Distributed linear programming models in a smart grid /

Saved in:
Bibliographic Details
Author / Creator:Ranganathan, Prakash, 1981- author.
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource (xxv, 213 pages) : illustrations
Language:English
Series:Power electronics and power systems
Power electronics and power systems (Springer)
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11273018
Hidden Bibliographic Details
Other authors / contributors:Nygard, Kendall E., author.
ISBN:9783319526171
3319526170
9783319526164
3319526162
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Summary:This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of understanding in formulating constraints for complex networks. We address this challenge by employing collection of Linear programming solvers that models the constraints of sub-systems and micro grids in a distributed fashion. The book can be treated as a useful resource to adaptively schedule resource transfers between nodes in a smart power grid. In addition, the feasibility conditions and constraints outlined in the book will enable in reaching optimal values that can help maintain the stability of both the computer network and the physical systems. It details the collection of optimization methods that are reliable for electric-utilities to use for resource scheduling, and optimizing their existing systems or sub-systems. The authors answer to key questions on ways to optimally allocate resources during outages, and contingency cases (e.g., line failures, and/or circuit breaker failures), how to design de-centralized methods for carrying out tasks using decomposition models; and how to quantify un-certainty and make decisions in the event of grid failures." The only book to focus on Linear Programming Methods for Cyber Physical Systems; " Features AMPL codes that show how to formulate IEEE test grid systems; " Includes code that can be used to tackle problems such as resource allocation, decomposition of a major grid into micro grids, and addressing uncertainty under renewable penetration scenarios.
Other form:Print version: Ranganathan, Prakash. Distributed linear programming models in a smart grid. Cham, Switzerland : Springer, 2017 3319526162 9783319526164
Standard no.:10.1007/978-3-319-52617-1
10.1007/978-3-319-52

