed artificial intelligence technique is evaluated by comparative analysis and comparison with other optimization techniques.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Networks and Systems |
| Publisher | Springer |
| Pages | 409-422 |
| Number of pages | 14 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
Publication series
| Name | Lecture Notes in Networks and Systems |
|---|---|
| Volume | 97 |
| ISSN (Print) | 2367-3370 |
| ISSN (Electronic) | 2367-3389 |
Bibliographical note
Publisher Copyright:© Springer Nature Switzerland AG 2020.
Keywords
- Artificial intelligence technique
- Distributed generators
- Gravitational search algorithm
- Phasor particle swarm optimization
- Renewable energy
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
