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A Joint Scheduling Strategy for Wind and Solar Photovoltaic Systems to Grasp Imbalance Cost in Competitive Market

Author

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  • Shreya Shree Das

    (Department of Electrical Engineering, Mizoram University, Aizawl 796004, India)

  • Arup Das

    (Department of Electrical Engineering, Mizoram University, Aizawl 796004, India)

  • Subhojit Dawn

    (Department of Electrical & Electronics Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada 520007, India)

  • Sadhan Gope

    (Department of Electrical Engineering, Mizoram University, Aizawl 796004, India)

  • Taha Selim Ustun

    (Fukushima Renewable Energy Institute, AIST (FREA), Koriyama 963-0298, Japan)

Abstract

The integration of renewable energy sources with active thermal power plants contributes to the green environment all over the globe. To achieve maximum reliability and sustainability of the renewable-thermal hybrid system, plentiful constraints need to be considered for minimizing the situation, which creates due to the unpredictable nature of renewable energy. In wind integrated deregulated system, wind farms need to submit the power generation scenario for future days to Independent System Operator (ISO) before the date of operation. Based on their submitted bid, ISO scheduled the power generation from different generating stations, including thermal and renewable. Due to the uncertain nature of the wind flow, there is always a chance of not fulfilling the scheduling amount of power from the wind farm. This violation in the market can impose an economic burden (i.e., imbalance cost) on the generating companies. The solar photovoltaic cell can be used to decrease the adverse economic effects of unpredicted wind saturation in the deregulated system. This paper presents consistent, competent, and effective operating schemes for the hybrid operation of solar PV and wind farms to maximize the economic profit by minimizing the imbalance cost, which occurs due to the mismatch between the actual and predicted wind speed. Modified IEEE 14-bus and modified IEEE 30-bus test systems have been used to check the usefulness of the proposed approach. Three optimization techniques (i.e., Sequential Quadratic Programming (SQP), Smart Flower Optimization Algorithm (SFOA), Honey Badger Algorithm (HBA)) have been used in this work for the comparative study. Bus Loading Factor (BLF) has been proposed here to identify the most sensitive bus in the system, used to place wind farms. The SFOA and HBA optimization technique has been used first time in this type of economic assessment problem, which is the novelty of this paper. The Bus Loading Factor (BLF) has been introduced here to identify the most sensitive bus in the system. After implementing the work, it has been seen that the operation of the solar PV system has reduced the adverse effect of imbalance cost on the renewable integrated deregulated power system.

Suggested Citation

  • Shreya Shree Das & Arup Das & Subhojit Dawn & Sadhan Gope & Taha Selim Ustun, 2022. "A Joint Scheduling Strategy for Wind and Solar Photovoltaic Systems to Grasp Imbalance Cost in Competitive Market," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5005-:d:799161
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    References listed on IDEAS

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    5. Subhojit Dawn & Gummadi Srinivasa Rao & M. L. N. Vital & K. Dhananjay Rao & Faisal Alsaif & Mohammed H. Alsharif, 2023. "Profit Extension of a Wind-Integrated Competitive Power System by Vehicle-to-Grid Integration and UPFC Placement," Energies, MDPI, vol. 16(18), pages 1-24, September.
    6. Arup Das & Subhojit Dawn & Sadhan Gope & Taha Selim Ustun, 2022. "A Strategy for System Risk Mitigation Using FACTS Devices in a Wind Incorporated Competitive Power System," Sustainability, MDPI, vol. 14(13), pages 1-21, July.
    7. Sheikh Safiullah & Asadur Rahman & Shameem Ahmad Lone & S. M. Suhail Hussain & Taha Selim Ustun, 2022. "Novel COVID-19 Based Optimization Algorithm (C-19BOA) for Performance Improvement of Power Systems," Sustainability, MDPI, vol. 14(21), pages 1-27, November.

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