预测太阳能系统安装的成本节约

Siti Atirah Binti Razak, N. Zaini, M. Latip
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引用次数: 0

摘要

安装太阳能电池板发电的好处并没有被广泛理解。因此,本研究旨在通过分析太阳能发电并模拟基于太阳辐照度数据的潜在成本节约来提高人们的认识。通过确定特定位置的实际太阳能发电量与太阳辐照度数据之间的相关性,建立了线性回归模型。本研究采用MSE、RMSE和r平方指标来评估预测的准确性。模型的MSE和RMSE分别为5.9和2.43,r平方值为0.75,预测精度较高。该模型可以根据太阳辐照度数据预测特定地点的太阳能发电量,从而可以估计减少电费和太阳能电池板产生的最大功率所节省的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Cost Saving Through Solar System Installation
The benefits of installing solar panels for electricity generation are not widely understood. Thus, this study aims to raise awareness by analyzing solar energy generation and simulating potential cost savings based on solar irradiance data. A Linear Regression model was developed by identifying the correlation between actual solar energy generation and solar irradiance data at a specific location. The study employs MSE, RMSE, and R-squared metrics to evaluate prediction accuracy. The developed model has a low MSE and RMSE value of 5.9 and 2.43, respectively, and a high R-squared value of 0.75, indicating high prediction accuracy. This model can predict solar power generation at specific locations based on solar irradiance data, enabling the estimation of cost savings from reduced electricity bills and maximum power generated by the solar panels.
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