Economic Power Dispatch of a Grid-Tied Photovoltaic-Based Energy Management System: Co-Optimization Approach

Author:

Adenuga Olukorede Tijani1ORCID,Krishnamurthy Senthil1

Affiliation:

1. Department of Electrical, Electronic and Computer Engineering, Cape Peninsula University of Technology, Bellville, Cape Town 7535, South Africa

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.

Funder

National Research Foundation

Eskom Tertiary Education Support Program

Eskom Power Plant Engineering Institute

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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