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Optimal energy management of a PV-WTG-BSS-DG microgrid system

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  • Adefarati, T.
  • Bansal, R.C.
  • Bettayeb, M.
  • Naidoo, R.

Abstract

The financial and technical advantages of renewable energy resources (RERs), coupled with their applications in the microgrid system (MGS) have considerably reduced the power demand from the utility grid. The green energy technologies (GETs) have become a potential alternative to increase energy efficiency, maximise the use of RERs and significantly reduce the operation of the diesel generator (DG). In view of this, this research work proposes an optimal power solution that comprises of the dynamic load, wind turbine generator (WTG), battery storage system (BSS), photovoltaic (PV) and DG. The energy management scheme is proposed in the study to coordinate the power sharing among the significant constituents of a MGS. The fmincon programming function is applied to explore local RERs for the benefits of customers at the demand side and to increase access to a continuous power supply. The objective of the proposed approach is to minimise the total cost (TC), minimise cost of energy (COE), maximise the benefit to cost ratio (BCR), maximise the application of RERs and minimise the operations of the DG and BSS. The variations of the power demand in spring, winter, autumn and summer are considered as the prerequisites to assess the operational efficiency of the power system. The outcomes of the research work established the fact that the proposed scheme can achieve a substantial reduction in the fuel cost (FC), maintenance cost (MC) and emission cost (EC) because the DG is only switched on when the power from RERs is not adequate to satisfy the power requirement. This indicates that the PV and WTG operate with great potentials to achieve cost savings and improve the performance of an off-grid MGS. The outcomes of this research work will provide significant information to the independent power providers (IPPs) and microgrid operators (MGOs) to make appropriate decisions while planning and designing their power systems. The results obtained from the study can be used by the government organisations as the benchmarks to improve the global power generation and reduce power crisis and subsidies on the importation of crude oil through diversification from brown energy technologies (BETs) to GETs.

Suggested Citation

  • Adefarati, T. & Bansal, R.C. & Bettayeb, M. & Naidoo, R., 2021. "Optimal energy management of a PV-WTG-BSS-DG microgrid system," Energy, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:energy:v:217:y:2021:i:c:s0360544220324658
    DOI: 10.1016/j.energy.2020.119358
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    2. Sharma, Pavitra & Dutt Mathur, Hitesh & Mishra, Puneet & Bansal, Ramesh C., 2022. "A critical and comparative review of energy management strategies for microgrids," Applied Energy, Elsevier, vol. 327(C).
    3. AlHajri, Ibrahim & Ahmadian, Ali & Alazmi, Radhi, 2023. "A comprehensive technical, economic, and environmental evaluation for optimal planning of renewable energy resources to supply water desalination units: Kuwait case study," Energy, Elsevier, vol. 275(C).
    4. Aslam Amir & Hussain Shareef & Falah Awwad, 2023. "Energy Management in a Standalone Microgrid: A Split-Horizon Dual-Stage Dispatch Strategy," Energies, MDPI, vol. 16(8), pages 1-25, April.
    5. Fathy, Ahmed, 2023. "Bald eagle search optimizer-based energy management strategy for microgrid with renewable sources and electric vehicles," Applied Energy, Elsevier, vol. 334(C).
    6. Zeljković, Čedomir & Mršić, Predrag & Erceg, Bojan & Lekić, Đorđe & Kitić, Nemanja & Matić, Petar, 2022. "Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations," Energy, Elsevier, vol. 242(C).
    7. Chen, Zhang & Yiliang, Xie & Hongxia, Zhang & Yujie, Gu & Xiongwen, Zhang, 2023. "Optimal design and performance assessment for a solar powered electricity, heating and hydrogen integrated energy system," Energy, Elsevier, vol. 262(PA).
    8. La Fata, Alice & Brignone, Massimo & Procopio, Renato & Bracco, Stefano & Delfino, Federico & Barilli, Riccardo & Ravasi, Martina & Zanellini, Fabio, 2022. "An efficient Energy Management System for long term planning and real time scheduling of flexible polygeneration systems," Renewable Energy, Elsevier, vol. 200(C), pages 1180-1201.
    9. Adefarati, T. & Bansal, R.C. & Naidoo, R. & Onaolapo, K.A. & Bettayeb, M. & Olulope, P.K. & Sobowale, A.A., 2024. "Design and techno-economic assessment of a standalone photovoltaic-diesel-battery hybrid energy system for electrification of rural areas: A step towards sustainable development," Renewable Energy, Elsevier, vol. 227(C).

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