Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/9754
Title: Economic power dispatch of a grid-tied photovoltaic-based energy management system: co-optimization approach
Authors: Adenuga, Olukorede 
Krishnamurthy, Senthil 
Keywords: Economic power dispatch;Photovoltaic (PV);Particle swarm optimization;co-optimization;energy management system
Issue Date: 2023
Publisher: MDPI AG
Source: Adenuga, O. & Krishnamurthy, S. 2023. Economic power dispatch of a grid-tied photovoltaic-based energy management system: co-optimization approach. Mathematics, 11(15):1-22. [https://doi.org/10.3390/math11153266]
Journal: Mathematics 
Abstract: The requirement for the integration of power plants due to the cyclical rise in electrical energy consumption is due to the fluctuating load demand experienced with the current grid systems. This integration necessitates effectively allocating loads to the power plants for a minimum grid-tied transmission line cost, while meeting the network constraints. In this paper, we formulate an optimization problem of minimizing the total operational cost of all committed plants transmitted to the grid, while also meeting the network constraints and ensuring economic power dispatch (EPD) and energy management system co-optimization. The developed particle swarm optimization (PSO) method resolves the optimization problem using a piecewise quadratic function to describe the operational cost of the generation units, and the B coefficient approach is employed to estimate the transmission losses. Intelligent adjustments are made to the acceleration coefficients, and a brand-new algorithm is suggested for distributing the initial power values to the generation units. The developed economic power dispatch strategy successfully demonstrated an imperative cost reduction, with a connected load of 850 MW, 1263 MW, and 2630 MW of power demand, contrasted with previous PSO application cost values percentage, maximum yearly cost savings of (0.55%, 91.87), (46.55%, 3.78), and (73.86%, 89.10), respectively, and significant environmental benefits. The proposed co-optimization approach can significantly enhance the self-consumption ratio compared to the baseline method.
URI: http://hdl.handle.net/11189/9754
DOI: doi.org/10.3390/math11153266
2227-7390 (online)
Appears in Collections:Eng - Journal articles (DHET subsidised)

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