Mining Optimum Models of Generating Solar Power Based on Big Data Analysis

• Main Authors: CHANG,SHUN-HAO, 章村豪
• Other Authors: Huang, Yin-Fu
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/n9fayd

碩士 === 國立雲林科技大學 === 資訊工程系 === 105 === Recently in exploiting green energy, solar power generation is a must-be trend and approach, especially for the countries with nature resource shortage. However, how to build solar power plants with the best power generation efficiency in limited spaces is always a crucial issue. In this paper, the approach of finding the optimum models of generating solar power is proposed to build solar power plants for different environments in Taiwan. First, we collect all the data from existing solar power farms, including 1) design methods of power generation, 2) actual power generation, and 3) surrounding environments. Then, after a series of preprocessing steps and system analysis on them, the optimal models of generating solar power could be mined out. Finally, in the experiments, we evaluate the system from five aspects regarding to input and output parameters. As a result, we observe that using the majority voting strategy improves the system accuracy and helps engineers build solar power plants with the maximum power generation.