本文整合太陽能發電系統 (Photovoltaic System, PV) 與電池儲能系統 (Battery Energy Storage System, BESS) 於微電網 (Microgrid, MG) 上的應用，將系統操作在併網模式以及孤島模式，併網模式時使用定功率控制，孤島模式時使用下垂控制，使各個子系統可以將功率平衡供應給負載，達到功率共享。下垂控制會造成系統頻率與電壓的穩態誤差，因此需要引進二次控制，使系統頻率與電壓回升到標稱值。本文使用分散式共識二次控制，透過樹莓派 (Raspberry Pi, R-Pi) 來達到各自分散式發電系統 (Distributed Generation, DG) 的資料傳輸，因此實現了虛實整合系統 (Cyber-Physical System, CPS)。物理系統由微電網電路架構與下垂控制器組成；網路系統由樹莓派組成，執行分散式二次控制。由於分散式控制需要網路溝通，所以會有網路攻擊的產生，包含錯誤資料注入攻擊 (False Data Injection, FDI)、拒絕服務攻擊 (Denial of Service, DoS) 和揭發攻擊 (Disclosure Attack) ……等等，在網路安全這部分也極為重要。本文使用了動態浮水印法進行網路攻擊的偵測，引進卡爾曼濾波器估測出系統的內部狀態，在發生攻擊時，透過檢測攻擊指標能夠即時順利檢測並且隔離遭受到攻擊的分散式發電系統之相關資料，使系統可以繼續運行。

This thesis addresses operations of a micro-grid (MG) by integrating the photovoltaic (PV) system and the battery energy storage system (BESS). The MG can be operated in both grid-connected mode and islanded mode. Usually, the constant power control is considered in grid-connected mode, and the droop control is used in islanded mode to achieve proper power sharing. The droop control will cause the steady-state error of the system frequency and voltage, so it is necessary to introduce secondary control to make the system frequency and voltage restore to the nominal value. In this thesis, the distributed secondary control is used to achieve the data transmission of the respective distributed generation (DG) through the Raspberry Pi (R-Pi), thus realizing the cyber-physical system (CPS). The physical system consists of a MG with a local droop control; the cyber system consists of a R-Pi, which performs distributed secondary control. Since the distributed control requires network communication, there will be affected by cyber attacks such as disclosure attacks, false data injection (FDI), and denial of service (DoS), how to detect cyber attacks and prevent cascaded blackouts becomes a crucial issue. This study exploits the dynamic watermarking method to detect these cyber attacks, and the Kalman Filter is introduced to estimate the internal state of the system. When an attack occurs, the indicators of the attack detection can successfully detect and isolate the relevant data of the attacked DG in a short period.

Contents
Abstract I
摘要 II
致謝 III
Contents IV
List of Figures VI
List of Tables VIII
Nomenclature IX
1 Introduction 1
1.1 Background and Motivation 1
1.2 Literature Review 1
1.3 Contributions of the Thesis 4
2 Architecture of Microgrid 5
2.1 Photovoltaic System 5
2.1.1 PV System Structure 6
2.1.2 Maximum Power Point Tracking Control 7
2.2 Battery Energy Storage System 9
2.2.1 BESS Structure 9
2.2.2 DC Converter 10
2.3 Voltage-Sourced Converter 11
2.3.1 Grid-Connected Mode 11
2.3.2 Primary Control 16
2.3.3 Distributed Secondary Control 19
2.4 Small-Signal Model of the MG 20
2.5 Chapter Conclusion 22
3 Cyber Attacks in isolated MGs 23
3.1 Cyber Attacks 23
3.1.1 Disclosure Attacks 23
3.1.2 False Data Injection (FDI) 23
3.1.3 Denial of Service (DoS) 24
3.1.4 Vulnerability Assessment 24
3.2 Attack Detection 25
3.2.1 Dynamic Watermarking Signal 26
3.2.2 Kalman Filter For Estimating States 27
3.2.3 Cyber Attack Indicators 28
3.3 Chapter Conclusion 31
4 Simulation Results 32
4.1 Introduction to OPAL-RT and Simulation Platform 32
4.2 Cyber-Physical System Implementation 35
4.3 Matlab/Simulink Simulation 36
4.4 OPAL-RT Experiment 38
4.5 Cyber-Physical System Simulation 40
4.6 Cyber Attacks 42
4.6.1 Case 1 False Data Injection 42
4.6.2 Case 2 Denial of Service 45
4.6.3 Attack Detection 47
4.7 Chapter Conclusion 47
5 Summary and Future Work 49
5.1 Summary 49
5.2 Future Work 49
REFERENCE 50

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