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題名 光電補助擴散的模擬分析
Simulation Analysis of Solar Power Subsidy and Diffusion: FIT versus FIP
作者 洪子軒
Hung, Tzu-Hsuan
貢獻者 莊皓鈞
Chuang, Hao-Chun
洪子軒
Hung, Tzu-Hsuan
關鍵詞 光電補助
固定價格躉售
電價差額補貼
系統動力學
Solar power subsidy
Feed-In Tariff
Feed-In Premium
System Dynamics
日期 2023
上傳時間 2-Aug-2023 13:35:33 (UTC+8)
摘要 問題定義：問題近年來由於環境變遷快速，極端氣候的出現，導致ESG議題再次成為焦點，為了降低傳統發電產生大量的溫室氣體及環境破壞，因此推廣綠色能源也成為各國政府追求的目標之一，而太陽能也成為非常好的替代能源。台灣政府近年來也致力於推廣綠色屋頂政策，而本研究也將針對太陽能光學補助政策進行深入的比較探討。
學術相關性：過去也有許多透過系統動力學模擬太陽能政策的研究，而本研究不同之處在於文中將針對兩種太陽能補助政策分為固定價格躉售FIT（Feed In Tariff）以及電價差額補貼FIP（Feed In Premium）進行系統動力學模型建立及模擬分析，並站在決策者的角度分析在不同的綠能安裝環境下及不同的預算考量下的最適決策。
分析方法：本研究透過不同安裝數量的設定以模擬不同的綠能環境成熟度以及透過不同的Initial Fund來模擬不同的政府預算，並觀察重要指標Installed FIT nt與Installed FIP nt的變化，進而比較在不同情境下FIT政策及FIP政策的特性。在本研究中將使用系統動力學來模擬整體電價環境相互影響的多個因子，並深入分析兩個政策的成效狀況及交互比較。
結論：透過模擬分析，發現了在時間較短期時，FIT政策的安裝成效較FIP政策好，而在長期下，FIP政策則較穩定且激勵安裝效率較高。而從安裝意願也可以發現在前期FIT政策的安裝意願維持在高點而後快速下降，FIP政策則是隨著市場微幅震盪的狀態，相對較為穩定。
Problem Definition: In recent years, the rapid environmental changes and the occurrence of extreme weather conditions have brought ESG (Environmental, Social, and Governance) issues back into focus. To reduce the generation of greenhouse gases and environmental damage caused by traditional power generation, promoting green energy has become one of the goals pursued by governments worldwide, with solar energy being an excellent alternative. The Taiwanese government has also been dedicated to promoting green roof policies in recent years, and this study aims to conduct an in-depth comparative analysis of solar energy optical subsidy policies.

Academic Relevance: Previous studies have used system dynamics modeling to simulate solar energy policies. However, this study differs in that it establishes and simulates a system dynamics model for two types of solar energy subsidy policies: Feed-In Tariff (FIT) with a fixed price and Feed-In Premium (FIP) with a price differential subsidy. From the perspective of decision-makers, the study analyzes the optimal decisions under different green energy installation environments and budget considerations.

Analytical Method: This study simulates different green energy maturity levels by setting various installation quantities and simulates different government budgets using different initial funds. The changes in important indicators, Installed FIT nt and Installed FIP nt, are observed to compare the characteristics of FIT and FIP policies under different scenarios. System dynamics will be used in this study to simulate the interplay of multiple factors affecting the overall electricity price environment and to analyze the effectiveness and comparative performance of the two policies in depth.

