A REVIEW ON APPLICATION OF NEURAL NETWORKS AND FUZZY LOGIC TO SOLVE HYDROTHERMAL SCHEDULING PROBLEM

Authors

  • S. Haroon Electrical Engineering Department, University of Engineering and Technology Taxila, Pakistan
  • T. N. Malik Electrical Engineering Department, University of Engineering and Technology Taxila, Pakistan
  • S. Zafar Electrical Engineering Department, University of Engineering and Technology Taxila, Pakistan

Abstract

Electrical power system is highly complicated having hydro and thermal mix with large number of machines. To reduce power production cost, hydro and thermal resources are mixed. Hydrothermal scheduling is the optimal coordination of hydro and thermal plants to meet the system load demand at minimum possible operational cost while satisfying the system constraints. Hydrothermal scheduling is dynamic, large scale, non-linear and non-convex optimization problem. The classical techniques have failed in solving such problem. Artificial Intelligence Tools based techniques are used now a day to solve this complex optimization problem because of their no requirements on the nature of the problem. The aim of this research paper is to provide a comprehensive survey of literature related to both Artificial Neural Network (ANN) and Fuzzy Logic (FL) as effective optimization algorithms for the hydrothermal scheduling problem. The outcomes along with the merits and demerits of individual techniques are also discussed.

References

R. Ferrero, J. Rivera and S. Shahidehpour, IEEE

Transactions on Power Systems 13 (1998)1534.

C.-a. Li and D. Streiffert, Incremental Network

Flow Programming for Short-Term Hydrothermal

Scheduling, Proceedings of the Tenth Power

Systems Computation Conference (1990).

M. Mohan, K. Kuppusamy and M.A. Khan,

International Journal of Electrical Power &

Energy Systems 14 (1992) 39.

E. Gil, J. Bustos, and H. Rudnick, IEEE

Transactions on Power Systems 18 (2003) 1256.

N. Sinha, R. Chakrabarti and P. Chattopadhyay,

Electric Power Systems Research 66 (2003) 97.

M. Omar, M. Soliman, A.A. Ghany and

F. Bendary, International Journal of Electric

Power & Energy Systems 43 (2012) 1340.

I. Farhat and M. El-Hawary, Short-Term HydroThermal Scheduling Using an Improved Bacterial

Foraging Algorithm, IEEE Conference on

Electrical Power & Energy (2009) pp. 1-5.

R. Naresh and J. Sharma, Generation,

Transmission and Distribution, IEE Proceedings

(1999) 657.

M. Basu, Electric Power Systems Research 64

(2003) 11.

U.O. Aliyu, G.K. Venayagamoorthy and S.Y.

Musa, Adaptive Load Frequency Control of

Nigerian Hydrothermal System Using Unsupervised and Supervised Learning Neural Networks,

IEEE Power Engineering Society General Meeting

(10 June 2004) pp. 1553-1558.

R.R. Aquino, M.A. Carvalho, O.N. Neto, M.M.

Lira, G.J.de Almeida, and S.N. Tiburcio,

Recurrent Neural Networks Solving a Real Large

Scale Mid-Term Scheduling for Power Plants,

International Joint Conference on Neural

Networks (2010) pp. 1-6.

R. Baños, F. Manzano-Agugliaro, F. Montoya,

C. Gil, A. Alcayde and J. Gómez, Renewable and

Sustainable Energy Reviews 15 (2011) 1753.

L.C. Saikia, S. Mishra, N. Sinha and J. Nanda,

International Journal of Electrical Power &

Energy Systems 33 (2011) 1101.

J. García-González, E. Parrilla and A. Mateo,

European Journal of Operational Research 181

(2007) 1354.

M. Suman and M.V.G. Rao, Recent 14 (2014)

A. Carneiro and D. Silva Filho, Fuzzy Logic

Applied to Operation Rules for Large

Hydrothermal Power Systems, Power System

Technology, International Conference on Power

(1998) pp. 918-922.

J. Dhillon, S. Parti and D. Kothari, International

Journal of Electrical Power & Energy Systems 23

(2001) 19.

J. Dhillon, S. Parti, and D. Kothari, IEE

Proceedings-Generation, Transmission and

Distribution 149 (2002) 191.

M. Basu, Electric Power Systems Research 69

(2004) 277.

M. Basu, Electric Power Components and Systems

(2004) 1287.

J. Nanda and A. Mangla, Automatic Generation

Control of an Interconnected Hydro-Thermal

System Using Conventional Integral and Fuzzy

Logic Controller, Electric Utility Deregulation,

Restructuring and Power Technologies,

Proceedings of the IEEE International Conference

on DRPT (2004) pp. 372-377.

M. Basu, International Journal of Emerging

Electric Power Systems 8 (2007).

G.-q. HU and R.-m. HE, Journal of North China

Electric Power University 3 (2007).

B. Anand and A. E. Jeyakumar, Load Frequency

Control of Hydro-Thermal System with Fuzzy

Logic Controller Considering Boiler Dynamics,

TENCON 2008, IEEE Region 10 Conference

(2008) pp. 1-5.

B. Monte and S. Soares, Fuzzy Inference Systems

Approach for Long Term Hydrothermal

Scheduling, Power Systems Conference and

Exposition, PSCE'09. IEEE/PES (2009) pp. 1-7.

R.A.L. Rabelo, R.A.S. Fernandes, A.A.F.M.

Carneiro, and R.T.V. Braga, An Approach Based

on Takagi-Sugeno Fuzzy Inference System

Applied to the Operation Planning of

Hydrothermal Systems, IEEE International

Conference on Fuzzy Systems (27-30 June 2011)

pp. 1111-1118.

Downloads

Published

27-04-2014

How to Cite

[1]
S. Haroon, T. N. Malik, and S. Zafar, “A REVIEW ON APPLICATION OF NEURAL NETWORKS AND FUZZY LOGIC TO SOLVE HYDROTHERMAL SCHEDULING PROBLEM”, The Nucleus, vol. 51, no. 2, pp. 239–247, Apr. 2014.

Issue

Section

Articles