Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models

Ayat Ali Saleh, Tomonobu Senjyu, Salem Alkhalaf, Majed A. Alotaibi and Ashraf M. Hemeida
Additional contact information
Ayat Ali Saleh: Electrical Engineering Department, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Tomonobu Senjyu: Department of Electrical and Electronics Engineering, Faculty of Engineering, University of the Ryukyus, Nakagami, Okinawa 903-0213, Japan
Salem Alkhalaf: Department of Computer, College of Science and Arts in Ar-Rass, Qassim University, Ar-Rass 51921, Saudi Arabia
Majed A. Alotaibi: Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Ashraf M. Hemeida: Electrical Engineering Department, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt

Energies, 2020, vol. 13, issue 21, 1-24

Abstract: This work introduces multi-objective water cycle algorithm (MOWCA) to find the accurate location and size of distributed energy resource (DERs) considering different load models for two seasons (winter, and summer). The impact of uncertainties produced from load and renewable energy resource (RES) such as wind turbine (WT) and photovoltaic (PV) on the performance of the radial distribution system (RDS) are covered as this is closer to the real operation condition. The point estimate method (PEM) is applied for modeling the RES uncertainties. An optimization technique is implemented to find the multi-objective optimal allocation of RESs in RDSs considering uncertainty effect. The main objectives of the work are to maximize the technical, economic and environmental benefits by minimizing different objective functions such as the dissipated power, the voltage deviation, DG cost and total emissions. The proposed multi-objective model is solved by using multi-objective water cycle algorithm (MOWCA), considering the Pareto criterion with nonlinear sorting based on fuzzy mechanism. The proposed algorithm is carried out on different IEEE power systems with various cases.

Keywords: uncertainty effect; multi-objective water cycle algorithm (MOWCA); power loss reduction; voltage deviation; cost; pollutant gas emissions; renewable energy source (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/21/5800/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/21/5800/ (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:13:y:2020:i:21:p:5800-:d:440621

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 ().