04509ntm a2200385 i 4500 0 0 lcc 0 1 REF 20000 20000 2023-05-16 0 FTKMA .A35 2022 r Thesis T000002139 2023-05-16 00:00:00 1 2023-05-16 THESIS 0 0 lcc 0 0 REF 20000 20000 2023-05-16 0 CD 13236 T000002140 2023-05-16 00:00:00 1 2023-05-16 THESIS 99512 99518 MY-KuUP 20251125110738.0 t||||fr|||| 000 0 ta 230516t20222022my a|||fr|||| 000 0 eng d THE0009623 (Local) Hardback UMP eng UMP rda FTKMA .A35 2022 r Thesis Ajith Gopi, author. Performance modelling and analysis of a utility scale solar photovoltaic power plant in a tropical region / Ajith Gopi Performance modeling and analysis of a utility scale solar photovoltaic power plant in a tropical region Kuantan, Pahang : UMP, 2022 © 2022 xv, 149 pages : illustrations (some color) ; 30 cm. + 1 CD-ROM rdacontent text rdacontent text rdamedia unmediated rdamedia computer rdacarrier volume rdacarrier computer disc rda text file PDF Faculty of Mechanical and Automotive Engineering Technology Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2022 Includes bibliographical references Solar photovoltaics has emerged as the major renewable energy technology for generating power. Tropical regions are the hotspots for utility-scale PV power plants and are highly influenced by the prevailing weather parameters like solar radiation, temperature variations, wind speed, humidity, atmospheric pressure, etc. The performance assessment of PV plants is influenced by the quality of data and the accuracy of instrumentation. The normal performance ratio (PR) metric has limitations when used for performance assessments of utility-scale PV plants. The influence of weather on the performance and the associated advanced prediction models are rarely studied in operational plants. Literature provides only limited examples of economic and environmental analysis of utility PV plants installed in tropical regions. The objective of this research includes the performance analysis of utility-scale PV power plants installed in tropical regions utilizing advanced weather station data, modeling the performance based on important weather parameters and economic & environmental assessment based on long-term measured data. The performance assessment of the solar farm is carried out based on IEC 61724 standards and on a normal performance ratio. Further, the weather corrected performance ratio is estimated by incorporating the local weather characteristics of the site. Performance modeling is accomplished using Minitab and AI tools like Response Surface methodology (RSM), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Economic and Environmental aspects are assessed utilizing the RETScreen software platform. The energy analysis of a utility scale PV power plant revealed that the southwest monsoon (SWM) season prevailing in a tropical humid region has a substantial influence on the generation pattern of the plant resulting in a 36% drop in annual energy generation. The solar PV plant’s average performance ratio (PR) is 74.45 %, with a 15.55 % capacity utilization factor (CUF) and an average daily generation of 2728.215 kWh over the study period (2017-2020). A comparative study of normal PR and weather-corrected PR revealed less variation on tropical regions for the studied plant compared to the colder regions. A unique performance model has been developed for predicting the generation for different weather seasons. Global tilted irradiation-based soar energy prediction model is also formulated with less than 4 % error. Among the AI-based models, the ANFIS model is observed to be more efficient for performance prediction. The analyzed solar farm installed in the tropical region has an annual life cycle savings of 35,312 USD/Yr. The environmental analysis revealed the capability of solar plants in mitigating 2827 tonnes of carbon per year. The outcome of this research work will contribute to the performance assessment and benchmarking of utility-scale PV power plants installed worldwide. It will also directly benefit the policymakers, consultants, utilities agencies, and developers. Faculty of Mechanical and Automotive Engineering Technology Dissertations Universities and colleges Dissertations Theses lcc THESIS