Date of Award

12-2022

Document Type

Project

Degree Name

Master of Science in Information Systems and Technology

Department

Information and Decision Sciences

First Reader/Committee Chair

Dr. Conrad Shayo

Abstract

Vast renewable energy facilities rely heavily on accurate predictions of future solar power output.  This study investigated the various factors causing poor, inefficient operation of Solar Plants and different methods to identify underperforming equipment. The main questions are: Q1: How can we predict electricity generation over the next several days so that the plant can run at peak efficiency? Q2: How can we figure out the exact maintenance needs of any power plant?  Q3: How do we identify faulty equipment to improve its efficiency to improve overall performance? and Q4: What are the different factors that are causing an inefficient operation of Solar power plant? Data was gathered from Kaggle and iPUMS and then analyzed in PyCharm Community Edition 2021.2.3 to provide answers to the research project questions. Given this observation using PyCharm, important discoveries from this project were: Q1: By comparing the irradiation of both of the plants, both plants' daily irradiation doesn't show much difference surely, but we can say that Plant 1 had the most consistent irradiation throughout a month, Q2: We observed that in comparison with DC power, AC power is a lot lesser than DC power but again since it's a Solar power plant therefore most of the power generation happens during day time.Q3: Figure 4.7 indicates that the 1BY6WEcLGh8j5v7 & bvBOhCH3iADSZry inverters are deficient when compared to others; perhaps these inverters require repair or replacement. Solar power plants are susceptible to several issues that might diminish their electricity generation due to their extended lifespans. Even two similar solar power plants in different locations may have varying efficiencies. Q4: As the DC_Power /Irradiation decreases there is a significant amount of increase in the model temperature. That excessive increase in heat leads to a decrease in the efficiency of that respective equipment. When the temperature rises, an excessive number of electrons are released from the solar panel, lowering the voltage produced and the panel's overall efficiency. Areas for further study include: (a) comparing the India experience to other growing nations with similar constraints to help create a prediction model that can resist all climatic and environmental changes and (b) conduct additional research on solar power prediction enable solar power plants to function efficiently.

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