Multi-objective optimal power flow with wind–solar–tidal systems including UPFC using Adaptive Improved Flower Pollination Algorithm(AIFPA) DOI
Basudeb Mondal,

Susanta Dutta,

Soumen Biswas

et al.

Smart Science, Journal Year: 2024, Volume and Issue: 12(3), P. 495 - 518

Published: June 4, 2024

Among the most significant non-linear challenges for power network design and smooth functioning of current modern updated system networks is optimum flow (OPF) problem. Importance electrical modeling has recently come to light due incremental use energy from renewable sources in systems networks. The goal wind, solar tidal recreate issue OPF. In this work, Weibull, Lognormal, also Gumbel probability distribution functions were applied simulate uncertainties photovoltaic, system. Additionally, by adding test scenarios unpredictable involving minimization cost function, loss active power, voltage deviation, increase stability voltage. accordance with chosen thermal producing units, solutions evaluated using different locations IEEE 30-bus testing that incorporate sources. proposed planning problem was solved multi-objective function where unified controller are utilized as flexible AC transmission controllers via introduced optimization algorithms simulation outcomes aforementioned technique have been compared Multi Objective Adaptive Guided Differential Evolution algorithms. adaptive improved flower pollination algorithm (AIFPA) a strong reliable presented work. AIFPA can efficiently deal many kinds high-complexity objective regions situations. Utilizing an system, suggested approaches' performance examined range functions. results obtained effective finding optimal solution meta-heuristic reported literature.

Language: Английский

A multi-strategy particle swarm algorithm with exponential noise and fitness-distance balance method for low-altitude penetration in secure space DOI
Donglin Zhu, Siwei Wang, Jiaying Shen

et al.

Journal of Computational Science, Journal Year: 2023, Volume and Issue: 74, P. 102149 - 102149

Published: Oct. 11, 2023

Language: Английский

Citations

23
An optimal standalone wind-photovoltaic power plant system for green hydrogen generation: Case study for hydrogen refueling station DOI Creative Commons
Rizk M. Rizk‐Allah, Islam A. Hassan, Václav Snåšel

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102234 - 102234

Published: May 6, 2024

Sustainability goals include the utilization of renewable energy resources to supply needs in addition wastewater treatment satisfy water demand. Moreover, hydrogen has become a promising carrier and green fuel decarbonize industrial transportation sectors. In this context, research investigates wind-photovoltaic power plant produce for refueling station operate an electrocoagulation unit Ostrava, Czech Republic's northeast region. The study conducts techno-economic analysis through HOMER Pro® software optimal sizing components investigate economic indices plant. employs photovoltaic panels wind turbines required electricity electrolyzers reactors. As off-grid system, lead acid batteries are utilized store surplus electricity. Wind speed solar irradiation key role site dependent parameters that determine cost hydrogen, electricity, treatment. simulated model considers capital, operating, replacement costs system components. proposed 240 kg as well 720 kWh electrical daily unit, respectively. Accordingly, annually generates 6997990 85595 hydrogen. Based on analysis, project's NPC is determined be €5.49 M levelized Hydrogen (LCH) 2.89 €/kg excluding compressor costs. This value proves effectiveness which encourages fuel-cell electric vehicles (FCVs). Furthermore, emerging studies treatment, increasing production lowering LCH. Therefore, able provide practicable methodology support components, beneficial industrialization development transition toward sustainability autonomous systems.

