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Impact of Optimum Allocation of Renewable Distributed Generations on Distribution Networks Based on Different Optimization Algorithms

Author

Listed:
  • Mohamed A. Tolba

    (Nuclear Researches Center, Egyptian Atomic Energy Authority (EAEA), 11787 Cairo, Egypt
    Electrical Power Systems Department, NRU, Moscow Power Engineering Institute, 111250 Moscow, Russia)

  • Hegazy Rezk

    (College of Engineering at Wadi Aldawaser, Prince Sattam bin Abdulaziz University, 11991 Wadi Aldawaser, Saudi Arabia
    Electrical Engineering Department, Faculty of Engineering, Minia University, 61111 Minia, Egypt)

  • Vladimir Tulsky

    (Electrical Power Systems Department, NRU, Moscow Power Engineering Institute, 111250 Moscow, Russia)

  • Ahmed A. Zaki Diab

    (Electrical Power Systems Department, NRU, Moscow Power Engineering Institute, 111250 Moscow, Russia
    Electrical Engineering Department, Faculty of Engineering, Minia University, 61111 Minia, Egypt)

  • Almoataz Y. Abdelaziz

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, 11517 Cairo, Egypt)

  • Artem Vanin

    (Electrical Power Systems Department, NRU, Moscow Power Engineering Institute, 111250 Moscow, Russia)

Abstract

Integration of Renewable Distributed Generations (RDGs) such as photovoltaic (PV) systems and wind turbines (WTs) in distribution networks can be considered a brilliant and efficient solution to the growing demand for energy. This article introduces new robust and effective techniques like hybrid Particle Swarm Optimization in addition to a Gravitational Search Algorithm (PSOGSA) and Moth-Flame Optimization (MFO) that are proposed to deduce the optimum location with convenient capacity of RDGs units for minimizing system power losses and operating cost while improving voltage profile and voltage stability. This paper describes two stages. First, the Loss Sensitivity Factors (LSFs) are employed to select the most candidate buses for RDGs location. In the second stage, the PSOGSA and MFO are implemented to deduce the optimal location and capacity of RDGs from the elected buses. The proposed schemes have been applied on 33-bus and 69-bus IEEE standard radial distribution systems. To insure the suggested approaches validity, the numerical results have been compared with other techniques like Backtracking Search Optimization Algorithm (BSOA), Genetic Algorithm (GA), Particle Swarm Algorithm (PSO), Novel combined Genetic Algorithm and Particle Swarm Optimization (GA/PSO), Simulation Annealing Algorithm (SA), and Bacterial Foraging Optimization Algorithm (BFOA). The evaluated results have been confirmed the superiority with high performance of the proposed MFO technique to find the optimal solutions of RDGs units’ allocation. In this regard, the MFO is chosen to solve the problems of Egyptian Middle East distribution network as a practical case study with the optimal integration of RDGs.

Suggested Citation

  • Mohamed A. Tolba & Hegazy Rezk & Vladimir Tulsky & Ahmed A. Zaki Diab & Almoataz Y. Abdelaziz & Artem Vanin, 2018. "Impact of Optimum Allocation of Renewable Distributed Generations on Distribution Networks Based on Different Optimization Algorithms," Energies, MDPI, vol. 11(1), pages 1-33, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:245-:d:127831
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    References listed on IDEAS

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    Cited by:

