Article
Energy & Fuels
Xizheng Zhang, Zeyu Wang, Zhangyu Lu
Summary: The hybrid modified GSA-PSO scheme is proposed to optimize the load dispatch of the microgrid containing electric vehicles, which can significantly improve the safety and economy of the grid, reduce the total cost and load variance.
Article
Multidisciplinary Sciences
Pham Vu Hong Son, Nghiep Trinh Nguyen Dang
Summary: The study introduces a hybrid multi-verse optimizer model (hDMVO) that combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to solve the discrete time-cost trade-off problem (DTCTP). The optimality of the algorithm is evaluated using 23 benchmark test functions, demonstrating its competitiveness with other algorithms. The performance of hDMVO is further evaluated using four benchmark test problems, showing its superiority in time-cost optimization for large-scale and complex projects compared to previous algorithms.
SCIENTIFIC REPORTS
(2023)
Article
Mathematics
Mokhtar Said, Ali M. El-Rifaie, Mohamed A. Tolba, Essam H. Houssein, Sanchari Deb
Summary: Economic Load Dispatch is a critical issue in power engineering, aiming to minimize production costs and reduce emissions. The Chameleon Swarm Algorithm showed promising performance in addressing this problem.
Article
Computer Science, Artificial Intelligence
Qisong Song, Liya Yu, Shaobo Li, Naohiko Hanajima, Xingxing Zhang, Ruiqiang Pu
Summary: In this study, particle swarm optimization (PSO) algorithm and ant colony optimization (ACO) algorithm were optimized to improve the comprehensive performance of energy dispatching between different sites. A new improved PSO-ACO algorithm was proposed based on hybrid algorithm to address the issue of poor energy dispatching efficiency between sites. The algorithm introduced multiobjective performance indicators, vitality factor, transformation of PSO routes into ant colony enhancement pheromone, angle guidance function, and high-quality pheromone update rule to enhance the optimization capability and convergence speed. Simulation experiments were conducted to compare the algorithm with other methods, and the results demonstrated that the improved PSO-ACO algorithm achieved shorter routes, lower time consumption, and higher security in energy dispatching optimization.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Bin Li, Ziping Wei, Jingjing Wu, Shuai Yu, Tian Zhang, Chunli Zhu, Dezhi Zheng, Weisi Guo, Chenglin Zhao, Jun Zhang
Summary: Evolutionary computation has achieved impressive results in solving complex problems, but there is no theoretical guarantee for reaching the global optimum. To address this challenge, researchers have proposed an evolutionary computation framework called EVOLER, aided by machine learning, which enables theoretically guaranteed global optimization of complex non-convex problems. This is achieved by learning a low-rank representation of the problem and exploring a small attention subspace using evolutionary computation methods to reliably avoid local optima.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Multidisciplinary Sciences
Mohammad Amin Akbari, Mohsen Zare, Rasoul Azizipanah-abarghooee, Seyedali Mirjalili, Mohamed Deriche
Summary: Motivated by cheetah hunting strategies, this paper proposes a nature-inspired algorithm called the cheetah optimizer (CO), which is shown to outperform other algorithms in extensive testing on benchmark functions and engineering problems.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Ijaz Ahmed, Um-E-Habiba Alvi, Abdul Basit, Tayyaba Khursheed, Alwena Alvi, Keum-Shik Hong, Muhammad Rehan
Summary: In this paper, a novel soft computing optimization technique is proposed for solving the dynamic economic dispatch problem (DEDP) of complex non-convex machines with several constraints. The proposed hybrid method GA-SQP converges to achieve the best optimal solution in a confined environment in a limited number of simulations, demonstrating applicability and adequacy over conventional methods.
Article
Thermodynamics
Wenqiang Yang, Xinxin Zhu, Qinge Xiao, Zhile Yang
Summary: This paper proposes an improved version of the multi-objective marine predator algorithm (IMOMPA) for solving the optimization of multi-objective dynamic economic-grid fluctuation dispatch (MODEGD). The IMOMPA algorithm improves population diversity, convergence speed, and global search ability. Numerical experiments on benchmark functions and generation units demonstrate the superiority of the IMOMPA algorithm, and plug-in electric vehicles (PEVs) connected to the grid (V2G) can help mitigate grid fluctuations.
