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    Data-driven optimal planning for hybrid renewable energy system management in smart campus: a case study

    Ajiboye, Ayooluwa A, Popoola, Segun I, Adewuyi, Oludamilare Bode, Atayero, Aderemi A and Adebisi, Bamidele ORCID logoORCID: https://orcid.org/0000-0001-9071-9120 (2022) Data-driven optimal planning for hybrid renewable energy system management in smart campus: a case study. Sustainable Energy Technologies and Assessments, 52 (B). p. 102189. ISSN 2213-1388

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    Abstract

    Academic and research institutions need to be at the forefront of research and development efforts on sustainable energy transition towards achieving the 2030 Sustainable Development Goal 7. Thus, the most economically feasible hybrid renewable energy system (HRES) option for meeting the energy demands of Covenant University was investigated in this study. Several optimal combinations of energy resource components and storage which have significant potentials within the university campus were modeled on HOMER software in grid-connected mode. The daily energy consumption data of Covenant University were measured using EDMI Mk10E digital energy meter for a whole year. Data for analyzing renewable energy potentials for several years were sourced from the NASA database through the HOMER platform. Significantly, due to the fluctuating price of diesel fuel in Nigeria, sensitivity analysis was carried out for each combination using diesel fuel prices ranging from 0.3 $/litre to 1 $/litre. The results of each projected combination which gave 32 simulation scenarios, were analyzed comparatively using eight important system performance indices which cover economic, technical, and environmental impact assessment with and without battery energy systems. The results of the comparative analysis showed that the PV-Diesel-Grid-BESS HRES is the best configuration for meeting the Covenant university load demands in terms of credible reduction in the net present cost and cost of electricity. However, deployment of the wind energy system is economically infeasible at the study site, while the diesel generator should be strictly a backup.

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