Conclusion: Through simulation analysis, it was found that in the short term, FIT policy had better installation effectiveness compared to the FIP policy, while in the long term, the FIP policy was more stable and stimulated higher installation efficiency. The willingness to install also showed that the installation willingness under the FIT policy remained high in the early stages but rapidly declined afterward, while the FIP policy exhibited relative stability with minor market fluctuations.
參考文獻 Anna, H., Mario, R., Claus, H., Gustav, R., Thomas, F. & Kartarina, V. (2007). Feed-in. systems in Germany, Spain and Slovenia: a comparison. International feed-in Cooperation. URL http://www.mresearch.com/pdfs/docket/NG/doc.pdf.
Ahmad, S., Tahar, R.M., Muhammad-Sukki, F., Munir, A.B. & Rahim, R.A. (2015). Role of feed-in tariff policy in promoting solar photovoltaic investments in Malaysia: A system dynamics approach. Energy,84 , 808-815.
Babich, V., Lobel, R. & Yücel, Safak. (2020). Promoting Solar Panel Investments: Feed-in-Tariff vs. Tax-Rebate Policies. Manufacturing & Service Operations Management, 22(6), 1148-1164.
Couture, T. & Gagnon, Y. (2010). An analysis of feed-in tariff remuneration models: im- plications for renewable energy investment. Energy, 38(2), 955-965.
Dong, Z., Yu, X., Chang, C-T, Zhou, D. & Sang, X. (2022). How does feed-in tariff. and renewable portfolio standard evolve synergistically? an integrated approach of tripartite evolutionary game and system dynamics. Renew Energy, 186, 864e77.
Guo, X. & Guo, X. (2015). China`s photovoltaic power development under policy in-centives: a system dynamics analysis. Energy, 93, 589e98.
Hsu, C.W. (2012). Using a system dynamics model to assess the effects of capital subsidies and feed-in tariffs on solar PV installations. Applied Energy, 100, 205-217.
Ibanez-Lopez, A.S., Martinez-Val, J.M. & Moratilla-Soria, B.&. (2017). A dynamic simulation. model for assessing the overall impact of incentive policies on power system reliability, costs and environment. Energy ,102 ,170e88.
Kërçi, T., Tzounas, G. &Milano F. (2022). A dynamic behavioral model of the long-term. development of solar photovoltaic generation driven by feed-in tariffs. Energy, 256, 124506.
Leepa, C. & Unfried, M. (2013). Effects of a cut-off in feed-in tariffs on photovoltaic. capacity: evidence from Germany. Energy, 56, 536e42.
Lane, D. C. (2007). The power of the bond between cause and effect: Jay Wright Forrester and the field of system dynamics. System Dynamics Review , 23(2-3), 95-118.
Peter M.S. (2006). The Fifth Discipline：The Art and Practice of The Learning Organization. Paperback, Deckle Edge.
Rao, A. (2005). Experimental Investigation on Use of Recycled Aggregates in Mortar. and Concrete. Open Journal of Civil Engineering, 4 ,4
Sheldon M.R. (2007). Introduction to Probability Models, University of Southern. California Los Angeles, California.
陳仁遶 （2002）。布朗運動：從物理學到財務學。數學傳播，26:1=101卷，頁17-22。
描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
110363070
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110363070
資料類型 thesis
dc.contributor.advisor 莊皓鈞zh_TW
dc.contributor.advisor Chuang, Hao-Chunen_US
dc.contributor.author (Authors) 洪子軒zh_TW
dc.contributor.author (Authors) Hung, Tzu-Hsuanen_US
dc.creator (作者) 洪子軒zh_TW
dc.creator (作者) Hung, Tzu-Hsuanen_US
dc.date (日期) 2023en_US
dc.date.accessioned 2-Aug-2023 13:35:33 (UTC+8)-
dc.date.available 2-Aug-2023 13:35:33 (UTC+8)-
dc.date.issued (上傳時間) 2-Aug-2023 13:35:33 (UTC+8)-
dc.identifier (Other Identifiers) G0110363070en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146444-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所(MBA學位學程)zh_TW
dc.description (描述) 110363070zh_TW
dc.description.abstract (摘要) 問題定義：問題近年來由於環境變遷快速，極端氣候的出現，導致ESG議題再次成為焦點，為了降低傳統發電產生大量的溫室氣體及環境破壞，因此推廣綠色能源也成為各國政府追求的目標之一，而太陽能也成為非常好的替代能源。台灣政府近年來也致力於推廣綠色屋頂政策，而本研究也將針對太陽能光學補助政策進行深入的比較探討。
學術相關性：過去也有許多透過系統動力學模擬太陽能政策的研究，而本研究不同之處在於文中將針對兩種太陽能補助政策分為固定價格躉售FIT（Feed In Tariff）以及電價差額補貼FIP（Feed In Premium）進行系統動力學模型建立及模擬分析，並站在決策者的角度分析在不同的綠能安裝環境下及不同的預算考量下的最適決策。
分析方法：本研究透過不同安裝數量的設定以模擬不同的綠能環境成熟度以及透過不同的Initial Fund來模擬不同的政府預算，並觀察重要指標Installed FIT nt與Installed FIP nt的變化，進而比較在不同情境下FIT政策及FIP政策的特性。在本研究中將使用系統動力學來模擬整體電價環境相互影響的多個因子，並深入分析兩個政策的成效狀況及交互比較。
結論：透過模擬分析，發現了在時間較短期時，FIT政策的安裝成效較FIP政策好，而在長期下，FIP政策則較穩定且激勵安裝效率較高。而從安裝意願也可以發現在前期FIT政策的安裝意願維持在高點而後快速下降，FIP政策則是隨著市場微幅震盪的狀態，相對較為穩定。		zh_TW
dc.description.abstract (摘要) Problem Definition: In recent years, the rapid environmental changes and the occurrence of extreme weather conditions have brought ESG (Environmental, Social, and Governance) issues back into focus. To reduce the generation of greenhouse gases and environmental damage caused by traditional power generation, promoting green energy has become one of the goals pursued by governments worldwide, with solar energy being an excellent alternative. The Taiwanese government has also been dedicated to promoting green roof policies in recent years, and this study aims to conduct an in-depth comparative analysis of solar energy optical subsidy policies.

Academic Relevance: Previous studies have used system dynamics modeling to simulate solar energy policies. However, this study differs in that it establishes and simulates a system dynamics model for two types of solar energy subsidy policies: Feed-In Tariff (FIT) with a fixed price and Feed-In Premium (FIP) with a price differential subsidy. From the perspective of decision-makers, the study analyzes the optimal decisions under different green energy installation environments and budget considerations.

