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Hydro-thermal generation scheduling using integrated gravitational search algorithm and predator–prey optimization technique

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Abstract

In this research work, an integrated optimization technique has been proposed by coordinating gravitational search algorithm (GSA) and predator–prey optimization (PPO) in a suitable manner to improve the search capability of algorithm. The integrated technique is applied to obtain the optimum generation schedule of hydro-thermal generation system considering some of the practical constraints and transmission losses. For the hydro-thermal systems, the multi-chain hydro model has been undertaken with due consideration of water transport delay between reservoirs. In PPO algorithm, the search is performed by considering the experience of other prey particles along with the effect of predator particle. The predator effect helps to avoid any possible stagnation of global best prey on local optima due to the fear created by predator particle. In PPO algorithm, the quality of the solutions has not been considered while updating the position of prey or predator, whereas in GSA, the agent direction is computed based on the overall force, and it is proportional to the quality of the solutions. Further, GSA is memory less and agent direction is not influenced by best positions. In the proposed integrated technique, the position of agent/prey is directed by overall force around themselves, global best prey position and predator effect. The proposed integrated technique is tested on three hydro-thermal systems. A penalty-free constraint handling approach is employed to satisfy all equality and inequality constraints. The results obtained from proposed technique have been compared with the results reported with the existing technique, and it is experienced that proposed technique is able to provide a better solution with improved convergence characteristics. The statistical analysis of results is also done to measure the sensitivity and robustness of the proposed technique.

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Authors and Affiliations

  1. Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, 147004, India

    Nitin Narang

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  1. Nitin Narang
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Correspondence to Nitin Narang.

Appendix

Appendix

See Tables 9, 10 and 11.

Table 9 Test system-II: ramp rate limits for thermal units
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Table 10 Test system-II: POZ for reservoir discharge rate
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Table 11 Test system-II: loss coefficients
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Narang, N. Hydro-thermal generation scheduling using integrated gravitational search algorithm and predator–prey optimization technique. Neural Comput & Applic 30, 519–538 (2018). https://doi.org/10.1007/s00521-016-2693-x

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