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Application Assessment of Pumped Storage and Lithium-Ion Batteries on Electricity Supply Grid

Author

Listed:
  • Macdonald Nko

    (Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0183, South Africa)

  • S.P. Daniel Chowdhury

    (Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0183, South Africa)

  • Olawale Popoola

    (Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0183, South Africa)

Abstract

National electricity supply utility in South Africa (Eskom) has been facing challenges to meet load demands in the country. The lack of generation equipment maintenance, increasing load demand and lack of new generation stations has left the country with a shortage of electricity supply that leads to load shedding. As a result, alternative renewable energy is required to supplement the national grid. Photovoltaic (PV) solar generation and wind farms are leading in this regard. Sunlight fluctuates throughout the day, thereby causing irradiation which in turn causes the output of the PV plant to become unstable and unreliable. As a result, storage facilities are required to mitigate challenges that come with the integration of PV into the grid or the use of PV independently, off the grid. The same storage system can also be used to supplement the power supply at night time when there is no sunlight and/or during peak hours when the demand is high. Although storage facilities are already in existence, it is important to research their range, applications, highlight new technologies and identify the best economical solution based on present and future plans. The study investigated an improved economic and technical storage system for generation of clean energy systems using solar/PV plants as the base to supplement the grid. In addition, the research aims to provide utilities with the information required for making storage facilities available with an emphasis on capital cost, implementation, operation and maintenance costs. The study solution is expected to be economical and technically proficient in terms of PV output stabilization and provision of extra capacity during peak times. The research technology’s focus includes different storage batteries, pumped storage and other forms of storage such as supercapacitors. The analysis or simulations were carried out using current analytic methods and software, such as HOMER Pro ® . The end results provide the power utility in South Africa and abroad with options for energy storage facilities that could stabilise output demand, increase generation capacity and provide backup power. Consumers would have access to power most of the time, thereby reducing generation constraints and eventually the monthly cost of electricity due to renewable energies’ accessibility. Increased access to electricity will contribute to socio-economic development in the country. The proposed solution is environmentally friendly and would alleviate the present crisis of load shedding due to the imbalance of high demand to lower generations.

Suggested Citation

  • Macdonald Nko & S.P. Daniel Chowdhury & Olawale Popoola, 2019. "Application Assessment of Pumped Storage and Lithium-Ion Batteries on Electricity Supply Grid," Energies, MDPI, vol. 12(15), pages 1-36, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2855-:d:251378
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    References listed on IDEAS

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    1. Diouf, Boucar & Pode, Ramchandra, 2015. "Potential of lithium-ion batteries in renewable energy," Renewable Energy, Elsevier, vol. 76(C), pages 375-380.
    2. Hongwen He & Rui Xiong & Jinxin Fan, 2011. "Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach," Energies, MDPI, vol. 4(4), pages 1-17, March.
    3. Caiping Zhang & Jiuchun Jiang & Linjing Zhang & Sijia Liu & Leyi Wang & Poh Chiang Loh, 2016. "A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery," Energies, MDPI, vol. 9(11), pages 1-16, November.
    4. Hemmati, Reza & Saboori, Hedayat, 2016. "Emergence of hybrid energy storage systems in renewable energy and transport applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 11-23.
    5. Chaofeng Pan & Yanyan Liang & Long Chen & Liao Chen, 2019. "Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach," Energies, MDPI, vol. 12(4), pages 1-19, February.
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    Cited by:

    1. Lingyan Xu & Fenglian Huang & Jianguo Du & Dandan Wang, 2020. "Decisions in Power Supply Chain with Emission Reduction Effort of Coal-Fired Power Plant under the Power Market Reform," Sustainability, MDPI, vol. 12(16), pages 1-30, August.
    2. Guangyi Wu & Xiangxin Shao & Hong Jiang & Shaoxin Chen & Yibing Zhou & Hongyang Xu, 2020. "Control Strategy of the Pumped Storage Unit to Deal with the Fluctuation of Wind and Photovoltaic Power in Microgrid," Energies, MDPI, vol. 13(2), pages 1-23, January.
    3. Triantafyllia Nikolaou & George S. Stavrakakis & Konstantinos Tsamoudalis, 2020. "Modeling and Optimal Dimensioning of a Pumped Hydro Energy Storage System for the Exploitation of the Rejected Wind Energy in the Non-Interconnected Electrical Power System of the Crete Island, Greece," Energies, MDPI, vol. 13(11), pages 1-21, May.

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