Table of Contents 1
Cover
4
Preface
6
1 Introduction
1.1 Challenges of Traditional Physical and Cyber Systems
1.2 Research Trends of CPSs
1.3 Opportunities for CPS Applications
7
2 Fundamentals of CPSs
2.1 Models for Exploring CPSs
2.2 Evaluation and Verification of CPSs
2.3 CPS Performance Improvement
8
3 Stability Enhancement of CPSs
3.1 Integration of Physical and Cyber Models
3.2 Settings of Stability Analysis
3.3 HMM‐Based Stability Improvement
3.4 Stability Enhancement of Illustrative WAPS
9
4 Reliability Analysis of CPSs
4.1 Conceptual DGSs
4.2 Mathematical Model of Degraded Network
4.3 Modeling and Simulation of DGSs
4.4 Reliability Estimation Via OPF
4.5 OPF of DGSs Against Unreliable Network
10
5 Maintenance of Aging CPSs
5.1 Data‐driven Degradation Model for CPSs
5.2 Maintenance Model and Cost Model
5.3 Applications to DGSs
5.4 Applications to Gas Turbine Plant
11
6 Game Theory Based CPS Protection Plan
6.1 Vulnerability Model for CPSs
6.2 Multi‐state Attack‐Defence Game
6.3 Attack Consequence and Optimal Defence
6.4 Applications to Distributed Generation Systems (DGSs) with Uncertain Cyber‐attacks
12
7 Bayesian Based Cyberteam Deployment
7.1 Poisson Distribution based Cyber‐attacks
7.2 Cost of MNB Model
7.3 Thompson‐Hedge Algorithm
7.4 Applications to Smart Grids
7.5 Performance of Thompson‐Hedge Algorithm
13
8 Recent Advances in CPS Modeling, Stability and Reliability
8.1 Modeling Techniques for CPS Components
8.2 Theoretical Stability Analysis
8.3 Game Model for CPSs
14
References
15
Index
List of Tables 1 Chapter 2Table 2.1 Domain Requirements and Descriptions.Table 2.2 The parameters and the 95% confidence interval of the distribution ... 2 Chapter 3Table 3.1 Parameters of the single‐area WAPS with communication network.Table 3.2 Parameters of frequency response model in the Figure 3.3.Table 3.3 Parameters of communication network in Figure 3.5.Table 3.4 State of DERs under different microgrid operating conditions.Table 3.5 Statistical properties of MSE of delay predictions.Table 3.6 Statistical properties of aggregated indicator of the case 1.Table 3.7 Statistical properties of aggregated indicator of the case 2.Table 3.8 Reliability of the integrated system for different network configur...Table 3.9 Optimal PID controllers [KP, KI, KD] for different network configur... 3 Chapter 4Table 4.1 Configurations of the communication networks types.Table 4.2 Technical characteristics different feeders.Table 4.3 Technical characteristics of the different power sources.Table 4.4 Simulation results of different cases under different demand levels...Table 4.5 CG, Actual Global Cost (AGC), ENS and RP for each scenario of the p...Table 4.6 EACG, EENS and ERP for the entire duration of the database. 4 Chapter 5Table 5.1 Technical details of generation plants.Table 5.2 O&M cost and fitting model by technology.Table 5.3 The indicators |Co| of the DGS over 12 scenarios on September 6, 20...Table 5.4 The estimatedTCo and total ENS (TENS) of the DGS of 12 scenarios fr...Table 5.5 The predicted PBM features and MCRLC(M, L, TI) as a function of MPOTable 5.6 The optimal maintenance strategies [MPO, TI] for different combinat... 5 Chapter 6Table 6.1 Settings for the Contest and the PSO. 6 Chapter 7Table 7.1 Regression results.Table 7.2 ANOVA results. List of Illustrations 1 Chapter 2Figure
