|
|
xiii | |
About the editors |
|
xvii | |
Preface |
|
xix | |
Acknowledgments |
|
xxi | |
Organization of this book |
|
xxiii | |
|
Part One Modeling and Control of Smart Power Distribution Network (Control Aspect) |
|
|
1 | (160) |
|
1 An overview of codes and control strategies for frequency regulation in wind power generation |
|
|
3 | (18) |
|
|
|
|
|
|
|
3 | (1) |
|
1.2 Grid codes on frequency regulation |
|
|
4 | (3) |
|
1.3 Frequency regulation framework |
|
|
7 | (1) |
|
|
8 | (1) |
|
1.5 Plant/farm-level coordinated control |
|
|
9 | (1) |
|
1.6 WTG-level control strategy |
|
|
10 | (5) |
|
|
15 | (2) |
|
|
17 | (1) |
|
|
17 | (1) |
|
|
18 | (3) |
|
2 A two-stage reserve scheduling considering wind turbine generator's de-loading control |
|
|
21 | (20) |
|
|
|
|
|
|
21 | (1) |
|
2.2 WTG-integrated dispatch mode and DFIG de-loading operation |
|
|
22 | (2) |
|
2.3 A bi-level optimization model for the two-stage reserve scheduling problem |
|
|
24 | (5) |
|
|
29 | (7) |
|
|
36 | (1) |
|
Appendix. The single-level model formulation |
|
|
36 | (3) |
|
|
39 | (1) |
|
|
39 | (2) |
|
3 Dynamic energy management and control of a grid-interactive DC microgrid system |
|
|
41 | (28) |
|
|
|
|
|
41 | (1) |
|
|
41 | (6) |
|
3.3 Dynamic energy management and control |
|
|
47 | (10) |
|
3.4 Results and discussion |
|
|
57 | (9) |
|
|
66 | (1) |
|
|
66 | (1) |
|
|
67 | (2) |
|
4 Modeling, control, and energy management for DC microgrid |
|
|
69 | (22) |
|
|
|
|
|
69 | (2) |
|
4.2 DC MG structure and modeling |
|
|
71 | (4) |
|
4.3 DC MG experimental set-up |
|
|
75 | (5) |
|
4.4 Optimal control and energy management for DC MG |
|
|
80 | (4) |
|
4.5 Results and discussions |
|
|
84 | (4) |
|
|
88 | (1) |
|
|
88 | (1) |
|
|
89 | (2) |
|
5 Hybrid AC/DC distribution network voltage control |
|
|
91 | (28) |
|
|
|
|
|
91 | (8) |
|
5.2 VSC-based hybrid AC/DC MG (lower layer) |
|
|
99 | (4) |
|
5.3 Proposed voltage control scheme (upper layer) |
|
|
103 | (4) |
|
|
107 | (10) |
|
|
117 | (1) |
|
|
117 | (1) |
|
|
117 | (2) |
|
6 Controlling the distributed energy resources under fading channel |
|
|
119 | (8) |
|
|
|
|
|
119 | (1) |
|
6.2 Microgrid state-space model |
|
|
120 | (1) |
|
6.3 LQG controller under fading channel |
|
|
120 | (1) |
|
6.4 Simulation results and discussions |
|
|
121 | (4) |
|
6.5 Conclusions and future work |
|
|
125 | (1) |
|
|
126 | (1) |
|
|
126 | (1) |
|
7 Cooperative energy dispatch for multiple autonomous microgrids with distributed renewable sources and storages |
|
|
127 | (34) |
|
|
|
|
127 | (3) |
|
7.2 Autonomous microgrid optimization model |
|
|
130 | (2) |
|
7.3 Cooperative operation control strategy (w/o storages) |
|
|
132 | (3) |
|
7.4 Numerical experiments and result |
|
|
135 | (9) |
|
|
144 | (2) |
|
7.6 Cooperative scheduling strategies (with storages) |
|
|
146 | (3) |
|
7.7 Case study with the IEEE 33-bus network scenario |
|
|
149 | (1) |
|
7.8 Simulation experiment and numerical result |
|
|
150 | (7) |
|
|
157 | (1) |
|
|
158 | (1) |
|
|
158 | (3) |
|
Part Two ICT Technologies for Smart Power Distribution Networks |
|
|
161 | (136) |
|
8 Privacy of energy consumption data of a household in a smart grid |
|
|
163 | (16) |
|
|
|
|
163 | (1) |
|