Analytical Method: This study simulates different green energy maturity levels by setting various installation quantities and simulates different government budgets using different initial funds. The changes in important indicators, Installed FIT nt and Installed FIP nt, are observed to compare the characteristics of FIT and FIP policies under different scenarios. System dynamics will be used in this study to simulate the interplay of multiple factors affecting the overall electricity price environment and to analyze the effectiveness and comparative performance of the two policies in depth.

Conclusion: Through simulation analysis, it was found that in the short term, FIT policy had better installation effectiveness compared to the FIP policy, while in the long term, the FIP policy was more stable and stimulated higher installation efficiency. The willingness to install also showed that the installation willingness under the FIT policy remained high in the early stages but rapidly declined afterward, while the FIP policy exhibited relative stability with minor market fluctuations.		en_US
dc.description.tableofcontents 中文摘要 i
ABSTRACT ii
Chapter 1緒論 1
1.1研究背景與動機 1
1.2 太陽能介紹 2
1.3 太陽能補助政策 2
1.3.1 固定價格躉售FIT（Feed In Tariff） 3
1.3.2 電價差額補貼FIP（Feed In Premium） 3
Chapter 2 系統動力學與太陽能補助政策 5
Chapter 3 模型建制 8
3.1 FIT（Feed In Tariff）Model 9
3.2 FIP（Feed In Premium）Model 13
Chapter 4 模型分析與結果 17
Chapter 5 結論與未來展望 24
參考文獻 25		zh_TW
dc.format.extent 1669867 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110363070en_US
dc.subject (關鍵詞) 光電補助zh_TW
dc.subject (關鍵詞) 固定價格躉售zh_TW
dc.subject (關鍵詞) 電價差額補貼zh_TW
dc.subject (關鍵詞) 系統動力學zh_TW
dc.subject (關鍵詞) Solar power subsidyen_US
dc.subject (關鍵詞) Feed-In Tariffen_US
dc.subject (關鍵詞) Feed-In Premiumen_US
dc.subject (關鍵詞) System Dynamicsen_US
dc.title (題名) 光電補助擴散的模擬分析zh_TW
dc.title (題名) Simulation Analysis of Solar Power Subsidy and Diffusion: FIT versus FIPen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Anna, H., Mario, R., Claus, H., Gustav, R., Thomas, F. & Kartarina, V. (2007). Feed-in. systems in Germany, Spain and Slovenia: a comparison. International feed-in Cooperation. URL http://www.mresearch.com/pdfs/docket/NG/doc.pdf.
Ahmad, S., Tahar, R.M., Muhammad-Sukki, F., Munir, A.B. & Rahim, R.A. (2015). Role of feed-in tariff policy in promoting solar photovoltaic investments in Malaysia: A system dynamics approach. Energy,84 , 808-815.
Babich, V., Lobel, R. & Yücel, Safak. (2020). Promoting Solar Panel Investments: Feed-in-Tariff vs. Tax-Rebate Policies. Manufacturing & Service Operations Management, 22(6), 1148-1164.
Couture, T. & Gagnon, Y. (2010). An analysis of feed-in tariff remuneration models: im- plications for renewable energy investment. Energy, 38(2), 955-965.
Dong, Z., Yu, X., Chang, C-T, Zhou, D. & Sang, X. (2022). How does feed-in tariff. and renewable portfolio standard evolve synergistically? an integrated approach of tripartite evolutionary game and system dynamics. Renew Energy, 186, 864e77.
Guo, X. & Guo, X. (2015). China`s photovoltaic power development under policy in-centives: a system dynamics analysis. Energy, 93, 589e98.
Hsu, C.W. (2012). Using a system dynamics model to assess the effects of capital subsidies and feed-in tariffs on solar PV installations. Applied Energy, 100, 205-217.
Ibanez-Lopez, A.S., Martinez-Val, J.M. & Moratilla-Soria, B.&. (2017). A dynamic simulation. model for assessing the overall impact of incentive policies on power system reliability, costs and environment. Energy ,102 ,170e88.
Kërçi, T., Tzounas, G. &Milano F. (2022). A dynamic behavioral model of the long-term. development of solar photovoltaic generation driven by feed-in tariffs. Energy, 256, 124506.
Leepa, C. & Unfried, M. (2013). Effects of a cut-off in feed-in tariffs on photovoltaic. capacity: evidence from Germany. Energy, 56, 536e42.
Lane, D. C. (2007). The power of the bond between cause and effect: Jay Wright Forrester and the field of system dynamics. System Dynamics Review , 23(2-3), 95-118.
Peter M.S. (2006). The Fifth Discipline：The Art and Practice of The Learning Organization. Paperback, Deckle Edge.
Rao, A. (2005). Experimental Investigation on Use of Recycled Aggregates in Mortar. and Concrete. Open Journal of Civil Engineering, 4 ,4
Sheldon M.R. (2007). Introduction to Probability Models, University of Southern. California Los Angeles, California.
陳仁遶 （2002）。布朗運動：從物理學到財務學。數學傳播，26:1=101卷，頁17-22。		zh_TW