Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO
Ramakrishna S. S. Nuvvula,
Devaraj Elangovan,
Kishore Srinivasa Teegala,
Rajvikram Madurai Elavarasan,
Md. Rabiul Islam and
Ravikiran Inapakurthi
Additional contact information
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
Energies, 2021, vol. 14, issue 17, 1-23
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.
Keywords: multi-objective ALA-QPSO; renewable energy sources; floating solar PV; bifacial solar panels; battery energy storage system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:17:p:5368-:d:624243
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