8.2 Smart grid and its many benefits |
|
|
163 | (2) |
|
8.3 Security vulnerabilities of smart grid and its impact |
|
|
165 | (2) |
|
8.4 Security objectives of smart grid |
|
|
167 | (2) |
|
8.5 Privacy preserving techniques in smart grids |
|
|
169 | (4) |
|
|
173 | (1) |
|
|
174 | (3) |
|
|
177 | (2) |
|
9 Microgrid communication system and its application in hierarchical control |
|
|
179 | (26) |
|
|
|
|
|
179 | (5) |
|
9.2 Communication construction based on hierarchical control |
|
|
184 | (4) |
|
9.3 Consensus algorithm based on microgrid communication system |
|
|
188 | (3) |
|
|
191 | (11) |
|
|
202 | (1) |
|
|
202 | (1) |
|
|
203 | (2) |
|
10 ICT technologies standards and protocols for active distribution network |
|
|
205 | (26) |
|
|
10.1 Introduction to the concept of information and communication technology (ICT) |
|
|
205 | (1) |
|
10.2 Introduction to active distribution network |
|
|
206 | (3) |
|
10.3 ICT technologies in the active distribution networks |
|
|
209 | (20) |
|
|
229 | (1) |
|
|
230 | (1) |
|
|
230 | (1) |
|
11 Virtual power plant communication system architecture |
|
|
231 | (20) |
|
|
|
|
|
231 | (2) |
|
11.2 VPPs in the smart grid concept |
|
|
233 | (3) |
|
11.3 Communication system architecture |
|
|
236 | (6) |
|
11.4 Communication protocols |
|
|
242 | (3) |
|
11.5 Communication system performance analysis |
|
|
245 | (2) |
|
|
247 | (1) |
|
|
248 | (3) |
|
12 Inertia emulation from HVDC links for LFC in the presence of smart V2G networks |
|
|
251 | (16) |
|
|
|
|
251 | (2) |
|
12.2 Inertia emulation from SPC-based HVDC systems for LFC |
|
|
253 | (3) |
|
12.3 Introduction to V2G network |
|
|
256 | (4) |
|
|
260 | (4) |
|
|
264 | (1) |
|
|
264 | (1) |
|
|
265 | (2) |
|
13 Internet of things application in smart grid: A brief overview of challenges, opportunities, and future trends |
|
|
267 | (18) |
|
|
|
267 | (1) |
|
13.2 Demand response opportunities in smart distribution systems |
|
|
268 | (4) |
|
13.3 IOT cyber physical security in smart grid |
|
|
272 | (2) |
|
13.4 Modeling and simulation challenges of IoT in smart grid |
|
|
274 | (4) |
|
|
278 | (2) |
|
|
280 | (2) |
|
|
282 | (3) |
|
14 H-infinity-based microgrid state estimations using the IoT sensors |
|
|
285 | (12) |
|
|
|
|
|
285 | (1) |
|
|
286 | (1) |
|
14.3 H-Infinity for microgrid state estimation |
|
|
287 | (1) |
|
14.4 Microgrid modeling and simulation results |
|
|
287 | (3) |
|
14.5 Conclusion and future work |
|
|
290 | (3) |
|
|
293 | (4) |
|
Part Three Optimization Models/Methods in Smart Distribution Networks (Optimization Aspects) |
|
|
297 | (290) |
|
15 Management of renewable energy source and battery bank for power losses optimization |
|
|
299 | (22) |
|
|
|
|
299 | (1) |
|
15.2 Energy management system for DC microgrid |
|
|
300 | (8) |
|
15.3 Results and discussions |
|
|
308 | (10) |
|
|
318 | (1) |
|
|
318 | (3) |
|
16 Scenario-based methods for robust electricity network planning considering uncertainties |
|
|
321 | (42) |
|
|
|
|
|
|
|
321 | (1) |
|
16.2 The mathematical model of network planning problem |
|
|
322 | (5) |
|
16.3 Scenario generation methods |
|
|
327 | (13) |
|
16.4 The solving process of the robust network planning |
|
|
340 | (1) |
|
|
