巴黎協定的通過，各國紛紛針對再生能源進行投資。在此再能源轉型趨勢，究竟會產生哪些問題，頗值得我們去探討。澳洲是全世界擁有較多先進再生能源的國家，過去台灣卻對其研究較少，因此本研究針對澳洲國家電力市場(National Electricity Market, NEM)，一個橫跨五個地區的市場來進行分析，目的為探討再生能源滲透率增加對電價的影響，並探討相關影響及政策以做為台灣的借鏡。
    本研究採用澳洲能源市場調度中心(Australian Energy Market Operator, AEMO)以及澳洲政府網站所提供的資料，透過Tableau資料視覺化軟體繪製儀表板等相關圖形，以全面的分析電力交易量、天然氣價格、太陽能發電量、風能發電量、水力發電量與天氣因素對批發電價的影響，再以迴歸分析做再次的驗證。
    在儀表板分析中採用2022年10月16日至2023年10月14日的資料，可以看到再生能源滲透率增加，通常會促使電價下降，但天然氣價格會有抵銷最低成本調度原則(Merit order effect, MOE)的現象，產生再生能源滲透率增加電價卻沒有下降的情形。而迴歸分析結果，以整個NEM地區來看，除了太陽能以外，其他的變數包括風能發電量、水力發電量、電力交易量以及天然氣價格對電價皆有顯著的影響。以各地區來看，影響電價顯著的自變數不同，因為各地區主要發展的再生能源種類有差異，另外發現所有再生能源變數對電價下降皆有顯著降低效果的現象，僅出現於維多利亞(VIC)這一地區，原因為VIC地理位置位於中心，調度較方便，因此再生能源邊際成本為零的降價效果較不會因為能源調度上的花費而被抵銷。
    整體研究結果顯示，再生能源滲透率越高對電價不一定有降價的效果，其中天然氣價格扮演非常重要的角色，若天然氣價格因國際市場而大幅飆漲，則原再生能源高滲透率可降低電價的效果將被高天然氣價格所抵銷，此現象深值得我國借鏡。

    With the passage of the Paris Agreement, countries have invested in renewable energy. Exploring the potential problems arising from this renewable energy transformation trend is crucial. Australia is a country with advanced renewable energy in the world, but Taiwan has historically conducted limited research in this area. Therefore, this study analyzes the Australian National Electricity Market (NEM), a market connecting five regions. The purpose is to examine the impact of increasing renewable energy penetration on electricity prices and to explore related impacts and policies, providing insights applicable to Taiwan.
    This study utilizes data provided by the Australian Energy Market Operator (AEMO) and the Australian government website. Through Tableau data visualization software to draw dashboards and other related graphics to comprehensively analyze the impact of electricity trading volume, natural gas prices, solar power generation, wind power generation, hydropower generation and weather factors on wholesale electricity prices. This analysis is further validated through regression analysis.
    Using data from October 16, 2022 to October 14, 2023 in the dashboard analysis, illustrates that increased penetration of renewable energy typically results in lower electricity prices. However, the presence of higher natural gas prices tends to offset the Merit Order Effect (MOE), leading to scenarios where the increase in renewable energy penetration does not correspond to a decrease in electricity prices. Regression analysis results reveal that, apart from solar energy, other variables such as wind power generation, hydropower generation, power trading volume, and natural gas prices significantly impact electricity prices across the entire NEM region. Considering each region individually, the independent variables significantly affecting electricity prices differ due to the diverse primary types of developed renewable energy in each area. Notably, Victoria (VIC) is the only region to found that all renewable energy variables have a significant reducing effect on the decline of electricity prices. This phenomenon is attributed to VIC's central geographical location, enabling more convenient dispatching, thereby mitigating the potential offsetting effect of zero marginal cost in renewable energy due to dispatching expenses.
    The overall research results show that high renewable energy penetration rates do not necessarily have a price reduction effect on electricity prices. Natural gas prices play a very important role. If natural gas prices surge sharply due to the international market, the effect of reducing electricity price due to the high penetration rate of original renewable energy will be offset by the high price of natural gas. This observation serves as an essential lesson for our country to consider and learn from.

