research-article

Collaborative Load Management with Safety Assurance in Smart Grids

Authors:

Hoang Hai Nguyen,

David K. Y. YauAuthors Info & Claims

ACM Transactions on Cyber-Physical Systems, Volume 1, Issue 2

Article No.: 12, Pages 1 - 27

https://doi.org/10.1145/2823351

Published: 03 February 2017 Publication History

Abstract

Load shedding can combat the overload of a power grid that may jeopardize the grid’s safety. However, disconnected customers may be excessively inconvenienced or even endangered. With the emergence of demand-response based on cyber-enabled smart meters and appliances, customers may participate in solving the overload by curtailing their demands collaboratively such that no single customers will have to bear a disproportionate burden of reduced usage. However, compliance or commitment to curtailment requests by untrusted users is uncertain, which causes an important safety concern. This article proposes a two-phase load management scheme that (i) gives customers a chance to curtail their demands and correct a grid’s overload when there are no immediate safety concerns but (ii) falls back to load shedding to ensure safety once the grid enters a vulnerable state. Extensive simulations based on a 37-bus electrical grid and traces of real electrical load demonstrate the effectiveness of this scheme. In particular, if customers are, as expected, sufficiently committed to the load curtailment, overloads can be resolved in real time by collaborative and graceful usage degradation among them, thereby avoiding unpleasant load shedding.

References

[1]

Hunt Allcott. 2008. Real Time Pricing and Electricity Markets. Retrieved January 15, 2017

[2]

Nima Amjady and Seyed Farough Majedi. 2007. Transient stability prediction by a hybrid intelligent system. IEEE Transactions on Power Systems 22, 3, 1275--1283.

[3]

ComEd. 2014. ComEd’s Hourly Pricing Program. Retrieved January 10, 2017, from https://rrtp.comed.com/.

[4]

Paolo Crucitti, Vito Latora, and Massimo Marchiori. 2004. Model for cascading failures in complex networks. Physical Review E 69, 4, 045104.

[5]

Clark W. Gellings. 2009. The Smart Grid: Enabling Energy Efficiency and Demand Response. Fairmont Press, Lilburn, GA.

[6]

Istemihan Genc, Ruisheng Diao, Vijay Vittal, Sharma Kolluri, and Sujit Mandal. 2010. Decision tree-based preventive and corrective control applications for dynamic security enhancement in power systems. IEEE Transactions on Power Systems 25, 3, 1611--1619.

[7]

Guang-Bin Huang. 2015. Extreme Learning Machines. Retrieved January 10, 2017, from http://www.ntu.edu.sg/home/egbhuang/elm_codes.html.

[8]

Robert Haber, Ruth Bars, and Ulrich Schmitz. 2012. Predictive Control in Process Engineering: From the Basics to the Applications. John Wiley 8 Sons, New York, NY.

[9]

Ellen L. Hahne. 1991. Round-robin scheduling for max-min fairness in data networks. IEEE Journal on Selected Areas in Communications 9, 7, 1024--1039.

Digital Library

[10]

Erik Hollnagel. 2009. The ETTO Principle: Efficiency-Thoroughness Trade-Off, Why Things That Go Right Sometimes Go Wrong. Ashgate Publishing, Farnham, Surrey, UK.

[11]

Guang-Bin Huang, Qin-Yu Zhu, and Chee-Kheong Siew. 2006. Extreme learning machine: Theory and applications. Neurocomputing 70, 1, 489--501.

[12]

ICSEG. 2015. WSCC 9-Bus System. Retrieved January 10, 2016, from http://publish.illinois.edu/smartergrid/wscc-9-bus-system.

[13]

E. S. Karapidakis and N. D. Hatziargyriou. 2002. Online preventive dynamic security of isolated power systems using decision trees. IEEE Transactions on Power Systems 17, 2, 297--304.

[14]

Yoshinori Kato and Shinichi Iwamoto. 2002. Transient stability preventive control for stable operating condition with desired CCT. IEEE Transactions on Power Systems 17, 4, 1154--1161.

[15]

Prabha Kundur. 1994. Power System Stability and Control. McGraw-Hill, New York, NY.

[16]

Hoang Hai Nguyen, Rui Tan, and David K. Y. Yau. 2015. Safety-Assured Performance Features in Complex Systems: Smart Grid Collaborative Load Management. Technical Report. ADSC. http://publish.illinois.edu/resilient-grid/files/2015/02/master.pdf.

[17]

NYISO. 2015a. New York Independent System Operator (NYISO) Real-Time Actual Load. Retrieved January 10, 2017, from http://mis.nyiso.com/public/P-58Blist.htm.

[18]

NYISO. 2015b. New York Independent System Operator (NYISO) Load Forecast Assumptions. Retrieved January 10, 2017, from http://www.nyiso.com/public/webdocs/markets_operations/market_data/load_data/FERC890aDALFDesc.pdf.

[19]

Les Pereira, Dmitry Kosterev, Donald Davies, and Shawn Patterson. 2004. New thermal governor model selection and validation in the WECC. IEEE Transactions on Power Systems 19, 1, 517--523.

[20]

PowerWorld. 2015. PowerWorld (version 17). Retrieved January 10, 2017, from http://www.powerworld.com.