Language: Английский

Citations

15
Economical-environmental-technical optimal power flow solutions using a novel self-adaptive wild geese algorithm with stochastic wind and solar power DOI Creative Commons
Pavel Trojovský, Eva Trojovská, Ebrahim Akbari

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 19, 2024

Abstract This study introduces an enhanced self-adaptive wild goose algorithm (SAWGA) for solving economical-environmental-technical optimal power flow (OPF) problems in traditional and modern energy systems. Leveraging adaptive search strategies robust diversity capabilities, SAWGA distinguishes itself from classical WGA by incorporating four potent optimizers. The algorithm's application to optimize OPF model on the different IEEE 30-bus 118-bus electrical networks, featuring conventional thermal units alongside solar photovoltaic (PV) wind (WT) units, addresses rising uncertainties operating conditions, particularly with integration of renewable sources (RESs). inherent complexity exacerbated inclusion RESs like PV WT poses significant challenges. Traditional optimization algorithms struggle due problem's high complexity, susceptibility local optima, numerous continuous discrete decision parameters. study's simulation results underscore efficacy achieving solutions OPF, notably reducing overall fuel consumption costs a faster more efficient convergence. Noteworthy attributes include its remarkable capabilities optimizing various objective functions, effective management challenges, consistent outperformance compared other algorithms. method exhibits ability achieve global or nearly settings parameters, emphasizing superiority total cost reduction rapid

Language: Английский

Citations

11
The Quick Crisscross Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario based Power Systems DOI Creative Commons

Sunilkumar P. Agrawal,

Pradeep Jangir, Laith Abualigah

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103703 - 103703

Published: Dec. 1, 2024

Language: Английский

Citations

11
Giant Pacific octopus optimizer based on fitness-distance balance and natural survival method to solve time-cost-quality-labor trade-off problem in construction projects DOI
Vu Hong Son Pham, Luu Ngoc Quynh Khoi

International Journal of Management Science and Engineering Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 18

Published: Jan. 21, 2025

Language: Английский

Citations

1
The Empirical Analysis, Mathematical Modeling, and Advanced Control Strategies for Buck Converter DOI Creative Commons
Asad Ullah, Sanam Shahla Rizvi,

Amna Khatoon

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 19924 - 19941

Published: Jan. 1, 2024

The DC-DC converters are essential in power electronics as they maintain a stable output voltage even when there changes input and load current. This study introduces an advanced Proportional-Derivative (PD) compensator for buck converters. enhances stability transient responsiveness by employing unique modulation technique that has not been previously applied this context. proposed method entails applying of 28 volts, which yields amplification 15 the presence interference. small signal transfer function converter is meticulously derived, considering converter's dynamic behavior to achieve exceptional results. comprehensively explains intricate relationship between voltages, providing theoretical basis our distinctive control approach. MATLAB code accurately generates Bode diagram function. graph illustrates frequency response converter, crucial factor enhancing quality voltage. research substantiated mathematical data shown through several simulated figures, distinguishing it from conventional methodologies. implemented achieves maximum efficiency exceeding 95% with minimum ripple factor.

Language: Английский

Citations

6
Multi-algorithm based evolutionary strategy with Adaptive Mutation Mechanism for Constraint Engineering Design Problems DOI Creative Commons
Rohit Salgotra,

Sayedali Mirjalili

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 258, P. 125055 - 125055

Published: Aug. 22, 2024

This paper proposes a new multi-algorithm based evolution strategy with the addition of adaptive mutation operators for global optimization. The algorithm namely Kepler meerkat naked (KMN) is on Kepler's optimization (KOA), (MOA), and mole-rat (NMRA), as core algorithms and, grey wolf optimizer (GWO) cuckoo search (CS) inspired equations enhanced exploration exploitation. proposed uses six parametric enhancements, follows an iterative division mechanism balanced operation. A comparative analysis done respect to classical benchmarks, CEC 2014, 2017, 2019 2022 benchmark datasets performance evaluation. Six engineering design problems are also used test KMN constraint Apart from that, binary version bKMN proposed, ten feature selection Performance testing success history-based DE (SHADE), LSHADE-SPACMA, self-adaptive (SaDE), fast opposition-based learning golden jackal (FROBL-GJO), LSHADE-EpSin, jSO, EBOwithCMAR, among others. Experimental statistical results performed using Wilcoxon's Friedman's tests, it has been found that highly competitive in contrast other under study.

Language: Английский

Citations

6
Multi-objective optimal power flow of thermal-wind-solar power system using an adaptive geometry estimation based multi-objective differential evolution DOI Creative Commons

Truong Hoang Bao Huy,

Hien Thanh Doan,

Dieu Ngoc Vo

et al.

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 149, P. 110977 - 110977

Published: Oct. 28, 2023

Sustainable energy is a key component of sustainable development. The current grid can be supplied by fossil fuel generators and renewable sources (RESs)-based generators, such as solar photovoltaic (PV) wind power generators. In an electrical network, generation from several must optimally coordinated to ensure efficient economical operation. However, the intermittent uncertain nature RESs complicate operation systems. this study, adaptive geometry estimation-based multi-objective differential evolution (AGE-MODE) method proposed for optimal flow in hybrid system thermal, wind, (MOOPF-TWS). approach, PV outputs are predicted based on Weibull lognormal probability distribution functions, respectively. Therefore, costs divided into direct costs, penalty underestimation, reserve overestimation. Furthermore, emissions, voltage deviation, real loss considered particular cases. AGE-MODE applied modified IEEE 30-bus 57-bus systems, where different case studies simulated with combinations two-, three-, four-objective optimizations MOOPF-TWS problems. Comparisons between other recently developed methods demonstrate its effectiveness resolving problems, particularly cases more than two objectives.

Language: Английский

Citations

15
A Comprehensive Review on Stochastic Optimal Power Flow Problems and Solution Methodologies DOI
Ankur Maheshwari, Yog Raj Sood, Supriya Jaiswal

et al.

IETE Technical Review, Journal Year: 2023, Volume and Issue: 41(2), P. 147 - 174

Published: June 20, 2023

The deregulation of the electricity market has been accompanied by growing utilization unpredictable renewable energy sources (RESs) such as solar, wind, and hydropower plants. Additionally, advancements in storage technologies new demands have further contributed to this trend. As a result, planning operation power systems are now surrounded higher level uncertainty. In order ensure proper integrated with RESs, modern equipped specific vital tools optimal flow (OPF), which regulates generation demand achieve objectives. Hence, paper conducts comprehensive review recently published research articles focusing on various solution strategies address OPF problems presence stochastic RESs demand. encompasses diverse methodologies, objective functions, constraints, distinct techniques simulate behavior dynamic loads. explores fundamental challenges, identifies critical gaps, highlights unexplored areas pertaining system future. This is essential for operators who need assess pre-plan flexibility competency their practical cost-effective under high penetration.

Language: Английский

Citations

14
Improve coati optimization algorithm for solving constrained engineering optimization problems DOI Creative Commons
Heming Jia,

Shengzhao Shi,

Di Wu

et al.

Journal of Computational Design and Engineering, Journal Year: 2023, Volume and Issue: 10(6), P. 2223 - 2250

Published: Oct. 26, 2023

Abstract The coati optimization algorithm (COA) is a meta-heuristic proposed in 2022. It creates mathematical models according to the habits and social behaviors of coatis: (i) In group organization coatis, half coatis climb trees chase their prey away, while other wait beneath catch it (ii) Coatis avoidance predators behavior, which gives strong global exploration ability. However, over course our experiment, we uncovered opportunities for enhancing algorithm’s performance. When confronted with intricate problems, certain limitations surfaced. Much like long-nosed raccoon gradually narrowing its search range as approaches optimal solution, COA exhibited tendencies that could result reduced convergence speed risk becoming trapped local optima. this paper, propose an improved (ICOA) enhance efficiency. Through sound-based envelopment strategy, can capture more quickly accurately, allowing converge rapidly. By employing physical exertion have greater variety escape options when being chased, thereby exploratory capabilities ability Finally, lens opposition-based learning strategy added improve To validate performance ICOA, conducted tests using IEEE CEC2014 CEC2017 benchmark functions, well six engineering problems.

Language: Английский

Citations

14