Optimal Performance of Power System Using an Optimal Power Flow Along with Optimal Inclusion of Distributed Generators Considering Voltage-Dependent Load Models
This study presents optimal power flow (OPF) techniques while optimizing the locations and sizes of distributed generators (DGs) integrated in a power system by solving a weighted-sum multi-fitness problem (MFP) involving three conflicting fitness functions: (i) active power loss reduction, (ii) voltage deviation reduction, and (iii) voltage stability improvement. The particle swarm optimizer (PSO) is applied to achieve the best fitness function along with deciding the control variables related to the conventional synchronous generators, DGs, transformers, and capacitor banks. The capability of the proposed method is tested and validated on the standard IEEE 14-bus system with consideration of different voltage-dependent load models, including constant, commercial, industrial, residential, and mixed load models. A comparison is made between the proposed method and other methods, which involves OPF only and optimal inclusion of DGs only in order to verify the capability of the proposed method in solving the optimization problem. The results imply that the suggested method based on using OPF along with optimal inclusion of DGs simultaneously can successfully decrease the active power losses, as well as improve the system's voltage profile and its stability for each load type and consequently enhance the overall system's performance.
Authors
- Sultan Sh. Alanzi (ORCID: https://orcid.org/0000-0001-6972-2763)
- Mohamed Hashem (ORCID: https://orcid.org/0000-0003-2593-3387)
- Rashad M. Kamel (ORCID: https://orcid.org/0009-0000-1332-4205)
Institutions
- Kuwait University (KW)
- Partners in Development for Research, Consulting and Training (Egypt) (EG)
Publication Details
- Published
- 2024-11-24
- DOI
- https://doi.org/10.1109/ispec59716.2024.10892481
- Citations
- 3
- Primary Topic
- Optimal Power Flow Distribution
- Type
- article
- Field-Weighted Citation Impact
- 0.63