[21]

Public Act. 2014. Public Act 094-0977. Retrieved January 10, 2017, from http://www.ilga.gov/legislation/publicacts/94/PDF/094-0977.pdf.

[22]

Mardavij Roozbehani, Munther A. Dahleh, and Sanjoy K. Mitter. 2012a. Volatility of power grids under real-time pricing. IEEE Transactions on Power Systems 27, 4, 1926--1940.

[23]

Mardavij Roozbehani, Mesrob Ohannessian, Donatello Materassi, and Munther A. Dahleh. 2012b. Load-Shifting Under Perfect and Partial Information: Models, Robust Policies, and Economic Value. Retrieved January 10, 2017, from https://dahleh.lids.mit.edu/wp-content/uploads/2012/08/2012-Load-ShiftingUnderPerfectAndPartialInformation.pdf.

[24]

Lui Sha. 2001. Using simplicity to control complexity. IEEE Software 18, 4, 20--28.

Digital Library

[25]

Joe A. Short, David G. Infield, and Leon L. Freris. 2007. Stabilization of grid frequency through dynamic demand control. IEEE Transactions on Power Systems 22, 3, 1284--1293.

[26]

Kai Sun, Siddharth Likhate, Vijay Vittal, V. Sharma Kolluri, and Sujit Mandal. 2007. An online dynamic security assessment scheme using phasor measurements and decision trees. IEEE Transactions on Power Systems 22, 4, 1935--1943.

[27]

Jay Taneja, Randy Katz, and David Culler. 2012. Defining CPS challenges in a sustainable electricity grid. In Proceedings of the 3rd ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS’12). ACM, New York, NY, 119--128.

Digital Library

[28]

Benjamin W. Wah, Yixin Chen, and Tao Wang. 2007. Simulated annealing with asymptotic convergence for nonlinear constrained optimization. Journal of Global Optimization 39, 1, 1--37.

Digital Library

[29]

Xiaofeng Wang, Naira Hovakimyan, and Lui Sha. 2013. L1Simplex: Fault-tolerant control of cyber-physical systems. In Proceedings of the 4th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS’13). ACM, New York, NY, 41--50.

Digital Library

[30]

Yan Xu, Zhao Yang Dong, Jun Hua Zhao, Pei Zhang, and Kit Po Wong. 2012. A reliable intelligent system for real-time dynamic security assessment of power systems. IEEE Transactions on Power Systems 27, 3, 1253--1263.

[31]

Zhao Xu, Jacob Østergaard, and Mikael Togeby. 2011. Demand as frequency controlled reserve. IEEE Transactions on Power Systems 26, 3, 1062--1071.

Cited By

Lou XTran CTan RYau DKalbarczyk ZLiu XTabuada PPajic MBushnell L(2019)Assessing and mitigating impact of time delay attackProceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems10.1145/3302509.3311042(207-216)Online publication date: 16-Apr-2019
https://dl.acm.org/doi/10.1145/3302509.3311042

Index Terms

Collaborative Load Management with Safety Assurance in Smart Grids
1. General and reference
  1. Cross-computing tools and techniques
    1. Reliability
2. Networks
  1. Network types
    1. Cyber-physical networks

Recommendations

Safety-Assured Collaborative Load Management in Smart Grids
ICCPS '14: ICCPS '14: ACM/IEEE 5th International Conference on Cyber-Physical Systems (with CPS Week 2014)

When a power grid is overloaded, load shedding is a conventional way to combat the imbalance between supply and demand that may jeopardize the grid's safety. However, disconnected customers may be excessively inconvenienced or even endangered. With the ...
Load Management for Multiple Datacenters towards Demand Response in the Smart Grid Integrating Renewable Energy
CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence

Recently, as the renewable and distributed power sources boost, many such resources are integrated into the smart grid as clean energy input. However, since the generation of solar power is intermittent and unstable, the smart grid needs to regulate the ...
Modeling safety and airworthiness (RTCA DO-178B) information: conceptual model and UML profile

Several safety-related standards exist for developing and certifying safety-critical systems. System safety assessments are common practice and system certification according to a standard requires submitting relevant system safety information to ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Cyber-Physical Systems

ACM Transactions on Cyber-Physical Systems Volume 1, Issue 2

April 2017

214 pages

ISSN:2378-962X

EISSN:2378-9638

DOI:10.1145/3015781

Editor:
Tei-Wei Kuo
National Taiwan University, and Academia Sinica, Taiwan

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 03 February 2017

Accepted: 01 December 2016

Revised: 01 June 2016

Received: 01 June 2015

Published in TCPS Volume 1, Issue 2

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Singapore Agency for Science, Technology and Research
Singapore's National Research Foundation

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
165
Total Downloads

Downloads (Last 12 months)5
Downloads (Last 6 weeks)1

Reflects downloads up to 20 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Lou XTran CTan RYau DKalbarczyk ZLiu XTabuada PPajic MBushnell L(2019)Assessing and mitigating impact of time delay attackProceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems10.1145/3302509.3311042(207-216)Online publication date: 16-Apr-2019
https://dl.acm.org/doi/10.1145/3302509.3311042

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents