Article
Energy & Fuels
Young-Su Kim, A-Rong Kim, Sung-Ju Tark
Summary: This paper proposes a new method for manufacturing efficient BIPV modules that meet aesthetic requirements. By using additive manufacturing, an optical pattern is created to maximize sunlight reaching the solar cells and hide them beneath the pattern. The optimized optical pattern is used to fabricate PV modules. The color BIPV technology is expected to expand the market and reduce carbon emissions.
Review
Construction & Building Technology
Nuria Martin-Chivelet, Konstantinos Kapsis, Helen Rose Wilson, Veronique Delisle, Rebecca Yang, Lorenzo Olivieri, Jesus Polo, Johannes Eisenlohr, Benjamin Roy, Laura Maturi, Gaute Otnes, Mattia Dallapiccola, W. M. Pabasara Upalakshi Wijeratne
Summary: This paper reviews the energy-related features of building-integrated photovoltaic (BIPV) modules and systems, including thermal, solar, optical, and electrical aspects. Further standardization is needed to evaluate the heat transfer and solar heat gain of BIPV modules. The optical properties of BIPV modules play a role in balancing energy saving, electricity generation, aesthetics, and visual comfort. Architecturally adapted BIPV design may reduce the efficiency of modules and systems compared to standard photovoltaic ones. Special operating conditions of BIPV systems complicate electrical design and performance forecasting.
ENERGY AND BUILDINGS
(2022)
Article
Energy & Fuels
L. Serrano-Lujan, C. Toledo, J. M. Colmenar, J. Abad, A. Urbina
Summary: This article presents an artificial intelligence-based approach for predicting the temperature of a photovoltaic module by considering both indoor and outdoor environmental factors. The results demonstrate the high accuracy of this method under different weather conditions.
Review
Construction & Building Technology
Tilmann E. Kuhn, Christof Erban, Martin Heinrich, Johannes Eisenlohr, Frank Ensslen, Dirk Holger Neuhaus
Summary: This paper reviews and analyzes the available technological design options for BIPV systems on roofs and facades, providing energy for decarbonization of the energy systems and analyzing the German BIPV market. It presents detailed analysis of design options for BIPV modules, focusing on PV cell design and color application, as well as options for constructional integration of BIPV modules in buildings.
ENERGY AND BUILDINGS
(2021)
Article
Energy & Fuels
Alba Ramos, Joaquim Romani, Jaume Salom
Summary: Building integrated photovoltaics (BIPV) is a promising technology for reducing building energy demand and CO2 emissions, especially in the refurbishment of old high-rise office buildings. A simulation study on a Spanish office building showed that BIPV can significantly decrease energy demand and improve daylighting conditions. Economic analysis also demonstrated the importance of electricity pricing schedules in promoting BIPV.
Review
Green & Sustainable Science & Technology
Guoqing Yu, Hongxing Yang, Daina Luo, Xu Cheng, Mark Kyeredey Ansah
Summary: BIPV windows integrate solar cells within window glazing, reducing building energy consumption and providing superior thermal insulation and electricity generation performance compared to traditional windows.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Ya Brigitte Assoa, Philippe Thony, Paul Messaoudi, Emmanuel Schmitt, Olivier Bizzini, Stephane Gelibert, Didier Therme, Julie Rudy, Fabien Chabuel
Summary: The study validated the mid-term performance of building integrated bifacial photovoltaic modules in real conditions, showing expected results. A significant thermal gradient along the facade was observed in warm season, while the innovative facade achieved a significant reduction in energy consumption compared to reference in winter.
Article
Construction & Building Technology
Pegah Hoseinzadeh, Morteza Khalaji Assadi, Shahin Heidari, Mohammad Khalatbari, R. Saidur, Kiana Haghighat Nejad, Hamed Sangin
Summary: This research focuses on designing a high-rise office building with BIPV system to reduce energy consumption, providing at least 20% of the monthly lighting electricity demand and decreasing thermal energy consumption.
ENERGY AND BUILDINGS
(2021)
Article
Environmental Sciences
Swagata Sarkar, Alagar Karthick, Venkatachalam Kumar Chinnaiyan, Pravin P. P. Patil
Summary: This study proposes a hybrid approach based on random forest (RF) and long short-term memory (LSTM) using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to estimate future energy forecast. The raw energy usage data is translated into multiple components using CEEMDAN. The component with the most significant frequency is predicted using RF, while the other components are forecasted using hybrid LSTM. The predictions from all components are then combined to form the final result. Experimental results show that the suggested strategy outperforms the reference methods.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Construction & Building Technology
Mo Chen, Wei Zhang, Lingzhi Xie, Bo He, Wei Wang, Jianhui Li, Zihao Li
Summary: The study investigated the electricity generation improvement of bifacial PV modules as building envelope and identified key factors influencing their power generation performance through experiments and simulations. It was found that increasing the reflectivity of the inner surface can enhance the electricity generation efficiency of bifacial PV modules.
ENERGY AND BUILDINGS
(2021)
Review
Energy & Fuels
Joaquim Romani, Alba Ramos, Jaume Salom
Summary: Building-integrated photovoltaics (BIPV) have attracted interest for their capacity to provide renewable power generation for buildings. Transparent and semi-transparent BIPV systems, which offer advantages in terms of daylighting and solar radiation control, have gained increasing attention in the past two decades. However, evaluating the performance of these systems involves complex considerations of optical, thermal, electrical, and daylighting factors.
