Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Sustainability, Journal Year: 2023, Volume and Issue: 15(12), P. 9434 - 9434

Published: June 12, 2023

Metaheuristic optimization algorithms are tools based on mathematical concepts that used to solve complicated issues. These intended locate or develop a sufficiently good solution an issue, particularly when information is sparse inaccurate computer capability restricted. Power systems play crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics optimize the performance of modern power attractive topic. This research paper investigates applicability several metaheuristic system challenges. Firstly, this reviews fundamental algorithms. Then, six problems regarding presented discussed. optimizing flow transmission distribution networks, reactive dispatching, combined economic emission optimal Volt/Var controlling systems, size placement DGs. A list The relevant results approved ability algorithm effectively. This, particular, explains their wide deployment field.

Language: Английский

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Photovoltaic Modeling: A Comprehensive Analysis of the I–V Characteristic Curve

Sustainability, Journal Year: 2024, Volume and Issue: 16(1), P. 432 - 432

Published: Jan. 3, 2024

The I–V curve serves as an effective representation of the inherent nonlinear characteristics describing typical photovoltaic (PV) panels, which are essential for achieving sustainable energy systems. Over years, several PV models have been proposed in literature to achieve simplified and accurate reconstruction characteristic curves specified manufacturer’s datasheets. Based on their derivation, can be classified into three distinct categories: circuit-based, analytical-based, empirical-based models. However, extensive analysis accuracy reconstructed different at maximum power point (MPP) has not conducted time writing this paper. IEC EN 50530 standard stipulates that absolute errors within vicinity MPP should always less than or equal 1%. Therefore, review paper conducts in-depth reconstructing panels. limitations existing were identified based simulation results obtained using MATLAB performance indices. Additionally, also provides suggestions future research directions.

Language: Английский

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An integrative TLBO-driven hybrid grey wolf optimizer for the efficient resolution of multi-dimensional, nonlinear engineering problems

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

Published: April 2, 2025

Language: Английский

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Enhanced Artificial Rabbits Algorithm Integrating Equilibrium Pool to Support PV Power Estimation via Module Parameter Identification

International Journal of Energy Research, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

This paper proposes a novel innovative version of enhanced artificial rabbit optimization (EARO) algorithm integrating an equilibrium pool (EP) that consists the best solutions. Furthermore, detour foraging and hiding mechanisms are modified to amplify search capability. These modifications enable dynamically focus on exploring various randomized directions emanating from EP. The proposed EARO is designed investigate PV module characteristics identification issue. To obtain nine parameters triple diode model (TDM) while taking into account three distinct real‐world modules, utilized evaluated in comparison with standard ARO. tested different modules: Ultra 85‐P panel, PVM_752GaAs, RTC France. results corresponding compared respect several published latest studies. simulation show shows significant overall improvement rates for each modules. A validation common SDM DDM France assessed which illustrates superiority robustness over recent results.

Language: Английский

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Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 77903 - 77931

Published: Jan. 1, 2024

Lithium-ion (Li-ion) batteries are being used in electric vehicles to reduce the reliance on fossil fuels due their high energy density, design flexibility, and efficiency compared other battery technologies. However, they undergo complex nonlinear degradation performance declines when abused, making reliability crucial for effective vehicle performance. This survey paper presents a comprehensive review of state-of-the-art assessments vehicles. First, operating principle Li-ion batteries, patterns, models briefly discussed. Afterwards, detailed qualitative quantitative approaches. The approach encompasses failure modes mechanisms effects analysis, X-ray computed tomography, scanning electron microscopy. In contrast, approaches involve multiphysics modelling, electrochemical impedance spectroscopy, incremental capacity differential voltage machine learning, transfer learning. Each technique is examined terms its principles, advantages, limitations, applicability Comparative analysis reveals that methods primarily early stages assess potential risks post-mortem laboratory, while techniques such as learning offer real-time prognostic health management anomaly prevention. Also, tend be more cost-effective counterparts. consolidating through standardization testing protocols, real-world data integration, controller area network use, policy regulation highlighted guide further research.

Language: Английский

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An efficient, fast, and robust algorithm for single diode model parameters estimation of photovoltaic solar cells

IET Renewable Power Generation, Journal Year: 2024, Volume and Issue: 18(5), P. 863 - 874

Published: Feb. 9, 2024

Abstract Parameter estimation of photovoltaic (PV) solar cells and module models pays attention to researchers owing their importance in practical considerations. The single diode model (SDM) circuit with five unknown parameters is widely used PV modules. In this paper, a novel approach called alternate optimization (AO) algorithm based on discrete search proposed estimate the SDM parameters. provides efficient robust performance, considering limited set values increasing convergence speed. Two case studies actual measurements are considered assess AO algorithm: RTC France cell monocrystalline modules different irradiations temperatures. numerical findings underscore superior performance across various metrics. Notably, it achieves an exceptional Root Mean Square Error (RMSE) 7.7426 × 10 −04 for approximately 1 −03 RMSE Additionally, exhibits unparalleled speed, showcasing fastest elapsed time 1.66 −05 —markedly 4.45 times quicker than method documented literature parameter estimation. Furthermore, stands out its efficiency, requiring maximum iterations estimation, substantial improvement compared more typically needed by algorithms existing literature. Its robustness also commendable, as evidenced stability final variety experiments, distinguishing from less found

Language: Английский

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Improved stochastic fractal search algorithm involving design operators for solving parameter extraction problems in real-world engineering optimization problems

Applied Energy, Journal Year: 2024, Volume and Issue: 365, P. 123297 - 123297

Published: April 27, 2024

Language: Английский

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Optimal system design for grid energy system using RRAP with MayFly optimization algorithm

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 139 - 161

Published: Jan. 1, 2025

Language: Английский

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Photovoltaic Farm Production Forecasting: Modified Metaheuristic Optimized Long Short-Term Memory Based Networks Approach

IEEE Access, Journal Year: 2025, Volume and Issue: 13, P. 25198 - 25222

Published: Jan. 1, 2025

Language: Английский

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Fully Informed Search Algorithm for Estimating the Parameters of Li-Ion Battery Model under UDDS Drive Cycle Profile

Transportation research procedia, Journal Year: 2025, Volume and Issue: 84, P. 275 - 282

Published: Jan. 1, 2025

Language: Английский

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