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Combined Economic and Emission Dispatch using RBF neural network

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Under the guidance of
Dr. N. Subrahmanyam
Presented by
B. Shiva Kumar

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Topics
¢ Introduction
¢ CEED
¢ RBF
¢ Algorithms
¢ OVERALL PROCESS DESCRIPTION
¢ CEED USING LAMBDA TECHNIQUE
¢ CLUSTERING TECHNIQUE
¢ CEED USING RBF
¢ Case studies
¢ 3GEN
¢ 6GEN
¢ 15GEN
¢ Conclusion




Introduction of work
¢ Formulating Combined economic and emission dispatch using RBF network
¢ comparing results using BPA network and conventional lambda technique



Combined Economic and Emission Dispatch
The multi-objective CEED problem is converted into single optimization problem by introducing price penalty factor, h
Minimize F = F + hpd* E
¢ The modified price penalty factor hpd, combines the emission with the normal fuel costs



Price Penalty Factor


¢ The price penalty factor for a particular load demand PD :
¢ Find the ratio between maximum fuel cost and maximum emission of each generator.
¢ sort hi values in ascending order.
¢ Add the maximum capacity of each unit (Pi,max) one at a time, starting from the smallest hi unit until Pi,max = PD
¢ At this stage, hi associated with the last unit in the process is the price penalty factor for the given load.



Modified Price Penalty Factor
¢ The computation steps for hpd :
¢ Find the ratio between maximum fuel cost and maximum emission of each generator
¢ sort hi values in ascending order
¢ Form an array, m by adding Pi,max one by one from the lowest hi value unit
¢ Add the elements of mi one at a time, starting from the smallest hi unit until S m > PD
¢ The modified price penalty factor hpd is computed by interpolating the values of hi for last two units by satisfying the corresponding load demand.



Numerical example
¢ hi = [h3 h2 h1] ; hi = [1.1909 2.6221 3.1057]
¢ The corresponding maximum limits of generating units are
Pi,max = [180 150 200]
¢ m is formed by adding maximum capacity of the units one by one
m = [180 330 530]
¢ For PD = 259MW; (180+330) MW >259MW
¢ The modified price penalty factor hm is computed by interpolating the values of hi for last two units by satisfying the corresponding load demand.
ie, hpd = 1.1909 + ((2.6221- 1.1909)/(330- 180))*(259- 180)
= 1.9446


MEMORISING FOR TRAINING
¢ Weight training:
1. First run the process with weights randomised with restrictions on itermax and epsilon
2. Repeat above step for a few trials say 6 - 9 trials and memorize all the finalised weights and Errorrate after complete training
3. Choose the best trial that is most successful among all trials
4. then run process using finalised weights after best run trial as initial set of weights instead of taking randomised weights
5. Repeation of above step 4 for itself for a few times
(say 5 “ 10) improves convergence time



Conclusion
¢ Combined economic and emission dispatch is formulated using RBF network.
“ Centres were apart
“ Memorising weights and centres, results in faster convergence
“ Network is tested for 3gen, 6gen, 15gen systems
¢ Can be combined with Unit Commitment Problem for complete study


References
An RBF Network With OLS and EPSO Algorithms for Real-Time Power Dispatch
by Chao-Ming Huang and Fu-Lu Wang
IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 22, NO. 1, FEBRUARY 2007
¢ R. Ramanathan, Emission constrained economic dispatch, IEEE Trans. Power Syst., vol. 9, no. 4, pp. 1994“2000, Nov. 1994.
¢ P. S. Kulkarni, A. G. Kothari, and D. P. Kothari, Combined economic and emission dispatch using improved backpropagation neural network, Elect. Mach. Power Syst., vol. 28, no. 1, pp. 31“44, Jan. 2000.
¢ P. S. Kulkarni, A. G. Kothari, and D. P. Kothari, Application of radial basis function neural network for economic dispatch, J. Inst. Eng. (India): Elect. Eng. Div., vol. 83, pp. 81“86, Sep. 2002.
¢ Solutions to Practical Unit Commitment Problems with Operational, Power Flow and Environmental Constraints I. Jacob Raglend and Narayana Prasad Padhy IEEE 2006
¢ Economic Power Dispatch Of Power System With Pollution Control Using Multiobjective Particle Swarm Optimization Tarek Bouktir, Rafik Labdani and Linda Slimani June 2007 University of Sharjah Journal of Pure & Applied Sciences Volume 4, No. 2

sir, i am doing project on this can u please send the entire project report and program with results file,it's very urgent sir