Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies DOI

Nor Laili Ismail,

Ismail Musirin,

Nofri Yenita Dahlan

et al.

Published: Dec. 5, 2022

Economic dispatch study is important in the electric power industry because it concerned with efficient electrical production and economics. It crucial to reduce operating costs of energy even small savings have a large impact on total generation fuel consumption. This paper presents proposed algorithm namely Hybrid Evolutionary-Barnacles Mating Optimization (HEBMO) solve non-convex economic (ED) problems specifically under line generator outages. The evaluation tested two types reliability test systems (RTS), named IEEE 30-Bus RTS 57-Bus RTS. HEBMO compared single optimization algorithm, EP BMO for performance purposes. results show that outperforms terms minimizing cost. On other hand, also achieves convincing fast computational time.

Language: Английский

A Social Group Optimization Algorithm Using the Laplace Operator for the Economic Dispatch Problem DOI Open Access

Dinu Călin Secui,

Cristina Hora, Florin Ciprian Dan

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(2), P. 405 - 405

Published: Feb. 4, 2025

The economic dispatch (ED) problem focuses on the optimal scheduling of thermal generating units in a power system to minimize fuel costs while satisfying operational constraints. This article proposes modified version social group optimization (SGO) algorithm address ED with various practical characteristics (such as valve-point effects, transmission losses, prohibited operating zones, and multi-fuel sources). SGO is population-based metaheuristic strong exploration capabilities, but for certain types problems, it may stagnate local optimum due potential imbalance between exploitation. new version, named SGO-L, retains structure incorporates Laplace operator derived from distribution into all iterative solution update equations. adjustment generates more effective search steps space, improving exploration–exploitation balance overall performance terms stability quality. SGO-L validated four systems small (six-unit), medium (10-unit), large (40-unit 110-unit) sizes diverse characteristics. efficiency compared other algorithms. experimental results demonstrate that proposed robust than well-known algorithms particle swarm optimization, genetic algorithms, differential evolution, cuckoo algorithms) competitor mentioned study. Moreover, non-parametric Wilcoxon statistical test indicates promising original For example, standard deviation obtained by shows significantly lower values (6.02 × 10−9 USD/h six-unit system, 7.56 10−5 10-unit 75.89 40-unit 4.80 10−3 110-unit system) (0.44 50.80 274.91 1.04 system).

Language: Английский

Citations

0
Chaos-enhanced metaheuristics: classification, comparison, and convergence analysis DOI Creative Commons
Abdelhadi Limane, Farouq Zitouni, Saad Harous

et al.

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(3)

Published: Feb. 19, 2025

Language: Английский

Citations

0
Electric vehicle integrated tidal-solar-wind-hydro-thermal systems for strengthing the microgrid and environment sustainability DOI Creative Commons
Sunanda Hazra,

Debarati Datta,

Chandan Paul

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 28, 2025

Abstract Incorporating electric vehicles (EVs) into the power grid significantly impacts its safe and reliable operation, while unpredictable nature of wind adds further complications. Solar power, though less efficient in converting sunlight to electricity compared remains a popular renewable energy source. Combining solar is advantageous because can be harnessed both day night, unlike energy. Tidal also offers option, although it has own set challenges. Consequently, utilization sources (RESs) have become increasingly complex. Fossil fuels, on other hand, are major cause severe pollution. This study addresses integration wind, solar, tidal, vehicles, using unique moth-flame optimization technique, solve challenge hydrothermal scheduling (HTS). The primary objective reduce generation costs adhering various limitations, including transmission losses, thermal unit valve point effects, RESs variability. In order maximize management, several EVs currently being built as virtual plants (VPPs), utilizing sustainable sources. So, VPPs combined make micro-grid more rigid. minimize fuel expenditures by balancing load demand losses satisfying all conditions. By evaluating with MFO, this demonstrates effectiveness method compares advanced techniques, highlighting superior efficiency, utility reliability. When performance normal HTS system, RES EV based system observed, clearly observed that improved results 5.49% conventional suggested COMFO approach. findings show effectively contribute hydro-thermal integrated power.

Language: Английский

Citations

0
An improved slime mould algorithm using multiple strategies DOI

Mozhong Zhu,

Rongkun Zhu,

Feng Li

et al.

International Journal of Parallel Emergent and Distributed Systems, Journal Year: 2024, Volume and Issue: 39(4), P. 461 - 485

Published: May 13, 2024

Aiming at the defects of standard slime mould algorithm (SMA), such as local optima stagnation, slow convergence and improper balance between exploitation exploration, we propose an improved SMA that contains adaptive t-distributed variation strategy, location update formula chaotic opposition-based learning is, MISMA. Utilizing comparative experiments ablation studies on classical benchmark CEC2020 suite, proved MISMA outperforms other state-of-the-art rival algorithms speed, solution accuracy, robustness, each component achieves improvement stage exhibits synergistic effects.

Language: Английский

Citations

3
Advances in Slime Mould Algorithm: A Comprehensive Survey DOI Creative Commons

Yuanfei Wei,

Zalinda Othman, Kauthar Mohd Daud

et al.

