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Multi-Objective Optimization Strategy for Wind-Photovoltaic-Pumped Storage Combined System Based on Gray Wolf Algorithm
Published 2024-10-01“…Direct grid connection will lead to a lower power generation income of the power station, a greater volatility of grid connection of electric energy, and more wind and photovoltaic power discards, resulting in lower carbon emission reductions. …”
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Design of Constant Modulus Radar Waveform for PSD Matching Based on MM Algorithm
Published 2025-06-01“…In this paper, based on the majorization–minimization (MM) framework, a novel algorithm is proposed to solve this problem. The proposed algorithm can be proved to converge to the stationary point, and the error reduction property can be obtained without the unitary requirements on the discrete Fourier transform (DFT) matrix. …”
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Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance
Published 2025-07-01“…The formulated multi-objective function incorporates real power loss (RPL) minimization, voltage deviation index (VDI) reduction, and voltage stability index (VSI) enhancement, employing a weighted sum approach (WSA) to ensure computational rigor. …”
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The quick crisscross sine cosine algorithm for optimal FACTS placement in uncertain wind integrated scenario based power systems
Published 2025-03-01“…Evaluated on the IEEE 30-bus test system under fixed and dynamic loading conditions, QCSCA outperformed various SCA variants, consistently minimizing generation costs, power losses, and gross costs. For instance, in Case 4, QCSCA achieved a gross cost reduction of 515.2580 $/h, outperforming competing algorithms by up to 1.29 %, while also achieving significant power loss reduction across multiple scenarios. …”
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Enhancing Reactive Power Compensation in Distribution Systems through Optimal Integration of D-STATCOM using the Pelican Optimization Algorithm
Published 2025-03-01“…Furthermore, a comparative analysis against recent methods from the literature highlights the superior efficacy of the POA algorithm, revealing reductions of 29.15% and 32.00% in active power losses for the IEEE 33-bus and IEEE 69-bus systems. …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency
Published 2025-06-01“…Performance evaluation verifies that the proposed scheme results in up to 60% of power savings, a reduction of up to 6.7 dB in PAPR, and a 2–5 dB SNR improvement while maintaining BER and power spectral density (PSD) performance. …”
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A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems
Published 2025-05-01“…The QOFBI algorithm achieves a 94.44% reduction in active power loss, highlighting its robust performance across different operational scenarios. …”
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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm
Published 2025-06-01“…It achieves over 60 % reduction in RMSE voltage drop and significantly improves the power factor to an average of 0.92. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm
Published 2025-08-01“…In this study, MRDMGWOA is simulated on the IEEE 39 system and 118 system, and its performance is compared with other heuristic algorithms. The results show that: (1) in the IEEE 39 system, MRDMGWOA reduces the power generation cost and CO<sub>2</sub> emission by 17% and 22%, respectively, and reduces the computation time by 16.14 s compared with the centralized optimization; (2) in the IEEE 118 system, the two metrics are further optimized, with a 20% and 17% reduction in the cost and emission, respectively, and an improvement in the computational efficiency by 45.46 s; (3) in the spacing, hypervolume, and Euclidian metrics evaluation, MRDMGWOA outperforms other algorithms; (4) compared with the existing DMOGWO and DMOMFO, the computation time of MRDMGWOA is reduced by 177.49 s and 124.15 s, respectively, and the scheduling scheme obtained by MRDMGWOA is more optimal than DMOGWO and DMOMFO.…”
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Revolutionizing Cardiac Risk Assessment: AI-Powered Patient Segmentation Using Advanced Machine Learning Techniques
Published 2025-05-01“…This study combines Artificial Intelligence (AI) techniques—specifically the k-means clustering algorithm—alongside dimensionality reduction methods like Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) to identify patient groups with varying levels of heart attack risk. …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions
Published 2025-05-01“…To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. Additionally, the Whale Optimization Algorithm is adopted to efficiently optimize the hyperparameters of iTransformer for the framework, improving parameter adaptability and convergence efficiency. …”
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Container Liner Shipping System Design Considering Methanol-Powered Vessels
Published 2025-04-01Get full text
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Fault Localization in Digital Power Distribution Networks Using a Chaotic Binary Particle Swarm Optimization–Enhanced Matrix Algorithm
Published 2024-01-01“…As digital distribution networks grow in complexity, ensuring efficient fault localization has become critical for reliable power delivery. This paper introduces a novel fault localization method that synergistically combines a matrix algorithm with a chaotic binary particle swarm optimization (CBPSO) algorithm. …”
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Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm
Published 2025-05-01Get full text
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Customer active power consumption prediction for the next day based on historical profile
Published 2022-06-01“…Logistic Regression Algorithm is used to determine the most probable nodes for the next 25 hours in case of residential or industrial customers.…”
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