Uncertainty-based dynamic economic dispatch for diverse load and wind profiles using a novel hybrid algorithm

Sourav Basak (), Bishwajit Dey () and Biplab Bhattacharyya ()
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Sourav Basak: Indian Institute of Technology (Indian School of Mines)
Bishwajit Dey: Indian Institute of Technology (Indian School of Mines)
Biplab Bhattacharyya: Indian Institute of Technology (Indian School of Mines)

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 5, No 32, 4723-4763

Abstract: Abstract Optimal scheduling of the conventional generating units for five dynamic test systems is percolated in this paper. When the valve point loading effect (VPE) is present, the system's fitness function becomes non-convex and nonlinear. This paper compares and contrasts among three types of wind profile formulations, namely linear, quadratic and cubic, which are used to calculate wind power from hourly wind speed to find the profile with the greatest penetration of wind power. Thereafter, the wind profiles in turns for the five test systems are used to execute dynamic economic dispatch. The optimization tool of the study was a unique hybrid algorithm created by combining the properties of the recently developed crow search algorithm (CSA) and JAYA. Results infer that maximum level of wind penetration was attained by linear wind profile and a fuel cost reduction of 8% was realized upon incorporation of the same. Also owing to its high penetration level, the least generation cost was obtained with linear wind profile when compared to quadratic and cubic ones. Furthermore, numerical results also claims that proposed hybrid CSAJAYA approach consistently yielded better quality solutions within minimum execution time without being affected by the dimension of the problem, thereby outperforming a long list of algorithms implemented for the study.

Keywords: Dynamic economic dispatch; VPE or valve point effect; Wind power; Optimization algorithms; CSAJAYA (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02218-5

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