Minimization of load shedding by sequential use of linear programming and particle swarm optimization

Minimization of load shedding during contingency conditions is solved as an optimization problem. As a new topic, instead of local load shedding, total load shedding of a large power system is considered. Power generation rescheduling is considered to minimize the load shedding, as well. Different importance factors for buses are also considered. The linear programming method (LP) is used to solve this problem in a short period of time without considering some power system constraints. Particle swarm optimization (PSO) is also used to solve the problem by considering all power system constraints, but with a longer solving time. Finally, a new method, the sequential use of LP and PSO, is proposed, which is faster than PSO and considers all constraints. The IEEE 14 bus test system is used to compare the performance of the mentioned methods and a comparison of the proposed algorithm and genetic algorithm is accomplished.

Minimization of load shedding by sequential use of linear programming and particle swarm optimization

Minimization of load shedding during contingency conditions is solved as an optimization problem. As a new topic, instead of local load shedding, total load shedding of a large power system is considered. Power generation rescheduling is considered to minimize the load shedding, as well. Different importance factors for buses are also considered. The linear programming method (LP) is used to solve this problem in a short period of time without considering some power system constraints. Particle swarm optimization (PSO) is also used to solve the problem by considering all power system constraints, but with a longer solving time. Finally, a new method, the sequential use of LP and PSO, is proposed, which is faster than PSO and considers all constraints. The IEEE 14 bus test system is used to compare the performance of the mentioned methods and a comparison of the proposed algorithm and genetic algorithm is accomplished.

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  • A. Shandilya, H. Gupta, J. Sharma, “Method for generation rescheduling and load shedding to alleviate line overloads using local optimization”, IEE Proceedings Generation, Transmission and Distribution, Vol. 140, pp. 342, 1993.
  • S.J. Huang, C.C. Huang, “Adaptive approach to load shedding including pumped storage units during underfre- quency conditions”, IEE Proceedings Generation, Transmission and Distribution, Vol. 148, pp. 165-171, 2001.
  • V.N. Chuvychin, N.S. Gurov, S.S. Venkata, R.E. Brown, “Adaptive approach to load shedding and spinning reserve control during underfrequency conditions”, IEEE Transaction On Power Systems, Vol. 11, pp. 1805-1810, 1996.
  • T.Q. Tuan, J. Fandino, J.C. Sabonnadiere, H. Vu, B. Heilbronn, “Determination of load shed using linear program- ming to avoid voltage instability”, International Power Conference Proceedings, Vol. 2, pp. 553-557, 1993.
  • E. De Tuglie, M. Dicorato, M. La Scala, P. Scarpellini, “A corrective control for angle and voltage stability enhancement on the transient time-scale”, IEEE Transactions on Power Systems, Vol. 15, pp. 1345-1353, 2000.
  • T.S.P. Fernandes, J.R. Lenzi, M.A. Mikilita, “Load shedding strategies using optimal load flow with relaxation of restrictions”, IEEE Transactions on Power Systems, Vol. 23, pp. 712-718, 2008.
  • W.M. Al Hasawi, K.M. El Naggar, “Optimum steady state load shedding scheme using genetic based algorithm”, th Mediterranean Electrotechnical Conference, pp. 605-609, 2002.
  • M.K. Maharana, K.S. Swarup, “Particle swarm optimization based corrective strategy to alleviate overloads in power system”, World Congress on Nature & Biologically Inspired Computing, pp. 37-42, 2009.
  • J.K. Delson, S.M. Shahidehpour, “Linear programming applications to power system economics, planning and operations”, IEEE Transactions on Power Systems, Vol. 7, pp. 1155-1163, 1992.
  • C.M. Shen, M.A. Laughton, “Power system load scheduling with security constraints using dual linear program- ming”, Proceedings of IEEE, Vol. 117, pp. 2117-2127, 1970.
  • B. Stott, O. Alsac, A.J. Monticelli, “Security analysis and optimization”, Proceedings of the IEEE, Vol. 75, pp. 1644, 1987.
  • M.R. Alrashidi, M.E. El-Hawary, “A survey of particle swarm optimization in electric systems”, IEEE Transaction on Evolutionary Computation, pp. 913-918, 2009.
  • R.L. Haupt, S.E. Haupt, Practical Genetic Algorithms, 2nd edition, Hoboken, New Jersey, John Wiley & Sons, http://www.ee.washington.edu/research/pstca/pf14/ pg tca14bus.htm