太陽光電躉購費率對減碳效益之評估研究-結合資料倉儲及系統動態學之運用

Carbon Reduction Evaluation for Solar PV Feed-in Tariff rates - A Combination of System Dynamics Approach and Data Warehouse

盧惠文(Lu, Hui Wen)

指導教授 ： 張瑞芬

國立清華大學/工學院/工業工程與工程管理學系/碩士(2015年)

摘要

由於工業與經濟的快速發展，人類對於能源的需求量逐年增加，其中化石能源的消耗量也逐年提升，然而化石能源的消耗會造成大量溫室氣體的排放並加速地球暖化現象。因此為吸引大眾或公司投資再生及永續能源，如太陽光電系統，許多國家紛紛提出綠色能源政策，例如躉購費率及資本補助等誘因來促進綠色能源發展。臺灣則於2009年提出了再生能源發展條例，該條例設置一個長期且固定的躉購費率之再生能源電能固定價格強制收購（Feed-in Tariff, FIT）制度，以提升民眾與企業設置再生能源的誘因，確保於二十年期間以一固定的費率保證收購再生能源的發電量。每年政府會依照再生能源的建置成本、年運轉維護費、年售電量等因子做躉購費率的計算，若是費率訂得太低，便無法吸引民間投資再生能源；訂得太高，則會對於政府財政造成龐大的負擔。
因此為探討目前臺灣的再生能源推廣目標，是否能使能源需求、環境問題和經濟考量（E3）這三個面向之議題達到平衡，本研究採用系統動態學（System Dynamics, SD）建構一太陽光電躉購之減碳效益評估模型，除考量躉購費率對太陽光電裝置容量、二氧化碳減排量及進口能源依存度之影響評估外，亦以進行不同躉購費率制度設計，如:階梯式、遞減式費率制度之情境模擬的減碳效益評估。由於能源歷史資料以Excel、PDF、html表格等不同的檔案形式儲存於不同的能源資訊平台，因此本研究以資訊整合的概念為出發點，建立一管理並儲存能源歷史資料的資料倉儲，且不同的決策模式需要不同的維度，因此須根據分析模式建立多維度資料方塊。本研究首先先從各個能源資訊平台蒐集研究所需數據，將數據整理並以統一的格式儲存於資料倉儲中，利用星狀架構的多維度資料方塊，提供更全面性的資訊視野。於分析前，使用者能藉由多維度的特性從不同維度來觀測能源發展趨勢，進而利用SQL語法將資料導入至本研究所建構之太陽光電躉購之減碳效益評估模型內做為模擬數值。
本研究以德國遞減式躉購費率及西班牙階梯式躉購費率作為情境模擬，模擬結果顯示使用逐年遞減式躉購費率雖然其減碳量相對而言較少，但是其能夠有效降低減碳成本，同時亦能減緩進口能源依存度，因此採用遞減式躉購費率為較佳的方案。期望藉由此模擬結果可協助政府制定躉購費率時，量化且具備時間軸之評估工具。

關鍵字

減碳效益分析 ； 太陽光電 ； 躉購費率 ； 系統動態學 ； 資料倉儲

並列摘要

Due to rapid industrial development and economic growth, the demand for energy consumption has increased gradually. Fossil fuels (coal, natural gas, and petroleum) account for 90% of non-renewable energy source. However, the combustion of fossil fuels is the major source of pollutants which will result in greenhouse gas emissions and global warming. Taiwan government has enacted the Statute for Renewable Energy Development, which guarantees that the public who own renewable electricity generation facilities, such as roof-top solar photovoltaic (PV) systems, will receive a fixed price for all of the electricity they generate for a contract term of twenty years. For government, how to set the appropriate feed-in tariff (FIT) rates is the major issue because the low FIT rates will make it unattractive to invest in renewable energy but the high FIT rate will cause government's financial burden.
Therefore, in order to investigate if the current renewable energy promotion policies in Taiwan can make energy demand, environmental concerns and economic considerations (E3) reach balance, this research adopts system dynamics (SD) approach to develop an analysis model to evaluate FIT policy. The impacts of FIT on solar PV installed capacities, carbon dioxide emissions and energy dependency on imports are all considered. There are lots of energy-related platforms providing various energy data with different storage format. Therefore, with the concept of information integration, this research establishes a data warehouse (DW) to store and manage historical energy data collected from global energy platform. However, different decision-making models require various data dimensions, so the multi-dimensional data cubes should be built according to analysis model. In this research, the DW is built based on star-type data cube design, which provides comprehensive view of information. The data can be queried and then used as input data to plot the data trend using line graphs. It is necessary to understand and compare the data from different perceptions before analysis. Then, the data can be used as the input data of SD model with SQL syntax.
The SD model simulates the scenarios of policies for promoting renewable energy which reference the FIT rate of Germany and Spain. The simulation results show that the adoption of Germany FIT policy (where FIT declines at 1% annually) will effectively reduce the cost of carbon reduction and energy dependency on imports. Therefore, a gradual decline in FIT rates would be a better choice. The SD simulation results are valuable reference for governments to adjust the appropriate FIT rates.

並列關鍵字

Carbon Reduction Benefit Analysis ； Photovoltaic ； Feed-in Tariff ； System Dynamics Approach ； Data Warehouse

參考文獻

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