目錄
第一章	緒論	1
1.1.	研究背景	1
1.2.	研究動機與目的	5
1.3.	研究架構	5
第二章	文獻回顧	7
2.1.	再生能源對電價影響相關文獻	7
2.1.1.	太陽能與風能個別對電價影響	7
2.1.2.	再生能源整體對電價影響	10
2.2.	再生能源對電價波動相關文獻	11
2.2.1.	太陽能與風能個別對電價波動影響	12
2.2.2.	再生能源整體對電價波動影響	14
2.3.	影響電價與電價波動其他因素相關文獻	15
2.4.	再生能源相關政策	17
2.4.1.	需量反應	17
2.4.2.	儲能與能源調度	19
2.5.	視覺化分析相關文獻	21
2.6.	小結	22
第三章	研究方法	23
3.1.	視覺化分析	23
3.1.1.	軟體介面介紹	24
3.1.2.	應用方式	26
3.2.	實證分析	31
3.2.1.	實證分析研究方法	31
3.2.2.	基本模型架構	31
第四章	資料來源介紹與初步視覺化分析	32
4.1.	電價	32
4.1.1.	電價折線圖	32
4.1.1.1.	年平均電價折線圖	33
4.1.1.2.	月平均電價折線圖	34
4.1.1.3.	小時平均電價折線圖	36
4.1.2.	電價盒鬚圖	46
4.2.	發電燃料比	50
4.2.1.	發電量長條圖	50
4.2.1.1.	年平均發電量燃料比	51
4.2.1.2.	月平均發電量燃料比	52
4.2.2.	再生能源占比	53
4.3.	電力交易量	58
4.3.1.	電力交易量長條圖	58
4.3.1.1.	每月電力交易量	59
4.3.1.2.	小時平均電力交易量	60
4.3.2.	電力交易量折線圖	61
4.4.	天然氣價格	63
4.4.1.	天然氣價格折線圖	64
4.4.1.1.	年平均天然氣價格	64
4.4.1.2.	月平均天然氣價格	65
4.5.	天氣因素	66
4.5.1.	降雨量	67
4.5.2.	氣溫	68
4.6.	實證模型	69
4.6.1.	資料彙整	69
4.6.2.	實證模型建立	72
第五章	視覺化與實證分析結果	75
5.1.	視覺化分析	75
5.1.1.	各地區儀表板說明	75
5.1.2.	小結	91
5.2.	迴歸分析	91
第六章	結論與建議	94
6.1.	結論	94
6.2.	建議與後續研究	96
參考文獻	97
一、	英文文獻	97
二、	網路資料	100
 
