Stochastic Multi-Objective Scheduling of a Hybrid System in a Distribution Network Using a Mathematical Optimization Algorithm Considering Generation and Demand Uncertainties

Ali Hadi Abdulwahid, Muna Al-Razgan, Hassan Falah Fakhruldeen, Meryelem Tania Churampi Arellano, Vedran Mrzljak (), Saber Arabi Nowdeh () and Mohammad Jafar Hadidian Moghaddam
Additional contact information
Ali Hadi Abdulwahid: Control and Automation Engineering Department, Southern Technical University, Engineering Technical College, Basra, Iraq
Muna Al-Razgan: Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11345, Saudi Arabia
Hassan Falah Fakhruldeen: Computer Techniques Engineering Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10011, Iraq
Meryelem Tania Churampi Arellano: Department of Civil Engineering, Universidad de Lima, Lima, Peru
Vedran Mrzljak: Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia
Saber Arabi Nowdeh: Institute of Research Sciences, Power and Energy Group, Johor Bahru 81310, Malaysia
Mohammad Jafar Hadidian Moghaddam: College of Engineering and Science, Victoria University, Melbourne, Australia

Mathematics, 2023, vol. 11, issue 18, 1-30

Abstract: In this paper, stochastic scheduling of a hybrid system (HS) composed of a photovoltaic (PV) array and wind turbines incorporated with a battery storage (HPV/WT/Batt) system in the distribution network was proposed to minimize energy losses, the voltage profile, and the HS cost, and to improve reliability in shape of the energy-not-supplied (ENS) index, considering energy-source generation and network demand uncertainties through the unscented transformation (UT). An improved escaping-bird search algorithm (IEBSA), based on the escape operator from the local optimal, was employed to identify the optimal location of the HS in the network in addition to the optimal quantity of PV panels, wind turbines, and batteries. The deterministic results for three configurations of HPV/WT/Batt, PV/Batt, and WT/Batt were presented, and the results indicate that the HPV/WT/Batt system is the optimal configuration with lower energy losses, voltage deviation, energy not supplied, and a lower HS energy cost than the other configurations. Deterministic scheduling according to the optimal configuration reduced energy losses, ENS, and voltage fluctuation by 33.09%, 53.56%, and 63.02%, respectively, compared to the base network. In addition, the results demonstrated that the integration of battery storage into the HPV/WT enhanced the various objectives. In addition, the superiority of IEBSA over several well-known algorithms was proved in terms of obtaining a faster convergence, better objective value, and lower HS costs. In addition, the stochastic scheduling results based on the UT revealed that the uncertainties increase the power losses, voltage deviations, ENS, and HPV/WT/Batt cost by 2.23%, 5.03%, 2.20%, and 1.91%, respectively, when compared to the deterministic scheduling.

Keywords: stochastic multi-objective scheduling; hybrid system; energy storage; reliability; unscented transformation; improved escaping-bird search algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/18/3962/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/18/3962/ (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:jmathe:v:11:y:2023:i:18:p:3962-:d:1242309

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

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