Abstract
Environmental Economic Dispatch is carried out in the energy control center to find the optimal thermal generation schedule such that power balance criterion and unit operating limits are satisfied and the fuel cost as well as emission is minimized. Environmental economic dispatch presents a complex, dynamic, non-linear and discontinuous optimization problem for the power system operator. It is quite well known that gradient based methods cannot work for discontinuous or nonconvex functions as these functions are not continuously differentiable As a result, evolutionary methods are increasingly being proposed. This paper proposes a chaotic micro bacterial foraging algorithm (CMBFA) employing a time-varying chemotactic step size in micro BFA. The convergence characteristic, speed, and solution quality of CMBFA is found to be significantly better than classical BFA for a 3-unit system and the standard IEEE 30-bus test system.
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Pandit, N., Tripathi, A., Tapaswi, S., Pandit, M. (2011). Static/Dynamic Environmental Economic Dispatch Employing Chaotic Micro Bacterial Foraging Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_69
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DOI: https://doi.org/10.1007/978-3-642-27172-4_69
Publisher Name: Springer, Berlin, Heidelberg
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