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Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO

Author

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  • Ramakrishna S. S. Nuvvula

    (School of Electrical Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India)

  • Devaraj Elangovan

    (TIFAC-CORE, Vellore Institute of Technology (VIT), Vellore 632014, India)

  • Kishore Srinivasa Teegala

    (Electrical & Electronics Engineering, GMR Institute of Technology, Rajam 532127, India)

  • Rajvikram Madurai Elavarasan

    (Clean and Resilient Energy Systems (CARES) Laboratory, Texas A&M University, Galveston, TX 77553, USA)

  • Md. Rabiul Islam

    (School of Electrical, Computer, and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Ravikiran Inapakurthi

    (Electrical & Electronics Engineering, Raghu Engineering College, Dakamarri, Visakhapatnam 531162, India)

Abstract

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability.

Suggested Citation

  • Ramakrishna S. S. Nuvvula & Devaraj Elangovan & Kishore Srinivasa Teegala & Rajvikram Madurai Elavarasan & Md. Rabiul Islam & Ravikiran Inapakurthi, 2021. "Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO," Energies, MDPI, vol. 14(17), pages 1-23, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5368-:d:624243
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    References listed on IDEAS

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    1. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    2. Jacob, Ammu Susanna & Banerjee, Rangan & Ghosh, Prakash C., 2018. "Sizing of hybrid energy storage system for a PV based microgrid through design space approach," Applied Energy, Elsevier, vol. 212(C), pages 640-653.
    3. Ramli, Makbul A.M. & Bouchekara, H.R.E.H. & Alghamdi, Abdulsalam S., 2018. "Optimal sizing of PV/wind/diesel hybrid microgrid system using multi-objective self-adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 121(C), pages 400-411.
    4. Mengjun Ming & Rui Wang & Yabing Zha & Tao Zhang, 2017. "Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(5), pages 1-15, May.
    5. Fei Han & Yu-Wen-Tian Sun & Qing-Hua Ling, 2018. "An Improved Multiobjective Quantum-Behaved Particle Swarm Optimization Based on Double Search Strategy and Circular Transposon Mechanism," Complexity, Hindawi, vol. 2018, pages 1-22, November.
    6. Wang, Shuoqi & Guo, Dongxu & Han, Xuebing & Lu, Languang & Sun, Kai & Li, Weihan & Sauer, Dirk Uwe & Ouyang, Minggao, 2020. "Impact of battery degradation models on energy management of a grid-connected DC microgrid," Energy, Elsevier, vol. 207(C).
    7. Zhang, Weiping & Maleki, Akbar & Rosen, Marc A. & Liu, Jingqing, 2018. "Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage," Energy, Elsevier, vol. 163(C), pages 191-207.
    8. Qian Zhang & Jinjin Ding & Weixiang Shen & Jinhui Ma & Guoli Li, 2020. "Multiobjective Particle Swarm Optimization for Microgrids Pareto Optimization Dispatch," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-13, March.
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    1. Asmita Ajay Rathod & Balaji Subramanian, 2022. "Scrutiny of Hybrid Renewable Energy Systems for Control, Power Management, Optimization and Sizing: Challenges and Future Possibilities," Sustainability, MDPI, vol. 14(24), pages 1-35, December.

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