Skip to main content

Literature Review

  • Chapter
  • First Online:
  • 906 Accesses

Part of the book series: Power Electronics and Power Systems ((PEPS))

Abstract

The goal of this chapter is to provide prior work done with linear-programming approaches for the resource-allocation problem. Operations-research (OR) modeling often concerns finding the best quantitative solution for management problems [HL01, Mom01]. The OR methods include mathematical-optimization modeling as simulation, and using OR methods has grown significantly since their origination during World War II. Templeman [Tem91] describes quantitative OR methods for designing and controlling industrial and economical operations. Many private and government organizations have improved their operations by successfully using mathematical programming [Wad83, Aro02, Chv83, Dan63, SS85]. This book focuses on a resource-allocation problem and applies linear programming for the solution approach.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Arora, S. (2006). Proving integrality gaps without knowing the linear program. Proceedings of the 43rd Symposium on Foundations of Computer Science (pp. 313–322).

    Google Scholar 

  2. Bradley, G., Brown, G., and Graves, G (1977). Design and implementation of large scale primal transshipment algorithms. Management Science, 1–34.

    Google Scholar 

  3. Bignucoloa, F., Caldona, R., & Prandonib, V. (2008). Radial MV networks voltage regulation with distribution management system coordinated controller. Electric Power Systems Research, 78(4), 634–664.

    Article  Google Scholar 

  4. Boutilier, C. (2001). Planning and programming with first-order Markov decision processes: Insights and challenges. City, MA: Morgan Kaufmann.

    Google Scholar 

  5. Boutilier, C. (2002). A POMDP formulation of preference elicitation problems. Proceedings of the Eighteenth National Conference on Artificial Intelligence, City, CA (pp. 239–246).

    Google Scholar 

  6. Chvatal, V. (1983). Linear programming. New York, NY: Freeman.

    MATH  Google Scholar 

  7. Dantzig, G. B. (1963). Linear programming and extensions. Princeton, NJ: Princeton University Press.

    Book  MATH  Google Scholar 

  8. Dantzig, G. B. (1983). Reminiscences about the origins of linear programming, mathematical programming: The state of the art springer lecture notes (pp. 78–86). Berlin, Germany: Springer.

    Google Scholar 

  9. Dobson, I., Carreras, B., & Newman, D. E. (2004). Probabilistic load-dependent cascading failure with limited component interactions. IEEE International Symposium on Circuits and Systems, City, Canada (pp. 15–32).

    Google Scholar 

  10. Dwyer, A., Nielsen, R., Stangl, J., & Markushevich, N. (1995). Load to voltage dependency tests at B.C. hydro, IEEE Transactions on Power Systems, 10(2), 709–715.

    Google Scholar 

  11. Farag, E., El-Saadany, F., & Seethapathy, R. (2012). A two ways communication-based distributed control for voltage regulation in smart distribution feeders. IEEE Transaction on Smart Grid, 766–772.

    Google Scholar 

  12. Greitzer, F., Podmor, R., Robinson, M., & Ey, P. (2009). Naturalistic decision making for power system operators. In International Conference on Naturalistic Decision Making (NDM). London, England.

    Google Scholar 

  13. Gueret, C., Prins, C., & Sevaux, M. (2000). Programmation lineaire. Paris: Editions Eyrolles.

    Google Scholar 

  14. Hillier, F., & Lieberman, G. (2001). Introduction to operations research. City, England: McGraw-Hill.

    MATH  Google Scholar 

  15. Khattam, W., Hegazy, Y., & Salama, Y. (2005). An integrated distributed generation optimization model for distribution system planning. IEEE Transactions on Power Systems, 20(2), 1158–1165.

    Google Scholar 

  16. Momoh, J. (2001). Electric power system Applications of optimization. City, NY: Marcel Dekker.

    Google Scholar 

  17. Moore, R. (1991). Global optimization to prescribed accuracy. Computers and Mathematics with Applications, 21(6), 25–39.

    Article  MathSciNet  MATH  Google Scholar 

  18. Nguyen, C., & Flueck, A. (2012). Agent based restoration with distributed energy storage support in smart grids. IEEE Transactions on Smart Grid, 3(2), 1029–1038.

    Google Scholar 

  19. Pipattanasomporn, M., Feroze, H., & Rahman, S. Multi-agent systems in a distributed smart grid: Design and implementation. Proceedings of IEEE PES 2009 Power Systems Conference and Exposition, Seattle, Washington, USA, March 2009 (pp. 1–6).

    Google Scholar 

  20. Ranganathan, P., & Nygard, K. A smart agent oriented linear programming control in electric grid. Annual Electric Power and Energy Conference, Canada, October 2012 (pp. 102–106).

    Google Scholar 

  21. Powell, W., Sheffi, Y., Nickerson, S., Butterbaugh, K., & Atherton, S. (1988). Maximizing profits for North American Van Lines truckload division: A new framework for pricing and operations. Interfaces, 18(1), 21–41.

    Article  Google Scholar 

  22. PowerGen plc. (1998). Private communication.

    Google Scholar 

  23. Ranganathan, P., & Nygard, K. (2010). An optimal resource assignment problem in Smart grid. The Second International Conference on Future Computational Technologies and Applications, Portugal, November 26 (pp. 75–82).

    Google Scholar 

  24. Salam, S. (2004). Comparison of Lagrangian relaxation and truncated dynamic programming methods for solving hydrothermal coordination problems. Proceedings of International Conference on Intelligent Sensing and Information Processing (pp. 265–270).

    Google Scholar 

  25. Song, Y. (1999). Modern optimization techniques in power systems. City, ST: Kluwer Academic Publishers.

    Book  MATH  Google Scholar 

  26. Sullivan, R., & Secrest, C. (1985). A simple optimization DSS for production planning at Dairymans Cooperative Creamery Association. Interfaces, 15(5), 46–53.

    Article  Google Scholar 

  27. Templeman, B. (1991). Optimization and decision support systems in civil engineering. City, ST: Routledge, Gordon and Breach Science Publishers Ltd.

    Google Scholar 

  28. Waddell, R. (1983). A model for equipment replacement decision and policies. Interfaces, 13(4), 1–7.

    Article  Google Scholar 

  29. Wang, H. (2001). Multi-agent co-ordination for the secondary voltage control in power system contingencies. Proceedings of IEEE Generation, Transmission and Distribution, 148(1), 61–66.

    Article  Google Scholar 

  30. Williams, P. (1993). Model building in mathematical programming (3rd revised edition). Chichester, England: Wiley.

    Google Scholar 

  31. Wright, S. (1997). Primal-dual interior point methods. SIAM, 145–157.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Ranganathan, P., Nygard, K.E. (2017). Literature Review. In: Distributed Linear Programming Models in a Smart Grid. Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-52617-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52617-1_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52616-4

  • Online ISBN: 978-3-319-52617-1

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics