Article
Thermodynamics
Fukang Ren, Ziqing Wei, Xiaoqiang Zhai
Summary: The hybridization of renewable energy and fossil energy in the energy supply system can reduce fossil energy consumption and CO2 emissions. This study evaluated two solar energy utilization systems and optimized hybrid CCHP systems using multi-objective optimization and decision-making tools, showing that system A operating under the electric load following strategy is more beneficial for three buildings.
Article
Energy & Fuels
Musik Park, Zhiyuan Wang, Lanyu Li, Xiaonan Wang
Summary: With increasing concerns over carbon dioxide emissions, the concept of Zero Energy Building (ZEB) and Electric Vehicles (EVs) have emerged to address environmental issues. This paper develops a new framework to find the optimal energy system design that meets EV charging demand and ZEB requirements, using machine learning models to predict charging demand and Genetic Algorithm and PROBID method to optimize costs and self-sufficiency ratio. The study finds that EV charging demand significantly affects energy system design, especially in small-size buildings.
Article
Construction & Building Technology
Seyed mohammad Ebrahimi Saryazdi, Alireza Etemad, Ali Shafaat, Ammar M. Bahman
Summary: This study proposes a reliable multi-objective model by integrating an Artificial Neural Network (ANN) model with Genetic Algorithm (GA) optimization method to obtain the optimal design for a typical residential Kuwaiti building. Discomfort hours and carbon emissions were selected as objective functions, and the results showed that the optimal design can substantially reduce energy consumption, discomfort hours, and carbon emission.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Badr Chegari, Mohamed Tabaa, Emmanuel Simeu, Fouad Moutaouakkil, Hicham Medromi
Summary: A new efficient multi-objective optimization method based on the BPO technique has been developed to improve indoor thermal comfort and energy performance of residential buildings in a Moroccan region. Results show significant reduction in thermal needs and improvement in indoor thermal comfort, with solutions using MOPSO showing best performance. The methodology is recommended for designers, engineers, architects, and engineering offices when considering multiple design variables and objectives.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Bo Liu, Dragan Rodriguez
Summary: This paper introduces a new simulation-based optimization technique - the Adaptive Sparrow Search Optimization Algorithm, to optimize the integrated sustainable energy systems in building design. Two objective functions are utilized to minimize the initial load demand and investment cost, while considering the minimum value limitation of renewable energy integration based on Montenegrin regulations and the constraint of householders' capability.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Thermodynamics
Matheus Soares Geraldi, Enedir Ghisi
Summary: This article proposes a method to integrate thermal satisfaction into energy benchmarking by considering energy consumption, construction aspects, climate conditions, systems, and thermal satisfaction level to assess the efficiency of buildings. The results show that buildings with low thermal satisfaction are benchmarked as less efficient.
Article
Construction & Building Technology
Maryam Talaei, Mohammadjavad Mahdavinejad, Rahman Azari, Alejandro Prieto, Hamed Sangin
Summary: The study demonstrates that a microalgae window significantly reduces building energy consumption compared with single-glazed, double-glazed, and water windows. The extent of energy savings varies with window size, algae density, and facade orientation. The proposed optimization framework helps increase the average values of energy performance metrics and daylighting metrics. Sensitivity analysis shows that window size has the highest effect on two studied performance metrics for all orientations, while algae density has minimal effect on energy consumption and no considerable effect on daylighting performance.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Energy & Fuels
David A. Agar, Paul Hansen, Magnus Rudolfsson, Bosko Blagojevic
Summary: This study applies the behavioural TOPSIS method to evaluate and rank biomass fuel pellets produced in Sweden. The study found that pellets produced from a reference spruce/pine sawdust blend are consistently ranked ahead of other pellet types in all scenarios.
Article
Operations Research & Management Science
A. Lopez-Garcia, V. Liern, B. Perez-Gladish
Summary: ESG criteria are important in investment decisions, but rating methodologies of ESG rating agencies have weaknesses in determining the relative importance of criteria. This paper proposes a MCDM approach called UW-TOPSIS that ranks firms based on their ESG global performance without the need for aggregation weights. However, it does not provide a global vector of weights for all alternatives, which is the objective of this paper.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Bingchao Zhao, Han Wang, Zhihao Huang, Qianqian Sun
Summary: This research provides an automated Multi-Criteria Decision Making (MCDM) technique with geographical information system (GIS) to solve the intricate nature of location identification and prioritization difficulty caused by the availability of numerous indicators, such as economic and environmental technical, social, and risk criteria. The F-TOPSIS outperforms the other methods with the highest performance ratio of 98.78% when compared to others.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Thermodynamics
J. Nondy, T. K. Gogoi
Summary: This study compares four different ORC configurations and finds that, under optimal conditions, the RR-ORC outperforms the other three configurations. The Regenerative and Recuperative ORCs are ranked as the second and third-best configurations. In all four configurations, the cost rate of exergy loss accounts for approximately 60% of the total system cost rate.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
G. R. Araujo, Henriqueta Teixeira, M. Gloria Gomes, A. Moret Rodrigues
Summary: This research focuses on the impact of different switching temperature ranges and thermochromic coating transmittance values on energy use in office rooms in different climates. The optimization results indicate that low transition temperatures of thermochromic glazings can lead to a 200% increase in electric lighting energy use, while the optimum solutions show a 15% improvement in total energy use compared to off-the-market thermochromic glazings.