圖目錄
圖 1.1-1全世界每年承諾投資於再生能源的金額	2
圖 1.1-2 VRE不同階段對電力系統的轉變與挑戰	2
圖 1.1-3 NEM地區示意圖	3
圖 1.1-4 2015年-2021年NEM年平均發電燃料配比	4
圖 1.1-5 2010年-2023年6月NEM年平均電價	4
圖 1.3-1研究架構圖	6
圖 3.1-1 Tableau開始頁面	24
圖 3.1-2工作頁面	25
圖 3.1-3隨時間變化舉例圖	26
圖 3.1-4關聯性舉例圖	26
圖 3.1-5量級舉例圖	27
圖 3.1-6偏差舉例圖	27
圖 3.1-7分布舉例圖	28
圖 3.1-8排名舉例圖	28
圖 3.1-9占比舉例圖	29
圖 3.1-10空間舉例圖	29
圖 3.1-11流程舉例圖	30
圖 4.1-1 NEM年平均電價折線圖	33
圖 4.1-2 NEM 2011年至2020年月平均電價折線圖	35
圖 4.1-3 NEM 2021年至2023年月平均電價折線圖	35
圖 4.1-4 NSW小時平均電價折線圖	37
圖 4.1-5 QLD小時平均電價折線圖	39
圖 4.1-6 SA小時平均電價折線圖	41
圖 4.1-7 TAS小時平均電價折線圖	43
圖 4.1-8 VIC小時平均電價折線圖	45
圖 4.1-9 NEM整體電價盒鬚圖	46
圖 4.1-10 NEM各區電價盒鬚圖1	48
圖 4.1-11 NEM各區電價盒鬚圖2	49
圖 4.2-1 2015年-2021年NEM年平均發電量燃料比	51
圖 4.2-2 近一年NEM月平均發電量燃料比	52
圖 4.2-3 NSW發電燃料百分比和再生能源滲透率	53
圖 4.2-4 QLD發電燃料百分比和再生能源滲透率	54
圖 4.2-5 SA發電燃料百分比和再生能源滲透率	55
圖 4.2-6 TAS發電燃料百分比和再生能源滲透率	56
圖 4.2-7 VIC發電燃料百分比和再生能源滲透率	57
圖 4.3-1 NEM月平均電力交易量	59
圖 4.3-2 NEM小時平均電力交易量	60
圖 4.3-3 鴨子曲線示意圖	61
圖 4.3-4 NEM小時平均電力交易量折線圖	62
圖 4.4-1 天然氣市場STTM(左)與DWGH(右)分布	63
圖 4.4-2 NEM年平均天然氣價格	64
圖 4.4-3 NEM月平均天然氣價格	65
圖 4.5-1 30年氣溫(左)與降雨量(右)年平均	66
圖 5.1-1 NSW電價綜合分析(全)	77
圖 5.1-2 NSW電價綜合分析(7月)	77
圖 5.1-3 NSW電價綜合分析(8月)	78
圖 5.1-4 NSW電價綜合分析(9月)	78
圖 5.1-5 QLD電價綜合分析(全)	80
圖 5.1-6 QLD電價綜合分析(7月)	80
圖 5.1-7 QLD電價綜合分析(8月)	81
圖 5.1-8 QLD電價綜合分析(9月)	81
圖 5.1-9 SA電價綜合分析(全)	83
圖 5.1-10 SA電價綜合分析(7月)	83
圖 5.1-11 SA電價綜合分析(8月)	84
圖 5.1-12 SA電價綜合分析(9月)	84
圖 5.1-13 TAS電價綜合分析(全)	86
圖 5.1-14 TAS電價綜合分析(7月)	86
圖 5.1-15 TAS電價綜合分析(8月)	87
圖 5.1-16 TAS電價綜合分析(9月)	87
圖 5.1-17 VIC電價綜合分析(全)	89
圖 5.1-18 VIC電價綜合分析(7月)	89
圖 5.1-19 VIC電價綜合分析(8月)	90
圖 5.1-20 VIC電價綜合分析(9月)	90

表目錄
表 4.5-1 NEM 1991年至2020年氣溫年平均	68
表 4.5-2 氣溫指標	68
表 4.5-3 NEM 1961年至1990年降雨量年平均	67
表 4.5-4 降雨量指標	67
表 4.6-1 NEM敘述統計	69
表 4.6-2 NSW敘述統計	70
表 4.6-3 QLD敘述統計	70
表 4.6-4 SA敘述統計	70
表 4.6-5 TAS敘述統計	71
表 4.6-6 VIC敘述統計	71
表 4.6-7 自變數預期影響結果	73
表 5.2-1電價與再生能源關係估計結果	92
表 5.2-2 虛擬變數結果	93

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二、	網路資料
1.	AEMO, GSH, from:
https://www.aemo.com.au/energy-systems/gas/gas-supply-hub-gsh/data-gsh/daily-gsh-reports
2.	AEMO, price and demand(電價與交易量)、fuel mix(燃料比), from:
https://www.aemo.com.au/energy-systems/electricity/national-electricity-market-nem/data-nem/data-dashboard-nem
3.	AEMO, Quarterly Energy Dynamics (QED) 2023 Q3, from: https://www.aemo.com.au/energy-systems/major-publications/quarterly-energy-dynamics-qed 
4.	AEMO, STTM, from:
https://www.aemo.com.au/energy-systems/gas/short-term-trading-market-sttm/data-sttm/daily-sttm-reports 
5.	Australian Government, Australian climate variability & change - Time series graphs, from:
Australian climate variability & change - Time series graphs (bom.gov.au)
6.	Australian Government, Australian energy update 2022 Table O Australian electricity generation, from:
https://www.energy.gov.au/publications/australian-energy-update-2022