Review
Computer Science, Interdisciplinary Applications
Simrandeep Singh, Nitin Mittal, Diksha Thakur, Harbinder Singh, Diego Oliva, Anton Demin
Summary: Image processing is a significant area of growth in the current scenario, with segmentation being a key step, where multilevel thresholding methods play an important role, and various optimization techniques can enhance the performance of image processing.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Tzu-Ching Tai, Chen-Cheng Lee, Cheng-Chien Kuo
Summary: This paper proposes a new hybrid algorithm called RLGWO to solve the large-scale economic load dispatch (ELD) problem. The algorithm imitates the hunting behavior and social hierarchy of grey wolves and is reinforced by robust tolerance-based adjust searching direction and opposite-based learning. The simulation results show that RLGWO outperforms previous algorithms in terms of fuel cost and computational efficiency.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Subhamay Basu, Mousumi Basu
Summary: This manuscript introduces a modified student psychology-based optimization (MSPBO) algorithm for the convoluted economic dispatch problem. Simulation results demonstrate that the suggested MSPBO algorithm is capable of delivering better outcomes.
APPLIED ARTIFICIAL INTELLIGENCE
(2021)
Article
Energy & Fuels
Mostafa Mojtahedzadeh Larijani, Mehrdad Ahmadi Kamarposhti, Tohid Nouri
Summary: In this paper, a new hybrid multiobjective algorithm, namely, the modified bald eagle search Algorithm (MBES), integrated with the grasshopper optimization algorithm, is proposed to solve the unit commitment (UC) problem. The UC problem is tackled under uncertainties related to demand and renewable generation capacities, and two innovative objective functions based on operation cost and emissions are introduced. Our findings demonstrate that the proposed MOGOA-MBES algorithm outperforms other algorithms in terms of reducing operation cost and emissions, and the inclusion of flexible loads can effectively mitigate cost and emission levels.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Whei-Min Lin, Chung-Yuen Yang, Ming-Tang Tsai, Yun-Hai Wang
Summary: This study proposes a method combining DPSO and SQP for solving unit commitment problems for ancillary services, with effective results demonstrated using real data. The research shows that costs with ancillary services are lower than those without ancillary services.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Jia-Jia Jiang, Wen-Xue Wei, Wan-Lu Shao, Yu-Feng Liang, Yuan-Yuan Qu
Summary: A large-scale bi-level particle swarm optimization algorithm is proposed in this paper, which addresses the slow convergence and local optimum issues of particle swarm optimization by enlarging the scale and enhancing the diversity of the initial population. The algorithm improves running efficiency by using the structural advantages of bi-level particle swarms.
Article
Computer Science, Artificial Intelligence
Hong Wang, Yikun Ou, Yixin Wang, Tongtong Xing, Lijing Tan
Summary: A semi-supervised bacterial heuristic feature selection algorithm is proposed to address high-dimensional and label-missing problems. The algorithm utilizes a k-nearest neighbor semi-supervised learning strategy to reconstruct missing labels and improves the bacterial heuristic algorithm using population initialization, dynamic learning, and elite population evolution strategies. Experimental results demonstrate its advantages in terms of classification accuracy and selected feature numbers.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Thermodynamics
Pengcheng Zhao, Jingang Wang, Liming Sun, Yun Li, Haiting Xia, Wei He
Summary: The production of green hydrogen through water electrolysis is crucial for renewable energy utilization and decarbonization. This research explores the optimal electrode configuration and system design of compactly-assembled industrial electrolyzer. The findings provide valuable insights for industrial application of water electrolysis equipment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
V. Baiju, P. Abhishek, S. Harikrishnan
Summary: Thermally driven adsorption desalination systems (ADS) have gained attention as an eco-friendly solution for water scarcity. However, they face challenges related to low water productivity and scalability. To overcome these challenges, integrating ADS with other desalination technologies can create a small-scale hybrid system. This study proposes integrating ADS with a Thermo Electric Dehumidification (TED) unit to enhance its performance.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
C. X. He, Y. H. Liu, X. Y. Huang, S. B. Wan, Q. Chen, J. Sun, T. S. Zhao
Summary: A decentralized centroid multi-path RC network model is constructed to improve the temperature prediction accuracy compared to traditional RC models. By incorporating multiple heat flow paths and decentralizing thermal capacity, a more accurate prediction is achieved.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chaoying Li, Meng Wang, Nana Li, Di Gu, Chao Yan, Dandan Yuan, Hong Jiang, Baohui Wang, Xirui Wang
Summary: There is an urgent need to shift away from heavy dependence on fossil fuels and embrace renewable energy sources, particularly in the energy-intensive oil refining process. This study presents an innovative concept called the Solar Oil Refinery, which applies solar energy in oil refining. A solar multi-energies-driven hybrid chemical oil refining system that utilizes solar pyrolysis and electrolysis has been developed, significantly improving solar utilization efficiency, cracking rate, and hydrogen yield.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chao Ma, Guanghui Wang, Dingbiao Wang, Xu Peng, Yushen Yang, Xinxin Liu, Chongrui Yang, Jiaheng Chen
