A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources

Mohammed Hamouda Ali, Ahmed Mohammed Attiya Soliman, Mohamed Abdeen, Tarek Kandil, Almoataz Y. Abdelaziz and Adel El-Shahat ()
Additional contact information
Mohammed Hamouda Ali: Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt
Ahmed Mohammed Attiya Soliman: Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt
Mohamed Abdeen: Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt
Tarek Kandil: School of Engineering and Technology, Western Carolina University, Cullowhee, NC 28723, USA
Almoataz Y. Abdelaziz: Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt
Adel El-Shahat: Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA

Energies, 2023, vol. 16, issue 4, 1-39

Abstract: Optimal Reactive Power Dispatch (ORPD is thought of as a noncontinuous, nonlinear global optimization problem. Within the system’s constraints, the ORPD manages to accomplish the reactive power flow. Due to its more intricate linkage of variables, the reactive power issue is more challenging to resolve than the optimum power flow issue. With the existence of renewable energy resources (RERs), solving the ORPD problem to attain the most stable and secure system condition has become a more challenging task. The goal of this article is to solve the objective function of ORPD combined with RERs using a metaheuristic novel optimizer named the African Vultures Optimization Algorithm abbreviated by (AVOA), where the formulation of the ORPD issue including minimization of three single objective functions as follows, voltage deviation, system operating cost, and real power loss, is introduced and also transmission power loss minimization is embraced with the simultaneous incorporation of the optimal renewable energy resources (RERs). Where the ORPD problem complexity grows exponentially with a mixture of continuous and discrete control variables, two distinct continuous and discrete types of optimization variables are considered, and the proposed single objective functions that meet different operating constraints are then transformed into a coefficient multi-objective ORPD problem and elucidated using the weighted sum approach. To validate the suggested algorithm’s effectiveness in addressing the ORPD issue, it is evaluated on three standard IEEE networks: the IEEE-30 bus small-scale network, the IEEE-57 bus medium-scale network, and the IEEE-118 bus large-scale network using different scenarios and the outcomes are compared to these other popular optimization techniques. The findings show that the suggested AVOA algorithm provides an efficient and sturdy high-quality solution for tackling ORPD situations and vastly enhances the overall system performance of power at all scales.

Keywords: optimal reactive power dispatch (ORPD); renewable energy resources (RERs); African Vultures Optimization Algorithm (AVOA); minimizing real power loss; minimizing reactive power cost; minimizing voltage deviation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/4/1562/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/4/1562/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:4:p:1562-:d:1057699

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().