    1. Mahmoud G. Hemeida & Salem Alkhalaf & Al-Attar A. Mohamed & Abdalla Ahmed Ibrahim & Tomonobu Senjyu, 2020. "Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO)," Energies, MDPI, vol. 13(15), pages 1-37, July.
    2. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Stochastic Unit Commitment Based on Multi-Scenario Tree Method Considering Uncertainty," Energies, MDPI, vol. 11(4), pages 1-17, March.
    3. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    4. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    5. Subrat Kumar Dash & Sivkumar Mishra & Almoataz Y. Abdelaziz & Mamdouh L. Alghaythi & Ahmed Allehyani, 2022. "Optimal Allocation of Distributed Generators in Active Distribution Networks Using a New Oppositional Hybrid Sine Cosine Muted Differential Evolution Algorithm," Energies, MDPI, vol. 15(6), pages 1-35, March.
    6. David Abdul Konneh & Harun Or Rashid Howlader & Ryuto Shigenobu & Tomonobu Senjyu & Shantanu Chakraborty & Narayanan Krishna, 2019. "A Multi-Criteria Decision Maker for Grid-Connected Hybrid Renewable Energy Systems Selection Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 11(4), pages 1-36, February.
    7. Anderson Passos de Aragão & Patrícia Teixeira Leite Asano & Ricardo de Andrade Lira Rabêlo, 2020. "A Reservoir Operation Policy Using Inter-Basin Water Transfer for Maximizing Hydroelectric Benefits in Brazil," Energies, MDPI, vol. 13(10), pages 1-26, May.
    8. Shazly A. Mohamed & Mohamed A. Tolba & Ayman A. Eisa & Ali M. El-Rifaie, 2021. "Comprehensive Modeling and Control of Grid-Connected Hybrid Energy Sources Using MPPT Controller," Energies, MDPI, vol. 14(16), pages 1-22, August.
    9. Chaymae Boubii & Ismail El Kafazi & Rachid Bannari & Brahim El Bhiri & Saleh Mobayen & Anton Zhilenkov & Badre Bossoufi, 2023. "Integrated Control and Optimization for Grid-Connected Photovoltaic Systems: A Model-Predictive and PSO Approach," Energies, MDPI, vol. 16(21), pages 1-22, November.
    10. Chaymae Boubii & Ismail El Kafazi & Rachid Bannari & Brahim El Bhiri & Badre Bossoufi & Hossam Kotb & Kareem M. AboRas & Ahmed Emara & Badr Nasiri, 2024. "Synergizing Wind and Solar Power: An Advanced Control System for Grid Stability," Sustainability, MDPI, vol. 16(2), pages 1-47, January.
    11. Essam A. Al-Ammar & Ghazi A. Ghazi & Wonsuk Ko, 2018. "Impact of Ambient Temperature on Shunt Capacitor Placement in a Distorted Radial Distribution System," Energies, MDPI, vol. 11(6), pages 1-17, June.
    12. Peter Makeen & Hani A. Ghali & Saim Memon & Fang Duan, 2023. "Insightful Electric Vehicle Utility Grid Aggregator Methodology Based on the G2V and V2G Technologies in Egypt," Sustainability, MDPI, vol. 15(2), pages 1-14, January.
    13. Salem Alkhalaf & Tomonobu Senjyu & Ayat Ali Saleh & Ashraf M. Hemeida & Al-Attar Ali Mohamed, 2019. "A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    14. Mohamed Tolba & Hegazy Rezk & Ahmed A. Zaki Diab & Mujahed Al-Dhaifallah, 2018. "A Novel Robust Methodology Based Salp Swarm Algorithm for Allocation and Capacity of Renewable Distributed Generators on Distribution Grids," Energies, MDPI, vol. 11(10), pages 1-34, September.
    15. Sherif M. Ismael & Shady H. E. Abdel Aleem & Almoataz Y. Abdelaziz & Ahmed F. Zobaa, 2019. "Probabilistic Hosting Capacity Enhancement in Non-Sinusoidal Power Distribution Systems Using a Hybrid PSOGSA Optimization Algorithm," Energies, MDPI, vol. 12(6), pages 1-23, March.
    16. Raavi Satish & Kanchapogu Vaisakh & Almoataz Y. Abdelaziz & Adel El-Shahat, 2021. "A Novel Three-Phase Power Flow Algorithm for the Evaluation of the Impact of Renewable Energy Sources and D-STATCOM Devices on Unbalanced Radial Distribution Networks," Energies, MDPI, vol. 14(19), pages 1-21, September.

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