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Optimizing PV Sources and Shunt Capacitors for Energy Efficiency Improvement in Distribution Systems Using Subtraction-Average Algorithm

Author

Listed:
  • Idris H. Smaili

    (Electrical Engineering Department, College of Engineering, Jazan University, Jazan 45142, Saudi Arabia)

  • Dhaifallah R. Almalawi

    (Department of Physics, College of Science, Taif University, Taif 21944, Saudi Arabia)

  • Abdullah M. Shaheen

    (Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt)

  • Hany S. E. Mansour

    (Electrical Engineering Department, Suez Canal University, Ismailia 41522, Egypt)

Abstract

This work presents an optimal methodology based on an augmented, improved, subtraction-average-based technique (ASABT) which is developed to minimize the energy-dissipated losses that occur during electrical power supply. It includes a way of collaborative learning that utilizes the most effective response with the goal of improving the ability to search. Two different scenarios are investigated. First, the suggested ASABT is used considering the shunt capacitors only to minimize the power losses. Second, simultaneous placement and sizing of both PV units and capacitors are handled. Applications of the suggested ASAB methodology are performed on two distribution systems. First, a practical Egyptian distribution system is considered. The results of the simulation show that the suggested ASABT has a significant 56.4% decrease in power losses over the original scenario using the capacitors only. By incorporating PV units in addition to the capacitors, the energy losses are reduced from 26,227.31 to 10,554 kW/day with a high reduction of 59.75% and 4.26% compared to the initial case and the SABT alone, respectively. Also, the emissions produced from the substation are greatly reduced from 110,823.88 kgCO 2 to 79,189 kgCO 2 , with a reduction of 28.54% compared to the initial case. Second, the standard IEEE 69-node system is added to the application. Comparable results indicate that ASABT significantly reduces power losses (5.61%) as compared to SABT and enhances the minimum voltage (2.38%) with a substantial reduction in energy losses (64.07%) compared to the initial case. For both investigated systems, the proposed ASABT outcomes are compared with the Coati optimization algorithm, the Osprey optimization algorithm (OOA), the dragonfly algorithm (DA), and SABT methods; the proposed ASABT shows superior outcomes, especially in the standard deviation of the obtained losses.

Suggested Citation

  • Idris H. Smaili & Dhaifallah R. Almalawi & Abdullah M. Shaheen & Hany S. E. Mansour, 2024. "Optimizing PV Sources and Shunt Capacitors for Energy Efficiency Improvement in Distribution Systems Using Subtraction-Average Algorithm," Mathematics, MDPI, vol. 12(5), pages 1-22, February.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:625-:d:1342352
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    References listed on IDEAS

    as
    1. Mahmoud Aref & Vladislav Oboskalov & Adel El-Shahat & Almoataz Y. Abdelaziz, 2023. "Modified Analytical Technique for Multi-Objective Optimal Placement of High-Level Renewable Energy Penetration Connected to Egyptian Power System," Mathematics, MDPI, vol. 11(4), pages 1-31, February.
    2. Ghareeb Moustafa & Ali M. El-Rifaie & Idris H. Smaili & Ahmed Ginidi & Abdullah M. Shaheen & Ahmed F. Youssef & Mohamed A. Tolba, 2023. "An Enhanced Dwarf Mongoose Optimization Algorithm for Solving Engineering Problems," Mathematics, MDPI, vol. 11(15), pages 1-26, July.
    3. Ehab S. Ali & Sahar. M. Abd Elazim & Sultan H. Hakmi & Mohamed I. Mosaad, 2023. "Optimal Allocation and Size of Renewable Energy Sources as Distributed Generations Using Shark Optimization Algorithm in Radial Distribution Systems," Energies, MDPI, vol. 16(10), pages 1-27, May.
    Full references (including those not matched with items on IDEAS)

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