Article
Green & Sustainable Science & Technology
Foday Conteh, Hiroshi Takahashi, Ashraf Mohamed Hemeida, Narayanan Krishnan, Alexey Mikhaylov, Tomonobu Senjyu
Summary: The study analyzed the techno-economic feasibility of a hybrid renewable energy system for sustainable rural electrification in a specific location in Sierra Leone, concluding that wind/PV/DG/battery is the most cost-effective, reliable, and sustainable option.
Article
Thermodynamics
Amirreza Naderipour, Amir Reza Ramtin, Aldrin Abdullah, Massoomeh Hedayati Marzbali, Saber Arabi Nowdeh, Hesam Kamyab
Summary: This paper presents an optimized stand-alone hybrid energy system composed of PV arrays, wind turbines, and battery storage with the goal of minimizing the total net present cost (TNPC) and considering interest rate changes. The improved Grasshopper Optimization Algorithm (IGOA) is used to determine optimal component sizing for the system. Results show that interest rate changes have a significant effect on system cost and reliability.
Article
Green & Sustainable Science & Technology
Daniel Sodano, Joseph F. DeCarolis, Anderson Rodrigo de Queiroz, Jeremiah X. Johnson
Summary: This study utilizes a loss of load probability model to estimate the capacity credit of solar photovoltaics and energy storage under high penetrations, finding that their synergistic effects can significantly improve system reliability by reducing daily peak demand hours and offering new insights into their potential benefits.
Article
Automation & Control Systems
Jing Bi, Haitao Yuan, Jiahui Zhai, MengChu Zhou, H. Vincent Poor
Summary: This work proposes an improved self-adaptive bat algorithm with genetic operations (SBAGO) that combines genetic algorithm (GA) and bat algorithm (BA) in a highly integrated way. SBAGO utilizes the search information of BA to perform GA's genetic operations, resulting in improved search performance. Experimental results show that SBAGO outperforms other algorithms in various metrics.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Computer Science, Interdisciplinary Applications
Xinning Li, Hu Wu, Qin Yang, Shuai Tan, Peng Xue, Xianhai Yang
Summary: The study proposed a multistrategy hybrid adaptive whale optimization algorithm (MHWOA) to address the issues with WOA. Through experiments and comparisons, it was found that MHWOA outperformed other algorithms in terms of convergence speed and optimization performance, showing promising applications.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2022)
Article
Energy & Fuels
Nilton Bispo Amado, Erick Del Bianco Pelegia, Ildo Luis Sauer
Summary: This article introduces a method to calculate the capacity value from renewable sources when the capacity of dispatchable generators in the system is variable. By abandoning the assumption of constant dispatchable capacity, this approach can be extended to incorporate other energy-limited resources into planning and operation models as reliable capacity sources.
Article
Computer Science, Interdisciplinary Applications
Mehmet S. Erdogan, Rym M'Hallah
Summary: This paper presents the real-life synchronized delivery and installation with vehicle sharing problem and proposes a mixed integer linear program and a heuristic algorithm for its solution. Extensive experimentation shows the superiority of the proposed methods in solving vehicle routing problems with time windows and the benefits of shared installation vehicles in reducing costs.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Construction & Building Technology
Pengcheng Li, Xuxiang Zhao, Dangsheng Ding, Xiwei Li, Yanjun Zhao, Lu Ke, Xiaoyue Zhang, Bin Jian
Summary: This study focused on optimizing steel trusses by using an efficient and accurate optimization methodology. Through genetic algorithms and finite element methods, both mono- and multi-parameter optimization designs were executed, and applicable optimization design methods and programs were developed. The analysis demonstrated that the proposed optimization method effectively reduced material consumption by optimizing truss height and member cross-section. Compared to the traditional trial-and-error method, the proposed optimization method offered higher calculation accuracy and better efficiency, providing a strong theoretical foundation for engineering design of steel trusses.
Article
Engineering, Industrial
Xueyan Sun, Weiming Shen, Birgit Vogel-Heuser
Summary: This paper addresses the distributed hybrid blocking flowshop scheduling problem with makespan criterion and proposes a hybrid genetic algorithm for solving it. Experimental results show that the proposed algorithm performs well on benchmarks and the local search method has a strong search capability.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Moises Silva-Munoz, Carlos Contreras-Bolton, Carlos Rey, Victor Parada
Summary: One of the fundamental problems in graph optimization is determining the maximum set of unconnected vertices, known as the maximum independent set problem. This paper presents a new artificially generated algorithm for solving this problem. The algorithm is generated using genetic programming, combining heuristics, a tabu search method, and an exact mathematical formulation to find the best computational performance among all generated algorithms.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Qaisar Abbas, Wonseok Choi, Garam Kim, Incheol Kim, Junhwan Lee
Summary: The study investigated the uplift load-carrying behavior of inclined micropiles embedded in different soil-rock conditions. The results showed that the MP's load capacity was highest when vertically installed in rock, while increasing the inclination angle resulted in decreased load capacity. Additionally, the load capacity of MPs embedded in soil-rock layers increased with the rock-embedded ratio and decreased with the inclination angle.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Energy & Fuels
Nur Atharah Kamarzaman, Shahril Irwan Sulaiman, Ahmad Ihsan Mohd Yassin, Hedzlin Zainuddin, Intan Rahayu Ibrahim
Summary: This paper presents a modified Honey Badger Algorithm (HBA) as a sizing optimization approach for an AC coupled stand-alone photovoltaic-battery system. The goal is to calculate the optimal size of system components while minimizing the Loss of Load Probability (LOLP). The results show that the modified HBA performs better in terms of achieving the lowest LOLP with relatively lower computational time compared to other meta-heuristic methods.
Article
Automation & Control Systems
S. Manikandan, M. Chinnadurai
Summary: This paper proposes a virtualized genetic algorithm to provide balanced virtual machine services in a hybrid cloud. The algorithm is implemented using a cloud simulator and compared with existing load balancing techniques using metrics such as response time, throughput, and turnaround time.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Wenlu Yang, Yinghui Zhang, Hongjun Wang, Ping Deng, Tianrui Li
Summary: Clustering ensemble has been a popular research topic, and this paper introduces a novel hybrid genetic model to solve clustering ensemble problems. By optimizing, combining, and transcending base clustering results, the proposed model maintains diversity and avoids local optima. An algorithm corresponding to the model is designed and experiments show the superiority of the proposed algorithm in integrating effective clustering.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yun Ou, Shao-Qiang Ye, Lei Ding, Kai-Qing Zhou, Azlan Mohd Zain
Summary: This paper proposes a hybrid extraction framework based on symbol rule and NN for fault diagnosis, aiming to improve the understandability of the rules. The results show that the proposed LAGA-BP method is feasible and practical in practice.
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.