Summary: This study proposes a bio-inspired fish-tail wind rotor to improve the wind power efficiency of the traditional Savonius rotor. Through transient simulations and orthogonal experiments, the key factors affecting the performance are identified. A response surface model is constructed to optimize the power coefficient, resulting in an improvement of 9.4% and 6.6% compared to the Savonius rotor.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sina Bahmanziari, Abbas-Ali Zamani
Summary: This paper proposes a new framework for improving electrical energy harvesting from piezoelectric smart tiles through a combination of magnetic plucking, mechanical impact, and mechanical vibration force mechanisms. Experimental results demonstrate a significant increase in energy yield and average energy harvesting time compared to other mechanisms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Nanjiang Dong, Tao Zhang, Rui Wang
Summary: This study establishes a multiobjective mixed-variable configuration optimization model for a comprehensive combined cooling, heating, and power energy system, and proposes an efficient generating operator to optimize this model. The experimental results show that the proposed algorithm performs better than other state-of-the-art algorithms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Ahmed E. Mansy, Eman A. El Desouky, Tarek H. Taha, M. A. Abu-Saied, Hamada El-Gendi, Ranya A. Amer, Zhen-Yu Tian
Summary: This study aims to convert office paper waste into bioethanol through a sustainable pathway. The results show that physiochemical and enzymatic hydrolysis of the waste can yield a high glucose concentration. The optimal conditions were determined using the Box-Behnken design, and a blended membrane was used for ethanol purification.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sven Klute, Marcus Budt, Mathias van Beek, Christian Doetsch
Summary: Heat pumps are crucial for decarbonizing heat supply, and steam generating heat pumps have the potential to decarbonize the industrial sector. This paper presents the current state, technical and economic data, and modeling principles of steam generating heat pumps.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Le Zhang, To-Hung Tsui, Yen Wah Tong, Pruk Aggarangsi, Ronghou Liu
Summary: This study investigates the effectiveness of a current-carrying-coil-based magnetic field in promoting anaerobic digestion of chicken manure. The results show that the applied magnetic field increases methane yield, decreases carbon dioxide production, and reduces the concentration of ammonia nitrogen. Microbial community analysis reveals the enrichment of certain methanogenic genera and enhanced metabolic pathways. Pilot-scale experiments confirm the technical effectiveness of the magnetic field assistance in enhancing anaerobic digestion of chicken manure.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Bo Chen, Ruiqing Ma, Yang Zhou, Rui Ma, Wentao Jiang, Fan Yang
Summary: This paper presents an advanced energy management strategy for fuel cell hybrid electric heavy-duty vehicles, focusing on speed planning and energy allocation. By utilizing predictive co-optimization control, this strategy ensures safe inter-vehicle distance and minimizes energy demand. Simulation results demonstrate the effectiveness of the proposed method in reducing fuel cell degradation cost and overall operation cost.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Fabio Fatigati, Roberto Cipollone
Summary: Organic Rankine Cycle-based microcogeneration systems that use solar sources to generate electricity and hot water can help reduce CO2 emissions in residential energy-intensive sectors. The adoption of a recuperative heat exchanger in these systems improves efficiency, reduces thermal power requirements, and saves on electricity costs.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Lipeng He, Renwen Liu, Xuejin Liu, Xiaotian Zheng, Limin Zhang, Jieqiong Lin
Summary: This research proposes a piezoelectric-electromagnetic hybrid energy harvester (PEHEH) for low-frequency wave motion and self-sensing wave environment monitoring. The PEHEH shows promising power output and the ability to self-power and self-sense the wave environment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Shangling Chu, Yang Liu, Zipeng Xu, Heng Zhang, Haiping Chen, Dan Gao
Summary: This paper studies a distributed energy system integrated with solar and natural gas, analyzes the impact of different parameters on its energy utilization and emissions reduction, and obtains the optimal solution through an optimization algorithm. The results show that compared to traditional separation production systems, this integrated system achieves higher energy utilization and greater reduction in carbon emissions.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Qingpu Li, Yaqi Ding, Guangming Chen, Yongmei Xuan, Neng Gao, Nian Li, Xinyue Hao
Summary: This paper proposes and studies a piston-type thermally-driven pump with a structure similar to a linear compressor, aiming to eliminate the high-quality energy consumption of existing pumps and replace mechanical pumps. The coupling mechanism of working fluid flow and element dimension is analyzed based on force analysis, and experimental data analysis is used to determine the pump operation stroke. Theoretical simulation is conducted to analyze the correlation mechanism of the piston assembly. The research shows that the thermally-driven pump can greatly reduce power consumption and has potential for industrial applications.
ENERGY CONVERSION AND MANAGEMENT
(2024)