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系統識別號 U0026-2407202017030400
論文名稱(中文) 考慮光伏發電不確定性之具儲能系統電動車充電站電能管理策略
論文名稱(英文) Energy Management Strategy for EV Charging Station with ESS and PV Considering PV Generation Uncertainty
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 108
學期 2
出版年 109
研究生(中文) 祖馬安
研究生(英文) Adama Zouma
電子信箱 stargue49@gmail.com
學號 N26077051
學位類別 碩士
語文別 英文
論文頁數 71頁
口試委員 指導教授-楊宏澤
口試委員-張文恭
口試委員-盧展南
口試委員-魏榮宗
口試委員-黃昭明
中文關鍵字 最佳化演算法  儲能系統  電動車充電站  再生能源  電動車雙向充放電  信賴區間  機會約束規劃  用戶群代表 
英文關鍵字 optimization  energy storage system  station  renewable energies  vehicle-to-grid/grid-to-vehicle (V2G/G2V)  confidence level  chance-constrained programming, aggregator 
學科別分類
中文摘要 因電網為早期家發展的基礎建設,且自開發以來之變更幅度有限,故未來若有大量電動車併接到配電系統,可能使配電系統的可靠度降低。本文研究了一配備儲能系統與太陽能發電系統之電動車充電站,並提出了一種經濟實用的可控分散式電力資源調度方法,以克服大量電動車併網之問題。論文中提出了充電站中太陽能發電與儲能混和運作的商業模式,其不需仰賴外界經濟性補貼,並建構相關數學模型以優化充電站的電能調度及契約容量。
本文中提出了一種基於太陽能發電不確定性的機會約束規劃方法,以決定電能最佳調度與契約容量,從而使電動汽車的充電成本最小化。在本研究中進行了模擬,以與現有方法進行比較。數值結果表明,所提出的方法不僅有利於充電站的業者,亦可提升電動汽車用戶之利益。此外,本文中亦展現了當太陽能系統發生故障時,車輛可作為支撐電網的可靠緊急備援,且同時兼顧充電成本最小化。
英文摘要 The current distribution system may be unreliable and inefficient if a large number of electric vehicles connect to it. This is because the grid technology currently in use has hardly changed since it was developed. In this thesis, an electric vehicle, photovoltaic-based charging station equipped with an energy storage system is studied and an algorithm for economic dispatch of the controllable resources in such a station to overcome the grid shortage is presented. Mathematical models for a subsidy-free integration of photovoltaic and energy storage systems in a charging station are developed along with a blueprint to optimize the contract capacity of the charging station.
A chance-constrained programming method is proposed based on photovoltaic uncertainty to determine the optimal dispatch and contracted power from the utility, such that the charging cost of the electric vehicle is minimized. Simulations are conducted in this study for a comparison with the existing method. The numerical results indicate that the proposed approach provides a range of contract capacity sizes that benefits both the aggregator of the charging station and electric vehicle users. Additionally, the thesis demonstrates how vehicles can be reliable agents in supporting the grid when photovoltaic panels fail while minimizing their charging costs.
論文目次 ACKNOWLEDGMENTS I
摘要 II
ABSTRACT III
Table of Contents IV
List of Figures VII
List of Tables IX
ABBREVIATIONS X
CHAPTER 1. INTRODUCTION 1
1. 1. Background and Motivation 1
1. 2. Literature Review 4
1. 3. Research Method and Contributions 8
1. 4. Organization of the Thesis 10
CHAPTER 2. SYSTEM ARCHITECTURE AND OPERATIONAL FLOW……… 11
2. 1. Introduction 11
2. 2. System Architecture 11
2. 3. Operational Flow 12
2. 4. Communication Procedure between EVs and CS 14
CHAPTER 3. PROPOSED EV CHARGING OPTIMIZATION APPROACH… 17
3. 1. Introduction 17
3. 2. Objective Function 18
3. 3. Constraints 20
3.3.1. SOC Constraints 20
3.3.1.1. Generic SOC Constraints 20
3.3.1.2. SOC Constraint Linearization 22
3.3.2. ESS Charging Feasibility 24
3.2.2.1. Acknowledging Contract Capacity 24
3.2.2.2. ESS Capacity Limits 25
3.3.3. Exemption of Contract Capacity Constraint 27
3.3.3.1. Charging Priority 27
3.3.3.2. Time-of-use Pattern Assignments 27
3. 4. Energy Exchange with Grid 31
3.4.1. Exchange Strategy 31
3.4.2. Profit Assessment 32
3. 5. Optimal Contract Capacity 34
3. 6. Probabilistic Model for Stochastic Variables 36
3.6.1. Probabilistic Model for Load Power Consumption 36
3.6.2. Probability Serialization Model for PV Generation 37
3.6.2.1. Probability Density Function 37
3.6.2.2. Probability Mass Function and Cumulative Distribution Function 37
CHAPTER 4. COMPUTATIONAL RESULTS 41
4. 1. Introduction 41
4. 2. Simulation Setup 41
4. 3. Comparing Different EV Charging Methods 46
4. 4. Simulation Results 48
4.4.1. EV Charging Methods Comparison 48
4.4.2. Range of Optimum Contract Capacities 50
4.4.3. Effect of PV Confidence Level and the Grid Request on Charging Station Scheduling 55
4.4.4. Economic Analysis of Grid-CS Energy Exchange 56
4.4.5. Effect of EV Penetration on Aggregator’s Profit 60
CHAPTER 5. CONCLUSION AND FUTURE PROSPECTS 63
5. 1. Conclusion 63
5. 2. Future Prospects 64
REFERENCES 66

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