Biomimetics, Journal Year: 2024, Volume and Issue: 9(1), P. 31 - 31

Published: Jan. 4, 2024

The slime mould algorithm (SMA) is a new swarm intelligence inspired by the oscillatory behavior of moulds during foraging. Numerous researchers have widely applied SMA and its variants in various domains field proved value conducting literatures. In this paper, comprehensive review introduced, which based on 130 articles obtained from Google Scholar between 2022 2023. study, firstly, theory described. Secondly, improved are provided categorized according to approach used apply them. Finally, we also discuss main applications SMA, such as engineering optimization, energy machine learning, network, scheduling image segmentation. This presents some research suggestions for interested algorithm, additional multi-objective discrete SMAs extending neural networks extreme learning machining.

Language: Английский

Citations

2
Data-driven width spread prediction model improvement and parameters optimization in hot strip rolling process DOI
Yanjiu Zhong, Jingcheng Wang, Jiahui Xu

et al.

Applied Intelligence, Journal Year: 2023, Volume and Issue: 53(21), P. 25752 - 25770

Published: Aug. 11, 2023

Language: Английский

Citations

5
Renewable energy utilizing and fluctuation stabilizing using optimal dynamic grid connection factor strategy and artificial intelligence-based solution method DOI
Zhi-Feng Liu,

Shi-Xiang Zhao,

X. Q. Zhang

et al.

Renewable Energy, Journal Year: 2023, Volume and Issue: 219, P. 119379 - 119379

Published: Sept. 28, 2023

Language: Английский

Citations

5
Directional crossover slime mould algorithm with adaptive Lévy diversity for the optimal design of real-world problems DOI Creative Commons

Ailiang Qi,

Dong Zhao, Fanhua Yu

et al.

Journal of Computational Design and Engineering, Journal Year: 2022, Volume and Issue: 9(6), P. 2375 - 2418

Published: Oct. 24, 2022

Abstract The slime mould algorithm (SMA) has become a classical applied in many fields since it was presented. Nevertheless, when faced with complex tasks, the converges slowly and tends to fall into local optimum. So, there is still room for improvement performance of SMA. This work proposes novel SMA variant (SDSMA), combining adaptive Lévy diversity mechanism directional crossover mechanism. Firstly, can improve population diversity. Then, enhance balance exploration exploitation, thus helping SDSMA increase convergence speed accuracy. compared variants, original algorithms, improved improved-SMAs, others on benchmark function set verify its performance. Meanwhile, Wilcoxon signed-rank test, Friedman other analytical methods are considered analyze experimental results. analysis results show that two strategies significantly improves computational cost smaller than function. Finally, proposed three real-world engineering design problems. experiments prove an effective aid tool computationally practical tasks.

Language: Английский

Citations

8
Five Phases Algorithm: A Novel Meta-heuristic Algorithm and Its Application on Economic Load Dispatch Problem DOI Open Access

Xiaopeng Wang Xiaopeng Wang,

Shu-Chuan Chu Xiaopeng Wang,

Václav Snášel Shu-Chuan Chu

et al.

網際網路技術學刊, Journal Year: 2023, Volume and Issue: 24(4), P. 837 - 848

Published: July 1, 2023

<p>A new meta-heuristic algorithm named the five phases (FPA) is presented in this paper. The proposed method inspired by theory traditional Chinese thought. FPA updates agents based on generating and overcoming strategy as well learning from agent with same label. has a simple structure but excellent performance. It also does not have any predefined control parameters, only two general parameters including population size terminal condition are required. This provides flexibility to users solve different optimization problems. For global optimization, 10 test functions CEC2019 suite used evaluate performance of FPA. experimental results confirm that better than 6 state-of-the-art algorithms particle swarm (PSO), grey wolf optimizer (GWO), multi-verse (MVO), differential evolution (DE), backtracking search (BSA), slime mould (SMA). Furthermore, applied Economic Load Dispatch (ELD) real power system problem. experiments give minimum cost operation obtained more competitive 14 counterparts. source codes can be found https://ww2.mathworks.cn/matlabcentral/fileexchange/118215-five-phases-algorithm-fpa.</p> <p>&nbsp;</p>

Language: Английский

Citations

4
An Efficient Solution for Economic Load Dispatch Using Cheetah Optimizer with Opposition-Based Learning and Adaptive Weighting Factor DOI Open Access

Victor Sai,

G. R. Jothi Lakshmi,

M Vanithasri

et al.

International journal of intelligent engineering and systems, Journal Year: 2024, Volume and Issue: 17(3), P. 139 - 148

Published: May 3, 2024

The multi-objective economic load dispatch problem (ELDP) with non-smooth cost functions and ramprate limits presents a challenging optimization task in power systems.This paper proposes the use of modified cheetah optimizer (MCO) that incorporates opposition-based learning (OBL) dynamic adaptive weighting factor to efficiently solve this problem.The simulations are conducted on standard test systems using MATLAB programming.A comparative study is performed, evaluating performance MCO against basic CO other similar heuristics.The results demonstrate effectiveness achieving optimal solutions for ELDP ramp-rate limits.The proposed approach offers promising solution addressing complex requirements system operation planning.The determined multi-criterion 3-bus as $6,838.6434/h,$7,738.789/h,and $8,252.033/hfor 700 MW, 800 MW 850 demand levels respectively.The evaluated $17,988.96/hfor 13-bus considering total 1800 MW.The 121960.30$/hr, 40-bus 10500 MW.These outcomes efficacy resolving generator valve controls.

Language: Английский

Citations

1