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系統識別號 U0026-0108201910413700
論文名稱(中文) 虛擬電廠之網路保護、最佳運轉及競價策略
論文名稱(英文) Network Protection, Optimal Operation, and Bidding Strategy of Virtual Power Plants
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 107
學期 2
出版年 108
研究生(中文) 唐文俊
研究生(英文) Wen-Jun Tang
學號 N28043016
學位類別 博士
語文別 英文
論文頁數 87頁
口試委員 口試委員-張宏展
口試委員-蔡孟伸
召集委員-林惠民
口試委員-張文恭
口試委員-鄧人豪
口試委員-吳瑞南
口試委員-張簡樂仁
口試委員-陳建富
指導教授-楊宏澤
中文關鍵字 故障電流限制器  自適應保護電驛整定  虛擬電廠  需量反應  強健最佳化  儲能電池  再生能源 
英文關鍵字 Fault Current Limiter  Adaptive Protection Strategy  Virtual Power Plant  Demand Response  Robust Optimization  Energy Storage System  Renewable Energy Source 
學科別分類
中文摘要 利用再生能源發電已被廣泛使用於電力系統,但由於其具有不確定性和不穩定性的特質,對電力系統造成相當程度的影響,系統調度策略也必然應有因應對策上的改變。未來將持續有小型,但分佈更廣泛的再生能源發電系統安裝於系統配電端。透過整合配電端再生能源發電系統、儲能系統和不同類型的彈性負載,虛擬電廠將過去單向電力潮流輸送的系統,轉變成雙向電力輸送的結構。配電端的角色也將從單純的用戶變成售電戶和用電戶的結合。虛擬電廠經由調控內部分散式電源與彈性負載,並與外部電網之電力市場進行能源、容量的買賣,以最大化其收益。
對內部分散式電源與彈性負載的調控,本研究針對下列議題加以研究,包括安裝故障電流限制器和再生能源發電系統後的配電網保護電驛自適應整定、具需量反應潛能之用戶篩選、需量反應模型建制及考慮發電與負載不確定性,與虛擬電廠對市場價格影響力的電力競價最佳化系統。為考慮不確定性因素,本研究使用強健最佳化的演算法,以涵蓋可能發生的預測誤差。為實現實際競價環境的模擬,本文並提出通過以雙層的博弈論為基礎,構建底層市場參與者的競價環境與上一層市場運營者的最佳化模擬環境。
模擬結果顯示所提出之保護電驛自適應最佳化、虛擬電廠排程管理與競價方法可有效保證區域系統穩定運轉的同時,最大化虛擬電廠參與者的利益最大化。且因考慮不確定性,可大幅減少於競價市場中產生得標但無法提供對應輔助服務遭受罰則的機率。
英文摘要 In light of the development of renewable energy and concerns over environmental protection, renewable energy resources have become a trend in distribution systems. Accordingly, the dispatch strategy of the system need to be changed. As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant plays a key role as not only a consumer but a prosumer. The structure also transform the traditional one-direction power delivery to bi-direction. The virtual power plant thus can enable itself to supply energy and ancillary services to the utility grid to maximize its profit.
To deal with the security, dispatch, operation and bidding issues faced by VPP, this dissertation proposes an overcurrent protection strategies with distributed generations and fault current limiters, the demand response potential analysis, elasticity demand response model construction, and operation and bidding strategy determination. By scheduling the energy storage systems, demand response, and renewable energy sources, virtual power plants can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, a bi-level game theory model is introduced to modify the bidding environment among market operators and all the participants.
The numerical results demonstrate the stable operation and profit maximized can be achieved through the proposed adaptive protection scheme and operation and bidding strategy optimization. By involving the uncertainty consideration and thus getting rid of penalty due to failing to provide the winning ancillary service quantity, the economic efficiency is proved to be increased.
論文目次 摘要 i
Abstract ii
致謝 iv
Table of Contents vi
List of Figures viii
List of Tables x
Acronym and Nomenclature 1
Acronym 1
Nomenclature 2
Chapter 1. INTRODUCTION 5
1.1 Backgrounds and Motivation 5
1.2 Review of Literature 7
1.3 Research Objective and Methods 10
1.4 The Overall Framework of The Proposed Method 12
Chapter 2. THE ADAPTIVE PROTECTION STRATEGIES 14
2.1 The Problem Caused by FCL Application 14
2.2 Data Collection and Preprocessing 17
2.2.1 Data Collection with Event Generation and Continuous Wavelet Transform …………………………………………………………………17
2.2.2 Sensitivity Analysis Algorithm 19
2.3 Proposed Protective Strategies 21
2.3.1 DT Relay Setting Models 21
2.3.2 Neural Network Topology-Adjusting Algorithm 24
Chapter 3. POTENTIAL DR CAPACITY ANALYSIS AND ELASTICITY DR MODEL 27
3.1 DR Program Candidate Screening Strategy 28
3.1.1 Potential Segmentation 30
3.1.2 Sensitivity Factors Selection 33
3.2 Consumption Prediction Models of Appliances 34
Chapter 4. OPTIMAL OPERATION AND BIDDING STRATEGY OF VIRTUAL POWER PLANT 37
4.1 VPP Bidding Strategy 37
4.2 Formulation with Uncertainties 45
4.3 Market Structure 48
4.4 The Two-level Game Structure and Methodology 51
Chapter 5. SIMULATION RESULTS AND DISCUSSION 55
5.1 Adaptive Protection Strategy 57
5.1.1 Modified IEEE 30-Bus Test System 57
5.1.2 Practical 83-Bus Power System in Taiwan 61
5.2 DR Program Candidate Selection 63
5.2.1 Accuracy of Prediction Model 63
5.2.2 Potencial Capacity Reuslt 65
5.3 Optimal Operation and Bidding Strategy of Virtual Power Plant 68
5.3.1 Illustrative System 68
5.3.2 Taipower System 75
Chapter 6. Conclusions and Future Prospects 79
6.1 Conclusions 79
6.2 Future Prospects 80
REFERENCES 81

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