台灣太陽能補助政策情境分析

Scenario Analysis of Solar Energy Subsidy Policy in Taiwan

陳心怡(Shin-Yi Chen)

指導教授 ： 高正忠

國立交通大學/工學院/環境工程系所/碩士(2011年)

https://doi.org/10.6842/NCTU.2011.00605

摘要

為了提高綠色能源及促進永續環境，國內正積極推廣太陽光電系統，補助政策是影響太陽光電發展的重要因素，本研究因而分析不同情境下之補助金額及能源與環境效益之差異。
本研究首先整理以往初設成本補助政策下的發展，並比較國內外歷史安裝量和初設成本趨勢，然後分析國內現行電能躉購政策。之後研擬可能的政策情境，包括電價上漲(EP)、綠稅(GT)及綠稅加電價上漲等情境；且建立一套方法分析各情境，該方法主要分二部分，第一部分預測安裝量、初設成本與費率，依所建立的擴散模式與經驗曲線預測安裝量與初設成本趨勢，再據以預測電能躉購費率；第二部分評估效益，主要分為補助金額、能源及環境三部分，首先分析補助所需支出；能源效益依日射量、總發電量及分區發電能力等分析之；環境效益則主要考量溫室氣體及空氣污染物之減量效益，比較分析各情境下的補助金額及效益。亦分析個別使用者的回收期，且針對主要參數進行敏感度分析。
情境分析結果顯示EP2%以上情境比徵收綠稅所增加的安裝量更多，淨成本較高。EP3%以上及GT750&EP2%以上情境預期可達到2025年目標安裝量2000 MWp，至2025年總補助金額700億元以上。GT&EP5%等情境則預期太陽光電在2025年可達到再生能源目標(8 %)的一半。豐日照區預期其總發電能力是其他分區20倍以上，適合在該區積極推動太陽光電。各情境2025年時的eCO2減量約為268.3~6813.2千噸，約佔2008年總量的0.1~2.6 %，TSP、SOx及NOx則約減少7.9~200.4噸、108.7~2760.9噸及120.6~3061.5噸。豐日照區因發電量較大回收期可縮短至19年，但其他分區及(D)值下回收期大多超過25年，可能影響安裝意願。所建議方法及相關結果預期可輔助相關決策分析或規劃。

關鍵字

太陽光電系統 ； 補助政策評估 ； 效益評估 ； 情境分析 ； 永續環境系統分析

並列摘要

For increasing green energy and pursuing sustainable environment, the government is promoting solar PV systems. A proper subsidy policy is essential for developing PV systems. This study thus analyzes various scenarios for implementing current feed-in tariffs (FIT) subsidy policy and compares their differences based on policy cost and energy and environmental benefits.
The historical progress under the previous initial-cost subsidy policy is first evaluated. The changing trends of domestic and foreign installations and system costs are also compared. To analyze the current FIT policy, three possible scenarios and various cases under each scenario are evaluated, including electricity price (EP) rise, green tax (GT), and electricity price rise with green tax. A method with two major steps is established for analyzing these scenarios. The first step forecasts installation quantities, initial costs, and feed-in tariffs, primarily based on a diffusion model and an experience curve. The second step estimates policy cost and energy and environmental benefits of each scenario case. The energy benefit is estimated based on solar radiation, average gross electricity generation, and gross electricity generation in each region. The environmental benefit is estimated according to GHG and air pollutant emission reductions. The payback periods for individual users at different regions are also evaluated. A sensitivity analysis for major parameters is also implemented.
According to the simulated results, the installation quantities of EP2% cases are larger than those of GT cases. Cases for EP3% and GT750&EP2% can reach the goal of 2000 MWp in 2025, but the total subsidy will be more than NT$7x104 million. In 2025, GT&EP5% cases may reach 4% of the national gross electricity generations, which is half of the national target of the renewable energy. The estimated gross electricity generation at the abundant radiation region is more than twenty times than those at other regions. The eCO2 reductions in 2025 range between 268.3 and 6813.2 thousand tons, about 0.1 to 2.6% of the 2008 total national emission. And TSP, SOx, and NOx reductions are approximately 7.9-200.4, 108.7-2760.9, and 120.6-3061.5 tons, respectively. The payback period for the abundant radiation region is about 19 years, while the payback periods at other regions are mostly longer than 25 years. The proposed method and results are expected to facilitate related decision making and planning analyses.

並列關鍵字

solar photovoltaic system ； subsidy ； benefit assessment ； scenario analysis ； sustainable environmental system analysis

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