Development of Power Models for the Integration of Multiple Renewable Energy Resources for Ajayi Crowther University’s Power System Flexibility
(1) Department of Electrical/Electronic Engineering, Ajayi Crowther University, Oyo, Nigeria
(2) Department of Electrical/Electronic Engineering, Ajayi Crowther University, Oyo, Nigeria
(3) Department of Electrical/Electronic Engineering, Ajayi Crowther University, Oyo, Nigeria
(4) Department of Mechanical Engineering, The Polytechnic, Ibadan, Nigeria
(5) Department of Laboratory Science, Ladoke Akintola University of Technology, Nigeria
(6) Department of Computer Engineering, Federal Polytechnic Offa, Nigeria
(7) LEDCO Limited, Ibadan, Nigeria
Corresponding Author
Abstract
The global energy landscape is rapidly evolving, driven by the pressing need to reduce greenhouse gas emissions and transition towards sustainable, renewable energy sources. In this context, Ajayi Crowther University (ACU), like many institutions and utilities worldwide, is faced with the challenge of integrating multiple renewable energy resources into its power system while maintaining grid reliability and flexibility. This research focuses on the development of comprehensive power models tailored to the specific needs of ACU's power system to facilitate the efficient integration of various renewable energy sources. The study begins by identifying the existing renewable energy resources available at ACU, including solar photovoltaic (PV), wind and mini-hydro systems, and potential biomass sources. Detailed data collection and monitoring are undertaken to gain insights into the intermittent nature of these resources and their respective energy generation profiles. To address the challenges associated with the intermittent nature of renewable energy sources, the proposed Renewable Energy Hybrid Distribution Generation (REHDG) modelling approach is based on a probabilistic framework, which captures the inherent uncertainty and stochastic nature of solar irradiance and temperature, wind speed, water flow, and bio-waste estimation. The power output of solar, wind, hydro, and bio-waste is treated as random variables and modelled with appropriate probability distribution functions (PDFs). These models enable the assessment of system performance allowing ACU to better anticipate energy generation fluctuations. Ultimately, this research aims to provide ACU with a tailored, data-driven approach to optimize its power system's integration of multiple renewable energy resources. The developed power models and control strategies will serve as valuable tools for achieving grid reliability, reducing greenhouse gas emissions, and enhancing sustainability in line with ACU's commitment to a greener energy future.
Keywords
Renewable Energy Sources; Grid Reliability; Power Models; Intermittent Nature; probability distribution functions (PDFs); Distributed Generations
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DOI: 10.56534/acjpas.v3i3.120
DOI (PDF): https://doi.org/10.56534/acjpas.v3i3.120.g47
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