Article
Energy & Fuels
Fang'ai Chi, Ying Xu
Summary: This study proposes a digital gene map for optimizing the design of university dormitory buildings. Utilizing a multi-objective genetic algorithm and data statistics tool, optimized solutions can be obtained to improve building performance. Through comparison studies, it is found that the optimized solutions have better performance improvements for different types of study rooms. This method is applicable to various types of university dormitories.
Article
Green & Sustainable Science & Technology
Lars Wederhake, Simon Wenninger, Christian Wiethe, Gilbert Fridgen, Dominic Stirnweiss
Summary: Energy performance certificates (EPCs) are criticized for their accuracy in benchmarking building energy performance (BEP), despite being examined by qualified auditors. Recent studies have shown that data-driven methods are more accurate in benchmarking than engineering-based methods, as they can learn from data collected by non-experts. This study presents a method that selects building variables that can be reliably collected even by occupants, and achieves 35% higher accuracy than engineering methods. The study proposes a stepwise method for designing data-driven EPCs and provides design recommendations and policy implications.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Ling Zhang, Jiaming Wu, Yan Xu, Chung-Hsing Yeh, Peng Zhou, Jianxin Fang
Summary: This paper proposes a data-driven approach to objectively evaluate the low carbon development level of cities. The approach formulates the evaluation problem as a multi-criteria decision analysis problem and combines bibliometric analysis, text mining, and optimal weighting. Case study results are used to compare the low carbon development performance of cities and make policy recommendations.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Thermodynamics
Endong Wang, Zhigang Shen, Neslihan Alp, Nate Barry
ENERGY CONVERSION AND MANAGEMENT
(2015)
Article
Thermodynamics
Endong Wang, Neslihan Alp, Jonathan Shi, Chao Wang, Xiaodong Zhang, Hong Chen
Article
Thermodynamics
Endong Wang
ENERGY CONVERSION AND MANAGEMENT
(2017)
Article
Construction & Building Technology
Endong Wang, Zhigang Shen, Kevin Grosskopf
ENERGY AND BUILDINGS
(2014)
Article
Engineering, Civil
Endong Wang, Zhigang Shen
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
(2013)
Article
Green & Sustainable Science & Technology
Endong Wang, Chris Yuan
JOURNAL OF CLEANER PRODUCTION
(2014)
Article
Green & Sustainable Science & Technology
Jingfeng Yuan, Lingzhi Li, Endong Wang, Miroslaw J. Skibniewski
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Multidisciplinary Sciences
Fanxiu Chen, Zuquan Jin, Endong Wang, Lanqin Wang, Yudan Jiang, Pengfei Guo, Xinya Gao, Xiaoyuan He
Summary: The researchers established a theoretical prediction model for the process of corrosion cracking in reinforced concrete, which can estimate the expansion force during the entire corrosion process and aid in real-time monitoring of steel corrosion in concrete structures.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Fan-xiu Chen, Yi-chen Zhong, Xin-ya Gao, Zu-quan Jin, En-dong Wang, Fei-peng Zhu, Xin-xing Shao, Xiao-yuan He
Summary: This study investigates the impact of rust expansion force due to corrosion on the durability of reinforced concrete structures by establishing a numerical model. The results show that the diameter of the steel bars and the thickness of the concrete cover can affect the magnitude of the rust expansion force.
SCIENTIFIC REPORTS
(2021)
Article
Chemistry, Multidisciplinary
Min Chen, Yu Jiang, Endong Wang, Yi Wang, Jun Zhang
Summary: This study developed a comprehensive evaluation index system for assessing urban infrastructure resilience in four Chinese cities using the PSR model. The results revealed that the resilience levels of the urban infrastructure in these cities were generally low with varying importance at different stages.
APPLIED SCIENCES-BASEL
(2022)
Article
Construction & Building Technology
Peng Mao, Xiang Wang, Rubing Wang, Endong Wang, Hongyang Li
Summary: This study conducted a questionnaire-based survey in Nanjing, China to analyze the sensitivity levels and adaptive behaviors of subway passengers towards health risks in the subway microenvironment. The results showed that older passengers and those with frequent illnesses were more sensitive to the health risks. Passengers on longer journeys and during rush hours were also more sensitive. Passengers with positive attitudes, previous environmentally influenced diseases, and knowledge related to the environment tended to demonstrate better adaptive behaviors.
Proceedings Paper
Computer Science, Artificial Intelligence
Endong Wang, Jared Forst, Neslihan Alp, Xiaoni Wang
PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON COMPUTER MODELING, SIMULATION AND ALGORITHM (CMSA 2018)
(2018)
Article
Energy & Fuels
Endong Wang
Article
Environmental Studies
Chris Yuan, Endong Wang, Qiang Zhai, Fan Yang
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
(2015)
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.