MARC

LEADER 00000cam a2200000Ii 4500
001 11273018
005 20210625184944.6
006 m o d
007 cr cnu|||unuuu
008 170404s2017 sz a ob 001 0 eng d
019 |a 981702253  |a 981811279  |a 984848358  |a 999417137  |a 1005758448  |a 1011796831  |a 1048191168  |a 1058531270  |a 1066611313  |a 1082298119  |a 1097092929  |a 1099612730  |a 1105176110  |a 1203994919 
020 |a 9783319526171  |q (electronic bk.) 
020 |a 3319526170  |q (electronic bk.) 
020 |z 9783319526164 
020 |z 3319526162 
024 7 |a 10.1007/978-3-319-52617-1  |2 doi 
024 8 |a 10.1007/978-3-319-52 
035 |a (OCoLC)981125850  |z (OCoLC)981702253  |z (OCoLC)981811279  |z (OCoLC)984848358  |z (OCoLC)999417137  |z (OCoLC)1005758448  |z (OCoLC)1011796831  |z (OCoLC)1048191168  |z (OCoLC)1058531270  |z (OCoLC)1066611313  |z (OCoLC)1082298119  |z (OCoLC)1097092929  |z (OCoLC)1099612730  |z (OCoLC)1105176110  |z (OCoLC)1203994919 
037 |b Springer 
040 |a N$T  |b eng  |e rda  |e pn  |c N$T  |d EBLCP  |d GW5XE  |d N$T  |d YDX  |d COO  |d AZU  |d UPM  |d UAB  |d MERER  |d ESU  |d IOG  |d OCLCQ  |d JBG  |d IAD  |d ICW  |d ICN  |d VLB  |d OTZ  |d VT2  |d OCLCQ  |d OCLCA  |d U3W  |d CAUOI  |d OCLCF  |d KSU  |d EZ9  |d RRP  |d WAU  |d AU@  |d WYU  |d OCLCQ  |d UKAHL  |d LQU  |d OCLCQ  |d UND  |d OCLCO  |d DCT 
049 |a MAIN 
050 4 |a TK3105 
072 7 |a TEC  |x 007000  |2 bisacsh 
072 7 |a THX  |2 bicssc 
100 1 |a Ranganathan, Prakash,  |d 1981-  |e author.  |0 http://id.loc.gov/authorities/names/no2017096687 
245 1 0 |a Distributed linear programming models in a smart grid /  |c Prakash Ranganathan, Kendall E. Nygard. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (xxv, 213 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Power electronics and power systems 
505 0 |a Preface; Acknowledgements; Contents; List of Figures; List of Tables; List of Abbreviations; Chapter 1: Introduction; 1.1 Objectives of the Book; 1.1.1 Objective #1. Formulate a Mathematical Model for the Smart-Grid Resource-Allocation Problem; 1.1.2 Objective #2. Design, Develop, and Implement a Distributed Solution Procedure for the Mathematical Model; 1.1.3 Objective #3. Develop an Experimental Design for Testing the Procedure Referenced in Objective 2; 1.1.4 Objective #4. Conduct the Experimental Testing Referenced in Objective 3. 
505 8 |a 1.1.5 Objective # 5. Develop Decision Models Using Linear Classifier, and Placement of Synchro phasors Using LP; 1.1.6 Objective # 6. Integrating Wind Source to Smart Grid Decision Using Linear Programming, and Modeling Capacitated Resourc ... ; Chapter 2: Literature Review; 2.1 Linear Programming in Practice; 2.2 Development of a Distributed Linear-Programming Model; Chapter 3: Energy Reallocation in a Smart Grid; 3.1 Introduction; 3.2 Problem Statement; 3.3 Physical Infrastructure Issues; 3.3.1 Distributed-Device Control Functions; 3.3.2 Selective Load Control; 3.4 Micro-Grid Islanding. 
505 8 |a 3.5 Distributed Pathway Control; 3.6 Smart-Grid Modeling; 3.7 Integer Linear-Programming Models; 3.8 Notation; 3.9 Uncertainty in Resource Allocation; 3.10 Smart-Grid Simulation; 3.11 Conclusions; Chapter 4: Resource Allocation Using Branch and Bound; 4.1 Distributed Energy Resources in a Smart Grid; 4.2 Related Work; 4.3 Assigning DER to RUA Formulation; 4.4 DER Capacities; 4.5 RUA Preferences; 4.5.1 Case 1; 4.6 Constraints; 4.7 Branch-and-Bound (BB) Strategy; 4.8 Results; 4.8.1 Case 1; 4.8.2 Case 2; 4.9 Conclusions; Chapter 5: Resource Allocation Using DW Decomposition; 5.1 Why Decompose? 
505 8 |a 5.2 Objective Function and Illustration of the DW Algorithm; 5.3 LP Formulation of the IEEE 14-BUS System; 5.3.1 Region 1 Constraints; 5.3.1.1 Objective for Region 1 (ZLOSS); 5.3.1.2 Node 1; 5.3.1.3 Node 2; 5.3.1.4 Node 3; 5.3.1.5 Node 4; 5.3.1.6 Node 5; 5.3.1.7 Joint-Capacity Constraints for Region 3; 5.3.1.8 Other Constraints; 5.3.2 Region 3 Constraints (Nodes 6, 12, and 13); 5.3.2.1 Objective for Region 3 (ZLOSS); 5.3.2.2 Node 12; 5.3.2.3 Node 13; 5.3.2.4 Node 6; 5.3.2.5 Joint-Capacity Constraints for Region 3; 5.3.2.6 Other Constraints; 5.3.3 Region 2 Constraints. 
505 8 |a 5.3.3.1 Objective for Region 2 (ZLOSS); 5.3.3.2 Node 7; 5.3.3.3 Node 8; 5.3.3.4 Node 9; 5.3.3.5 Node 10; 5.3.3.6 Node 11; 5.3.3.7 Node 14; 5.3.3.8 Joint-Capacity Constraints for Region 2; 5.3.3.9 Other Constraints; 5.3.4 Master Constraints (Linking Constraints); 5.4 Decomposing the IEEE 14-Bus System into Two Regions; 5.4.1 R2 Node Constraint in Region 1; 5.4.2 R1 Node Constraint in Region 1; 5.5 Formulating the IEEE 30-Bus Systemś Constraints; 5.5.1 Nodal Constraints for Region 1; 5.5.1.1 Node 1; 5.5.1.2 Node 2; 5.5.1.3 Node 3; 5.5.1.4 Node 4; 5.5.1.5 Node 12; 5.5.1.6 Node 13; 5.5.1.7 Node 14. 
504 |a Includes bibliographical references and index. 
520 |a This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of understanding in formulating constraints for complex networks. We address this challenge by employing collection of Linear programming solvers that models the constraints of sub-systems and micro grids in a distributed fashion. The book can be treated as a useful resource to adaptively schedule resource transfers between nodes in a smart power grid. In addition, the feasibility conditions and constraints outlined in the book will enable in reaching optimal values that can help maintain the stability of both the computer network and the physical systems. It details the collection of optimization methods that are reliable for electric-utilities to use for resource scheduling, and optimizing their existing systems or sub-systems. The authors answer to key questions on ways to optimally allocate resources during outages, and contingency cases (e.g., line failures, and/or circuit breaker failures), how to design de-centralized methods for carrying out tasks using decomposition models; and how to quantify un-certainty and make decisions in the event of grid failures." The only book to focus on Linear Programming Methods for Cyber Physical Systems; " Features AMPL codes that show how to formulate IEEE test grid systems; " Includes code that can be used to tackle problems such as resource allocation, decomposition of a major grid into micro grids, and addressing uncertainty under renewable penetration scenarios. 
650 0 |a Smart power grids  |x Mathematical models. 
650 0 |a Smart power grids  |x Data processing. 
650 0 |a Linear programming. 
650 7 |a TECHNOLOGY & ENGINEERING  |x Electrical.  |2 bisacsh 
650 7 |a Smart power grids  |2 fast  |0 (OCoLC)fst01792824 
650 7 |a Linear programming.  |2 fast  |0 (OCoLC)fst00999090 
655 4 |a Electronic books. 
700 1 |a Nygard, Kendall E.,  |e author.  |0 http://id.loc.gov/authorities/names/no95018736 
773 0 |t Springer eBooks 
776 0 8 |i Print version:  |a Ranganathan, Prakash.  |t Distributed linear programming models in a smart grid.  |d Cham, Switzerland : Springer, 2017  |z 3319526162  |z 9783319526164  |w (OCoLC)966794931 
830 0 |a Power electronics and power systems (Springer)  |0 http://id.loc.gov/authorities/names/n2004017663 
903 |a HeVa 
929 |a oclccm 
999 f f |i f1517bb3-22c1-5745-9b6f-d95008a6f55e  |s 03677d83-788f-5d2a-861f-951b2692149f 
928 |t Library of Congress classification  |a TK3105  |l Online  |c UC-FullText  |u https://link.springer.com/10.1007/978-3-319-52617-1  |z Springer Nature  |g ebooks  |i 12545893