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Large Scale Multi-area Static/Dynamic Economic Dispatch using Nature Inspired Optimization

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Abstract

Economic dispatch (ED) ensures that the generation allocation to the power units is carried out such that the total fuel cost is minimized and all the operating equality/inequality constraints are satisfied. Classical ED does not take transmission constraints into consideration, but in the present restructured power systems the tie-line limits play a very important role in deciding operational policies. ED is a dynamic problem which is performed on-line in the central load dispatch centre with changing load scenarios. The dynamic multi-area ED (MAED) problem is more complex due to the additional tie-line, ramp-rate and area-wise power balance constraints. Nature inspired (NI) heuristic optimization methods are gaining popularity over the traditional methods for complex problems. This work presents the modified particle swarm optimization (PSO) based techniques where parameter automation is effectively used for improving the search efficiency by avoiding stagnation to a sub-optimal result. This work validates the performance of the PSO variants with traditional solver GAMS for single as well as multi-area economic dispatch (MAED) on three test cases of a large 140-unit standard test system having complex constraints.

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Acknowledgment

The authors sincerely acknowledge the financial support provided by University Grant Commission (UGC), New Delhi, India under major research project entitled Power System Optimization and Security Assessment using Soft Computing Techniques, vide F No. 34-399/2008 (SR) dated, December 24, 2008. The authors also thank Madhav Institute of Technology and Science, Gwalior for providing facilities for carrying out this work. The first author acknowledges UGC research award for post doctoral work sanctioned by UGC, New Delhi vide letter no. F-30-120(SC)/2009 (SA-II).

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Authors and Affiliations

  1. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India

    Manjaree Pandit, Kalpana Jain & Hari Mohan Dubey

  2. Department of Electrical Engineering, Nagaji Group of Institutes, Gwalior, Madhya Pradesh, India

    Rameshwar Singh

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  1. Manjaree Pandit
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  2. Kalpana Jain
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Correspondence to Manjaree Pandit.

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Pandit, M., Jain, K., Dubey, H.M. et al. Large Scale Multi-area Static/Dynamic Economic Dispatch using Nature Inspired Optimization. J. Inst. Eng. India Ser. B 98, 221–229 (2017). https://doi.org/10.1007/s40031-016-0248-2

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