341 | (6) |
|
|
347 | (1) |
|
|
347 | (12) |
|
|
359 | (4) |
|
17 Scenarios/probabilistic optimization approaches for network operation considering uncertainties |
|
|
363 | (48) |
|
|
|
|
|
17.1 Introduction scenario |
|
|
363 | (6) |
|
17.2 Basic problems of power system optimization with large-scale wind power integration |
|
|
369 | (2) |
|
17.3 Research status of power system optimization with large-scale wind power integration |
|
|
371 | (5) |
|
17.4 p-Efficient point theory |
|
|
376 | (10) |
|
17.5 Moment matching theory |
|
|
386 | (19) |
|
|
405 | (1) |
|
|
406 | (2) |
|
|
408 | (3) |
|
18 The optimal planning of wind power capacity and energy storage capacity based on the bilinear interpolation theory |
|
|
411 | (36) |
|
|
|
|
|
|
411 | (1) |
|
18.2 Research status of wind power accommodation |
|
|
412 | (10) |
|
18.3 Adequacy indices with wind power integration |
|
|
422 | (6) |
|
18.4 Estimation of wind power accommodation |
|
|
428 | (6) |
|
18.5 The optimal allocation of the wind power capacity and ESS capacity based on bilinear interpolation |
|
|
434 | (2) |
|
|
436 | (4) |
|
|
440 | (1) |
|
|
440 | (4) |
|
|
444 | (3) |
|
19 Optimal energy dispatch in residential community with renewable DGs and storage in the presence of real-time pricing |
|
|
447 | (20) |
|
|
|
|
|
|
448 | (2) |
|
19.2 System model and problem formulation |
|
|
450 | (4) |
|
19.3 Optimal energy dispatch approach |
|
|
454 | (4) |
|
19.4 Simulation experiment and numerical result |
|
|
458 | (6) |
|
19.5 Conclusions and future work |
|
|
464 | (1) |
|
|
464 | (1) |
|
|
465 | (2) |
|
20 Evaluation on the short-term power supply capacity of an active distribution system based on multiple scenarios considering uncertainties |
|
|
467 | (36) |
|
|
|
|
|
|
467 | (3) |
|
20.2 Analysis of uncertainty factors in evaluating PSC |
|
|
470 | (16) |
|
20.3 Definition of PSC evaluation index |
|
|
486 | (2) |
|
20.4 Short-term PSC evaluation algorithm based on multiscene technology |
|
|
488 | (5) |
|
|
493 | (6) |
|
|
499 | (1) |
|
|
499 | (3) |
|
|
502 | (1) |
|
21 Multi-time-scale energy management of distributed energy resources in active distribution grids |
|
|
503 | (26) |
|
|
|
|
|
|
503 | (2) |
|
|
505 | (4) |
|
21.3 Hierarchical multi-time-scale energy management system |
|
|
509 | (9) |
|
21.4 Simulation configuration and implementations |
|
|
518 | (2) |
|
21.5 Results and discussion |
|
|
520 | (6) |
|
|
526 | (1) |
|
|
526 | (2) |
|
|
528 | (1) |
|
22 Distribution network planning considering the impact of electric vehicle charging station load |
|
|
529 | (26) |
|
|
|
|
|
529 | (2) |
|
22.2 Different operating parameters of distribution network |
|
|
531 | (3) |
|
22.3 Impact of EV charging load on different operating parameters of distribution network |
|
|
534 | (6) |
|
22.4 Optimal placement of charging stations in distribution network |
|
|
540 | (2) |
|
|
542 | (9) |
|
|
551 | (1) |
|
|
551 | (4) |
|
23 Distribution systems hosting capacity assessment: Relaxation and linearization |
|
|
555 | (32) |
|
Mohammad Seydali Seyf Abad |
|
|
|
|
|
555 | (4) |
|
23.2 HC mathematical modeling |
|
|
559 | (8) |
|
|
567 | (11) |
|
|
578 | (6) |
|
|
584 | (1) |
|
|
585 | (1) |
|
|
585 | (2) |
Index |
|
587 | |