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El. knyga: Integration of Renewable Generation and Elastic Loads into Distribution Grids

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This brief examines the challenges of integrating distributed energy resources and high-power elastic loads into low-voltage distribution grids, as well as the potential for pervasive measurement. It explores the control needed to address these challenges and achieve various system-level and user-level objectives. A mathematical framework is presented for the joint control of active end-nodes at scale, and extensive numerical simulations demonstrate that proper control of active end-nodes can significantly enhance reliable and economical operation of the power grid.

Introduction.- Related Work.- System Model.- Optimal Control of Active End-nodes.- Evaluation.- Conclusion.
1 Introduction
1(12)
1.1 Traditional Grid
1(2)
1.2 Drivers of Change
3(3)
1.2.1 Renewable Energy Systems
3(1)
1.2.2 Electric Vehicles
4(1)
1.2.3 Battery Storage Systems
5(1)
1.2.4 Emerging Challenges and Opportunities
6(1)
1.3 Enabling Technologies for the Control of Active End-Nodes
6(2)
1.3.1 Pervasive Measurement and Communication
7(1)
1.3.2 Pervasive Control
7(1)
1.4 Need for a New Approach for Control of Active End-Nodes
8(3)
1.4.1 Goals
9(1)
1.4.2 Optimal Control in Quasi Real-Time
10(1)
1.5
Chapter Summary
11(1)
References
11(2)
2 Related Work
13(16)
2.1 The Impact of Active End-Nodes on the Distribution Grid
13(3)
2.1.1 Impact of EV Adoption
14(1)
2.1.2 Impact of PV Adoption
15(1)
2.2 Control of EV Chargers
16(8)
2.2.1 Pre-Dispatch Scheduling
17(2)
2.2.2 Near Real-Time Control
19(5)
2.3 Control of Renewable Inverters
24(1)
2.4 Joint Control of Elastic Loads and Renewable Energy Systems
25(1)
2.5
Chapter Summary
25(1)
References
26(3)
3 System Model
29(12)
3.1 Power Distribution System
29(4)
3.1.1 Network Model
30(1)
3.1.2 Operating Constraints
31(2)
3.2 End-Node Models and Constraints
33(3)
3.2.1 Inelastic Loads
33(1)
3.2.2 Solar Photovoltaic Systems
33(1)
3.2.3 Battery Storage Systems
34(1)
3.2.4 Electric Vehicle Chargers
35(1)
3.2.5 Load Aggregation at Buses
36(1)
3.3 Power Flow Model
36(2)
3.4 Fairness and Resource Allocation
38(1)
3.5
Chapter Summary
38(1)
References
39(2)
4 Optimal Control of Active End-Nodes
41(14)
4.1 The Synergy Between EV Chargers and PV Inverters
41(2)
4.2 Control Objectives
43(2)
4.2.1 Objective 1---Maximizing Revenue Through Fair Power Allocation to EV Chargers
44(1)
4.2.2 Objective 2---Minimizing Solar Curtailment
44(1)
4.2.3 Objective 3---Minimizing the Use of Conventional Power
45(1)
4.3 Optimal Control
45(4)
4.3.1 Optimization Problems
45(4)
4.4 Multi-Tier Control Architecture
49(1)
4.5 Benchmarks
50(2)
4.5.1 Without Local Storage
51(1)
4.5.2 With Local Storage
52(1)
4.6
Chapter Summary
52(1)
Reference
53(2)
5 Evaluation
55(20)
5.1 Simulation Framework
55(3)
5.1.1 Architecture
56(1)
5.1.2 Interactions Between Software Components
57(1)
5.1.3 Programming Interface
57(1)
5.2 Simulation Scenarios
58(6)
5.2.1 Test Distribution System
59(1)
5.2.2 Load Profiles
60(3)
5.2.3 Solar Traces
63(1)
5.2.4 Storage
63(1)
5.2.5 EV Model
63(1)
5.3 Results
64(8)
5.3.1 The Effect of Uncontrolled EV Charging
64(3)
5.3.2 The Effect of Uncontrolled Solar Generation
67(1)
5.3.3 Evaluating the Proposed Control
67(5)
5.4
Chapter Summary
72(1)
References
73(2)
6 Conclusion
75(4)
6.1 Summary of Achieved Goals
75(1)
6.2 Limitations and Future Work
76(1)
6.2.1 TCP-Style Control for Active End-Nodes
76(1)
6.2.2 Generalizing to Unbalanced Multi-Phase Distribution Systems
77(1)
6.2.3 Optimizing Capacitor Banks and Load Tap Switching Operations
77(1)
6.3 Concluding Remarks
77(1)
References
78(1)
Index 79
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