由於近年來的能源危機，越來越多政府及私人機關提倡應用再生能源來解決石化能源開採限制及能源議題。然而卻缺乏系統性的資料分析，並提供給使用者相關意見作為參考。推薦系統在電子商務上已行之有年，然而目前為止卻沒有將推薦系統運用於能源議題上，尤其使用者經驗的頁面設計仍然缺乏。因此，本研究提出一個以企業為導向的能源組合推薦系統，其整合電力預測、再生能源預測以及製造模式之資料模組及模型模組為基本架構。為了區分不同類型的使用者，本研究提出一分類法以一維模糊粒子群演算法搜尋求解，並以國立清華大學為企業架構基礎推薦最佳再生能源配比及未來電力需求，以評估本系統之適用性。

Owing to the over-exploitation of fossil fuels, many governments and companies have been promoting renewable energy to resolve the limitation of fossil energy and environmental issues. Nevertheless, lacks of systematic analysis to provide useful information. A Recommender System is a popular approach to promote products in Electronic Commerce. Till now there is no research developed a recommender system for environmental protection. In addition, user-friendly interface of recommender system is still lacking. Therefore, this research aims to construct an enterprise-oriented web recommender system to cope with environmental issues. In order to identify the users, the system has proposed a modules of clustering analysis called one-dimension Particle Swarm Optimization with Fuzzy C-means. The proposed web recommender system has integrated data-module and model-module for electricity, renewable energy prediction and generation. Based on the forecasted electricity consumption, a case of National Tsing Hua University is provided as an enterprise with the recommendation of the best investment of renewable energy to illustrate and validate the system.

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