Hydrothermal Economic Dispatch Incorporating the Valve Point Effect in Thermal Units Solved by Heuristic Techniques

This document explores short-term hydrothermal economic dispatch (HTED) while explicitly modeling the valve-point effect of thermal units as a factor that adds complexity to power system optimization. Two nature-inspired optimizers, the Bat Algorithm (BAT) and the Artificial Bee Colony (ABC) algorithm, were used on a 24 h horizon for nine unit power plants (five thermal, four hydro). After 30 independent runs, BAT produced the lowest daily operating cost at USD 307,952.44, whereas ABC obtained USD 311,457.48, a 1.14% saving (USD 3.5 k) in favour of BAT. However, ABC converged almost twice as fast, stabilizing after around 40 iterations, while BAT required around 80 iterations. The results demonstrate that BAT offers a modest but measurable economic advantage, whereas ABC provides faster convergence, which is important when real-time computational limits dominate. These quantitative findings confirm that meta-heuristic techniques are practical tools for HTED and highlight the trade-off between cost minimization and computational speed.

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Publication Details

Journal
Energies
Published
2025-05-27
DOI
https://doi.org/10.3390/en18112789
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Hydrothermal Economic Dispatch Incorporating the Valve Point Effect in Thermal Units Solved by Heuristic Techniques

Carlos Barrera-Singaña, Luis Tipán, K. Hernández
Energies
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
article

Hydrothermal Economic Dispatch Incorporating the Valve Point Effect in Thermal Units Solved by Heuristic Techniques

Carlos Barrera-Singaña, Luis Tipán, K. Hernández
article en

Abstract

This document explores short-term hydrothermal economic dispatch (HTED) while explicitly modeling the valve-point effect of thermal units as a factor that adds complexity to power system optimization. Two nature-inspired optimizers, the Bat Algorithm (BAT) and the Artificial Bee Colony (ABC) algorithm, were used on a 24 h horizon for nine unit power plants (five thermal, four hydro). After 30 independent runs, BAT produced the lowest daily operating cost at USD 307,952.44, whereas ABC obtained USD 311,457.48, a 1.14% saving (USD 3.5 k) in favour of BAT. However, ABC converged almost twice as fast, stabilizing after around 40 iterations, while BAT required around 80 iterations. The results demonstrate that BAT offers a modest but measurable economic advantage, whereas ABC provides faster convergence, which is important when real-time computational limits dominate. These quantitative findings confirm that meta-heuristic techniques are practical tools for HTED and highlight the trade-off between cost minimization and computational speed.

EnergiesVol. 18(11)
Politecnica Salesiana University (EC)
Universidad Politécnica Salesiana del Ecuador
Openalex Percentile: Top 89%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
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