Article
Energy & Fuels
N. J. Bodele, P. S. Kulkarni
Summary: Due to the focus on energy savings and eco-friendliness, solar PV-based DC Nano-grids are gaining popularity for residential and commercial buildings. However, solar photovoltaic systems are intermittent and unreliable due to external factors and power degradation. To address these issues, this paper proposes a bidirectional modular PV battery system (BMPBS) that utilizes non-isolated buck and boost converters. The BMPBS can handle losses and intermittency in SPV with the help of a battery storage system, making the overall SPV system reliable.
Article
Thermodynamics
C. John De Britto, S. Nagarajan, R. Senthil Kumar
Summary: This manuscript focuses on the energy storage technology with renewable energy design, which can directly reduce the overall constraint of electrical microgrid in the future. By targeting the entire site for essential energy storage systems based on predefined functions, the original energy monitoring arrangement can lower the typical cost of microgrids and increase the utilization of renewable assets. The concept of hybrid integrated microgrids combining solar PV, wind turbines, and nickel-cadmium battery storage is fundamental for modeling and calculation.
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Nuria Martin-Chivelet, Jesus Polo, Carlos Sanz-Saiz, Lucy Tamara Nunez Benitez, Miguel Alonso-Abella, Jose Cuenca
Summary: This paper assesses the suitability of two steady-state photovoltaic module temperature models (Ross and Faiman) for building integrated photovoltaic rainscreens and curtain walls. The study shows that the Ross model is the most suitable for predicting annual PV energy output in these applications, highlighting the importance of fitting model coefficients with representative in situ data.
Article
Engineering, Electrical & Electronic
Cheng Wang, He Peng, Liqun He, Lei Li, Yaosuo Xue
Summary: This article presents a coupled-DC power module-based cascaded multilevel converter for integrating utility-scale photovoltaic (PV) generations. The system provides more flexible power routes through coupling different DC-links, enlarging the operating range and considering active power mismatches. Simulation and experimental results demonstrate that the proposed system can handle module mismatches, improve solar power utilization and system efficiency.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Hongsheng Hu, Tao Cai, Shanxu Duan, Xiaoming Zhang, Jintao Niu, Hao Feng
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2020)
Article
Energy & Fuels
Jianxun Lang, Xiaosheng Peng, Wenze Li, Tao Cai, Zhenhao Gan, Shanxun Duan, Chaoshun Li
Summary: A novel two-stage short-term wind power interval prediction method is proposed in this study, which uses the minimal gated memory network and improved interval width adaptive adjustment strategy for prediction. Experimental results demonstrate that the proposed model can obtain suitable wind power intervals with high confidence and quality.
Article
Dermatology
Tao Cai, Lei Zhang, Kunpeng Zhu, Jianping Hu, Taichen Zhan, Liwei Liu, Cheng Li, Chunlin Zhang
Summary: The study demonstrates that the application of NPWT with VSD material in patients undergoing pelvic reconstruction after malignant bone tumor resection can effectively prevent infection, reduce the duration of antibiotic administration and inpatient stay, and improve wound healing rates compared to conventional treatment.
ADVANCES IN SKIN & WOUND CARE
(2021)
Article
Energy & Fuels
Xiaosheng Peng, Kai Cheng, Jianxun Lang, Zuowei Zhang, Tao Cai, Shanxu Duan
Summary: A short-term WPP model based on SFFS feature selection and BLSTM deep learning is proposed in this study, which effectively selects core features and improves prediction accuracy, while reducing phase errors of WPP.
Article
Thermodynamics
Xiaosheng Peng, Hongyu Wang, Jianxun Lang, Wenze Li, Qiyou Xu, Zuowei Zhang, Tao Cai, Shanxu Duan, Fangjie Liu, Chaoshun Li
Summary: The study developed a new neural-network prediction model called EALSTM-QR considering NWP input and deep learning methods, showing good accuracy and reliability for wind-power interval and probability prediction. The model utilizes Encoder, Attention, bidirectional LSTM, and quantile regression levels to generate wind-power time-series probability prediction results and obtain final prediction intervals.
Article
Energy & Fuels
Cai Tao, Junjie Lu, Jianxun Lang, Xiaosheng Peng, Kai Cheng, Shanxu Duan
Summary: In this paper, a hybrid model that considers both accuracy and efficiency is proposed for predicting photovoltaic power generation. Improved feature selection and a bias compensation-long short-term memory network are used to enhance prediction accuracy and efficiency. Experimental results show significant improvements compared to traditional methods.
Article
Automation & Control Systems
Xiufeng Zhang, Gang Wang, Tao Cai, Jian Sun
Summary: This paper investigates the identification of the interaction geometry of a set of agents aiming to achieve consensus. By classifying agents into subsets and introducing input and output agents, a relationship between the transfer function matrix and parameter identifiability is established, with solutions proposed for two specific cases.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Hongsheng Hu, Shanxu Duan, Tao Cai, Pingkang Zheng
Summary: This study addresses the current unbalance issue among multiple branches in an inductive power transfer system, and proposes a current-sharing compensation method with specially designed capacitors to suppress the current unbalance. The feasibility of this method is verified through experiments, achieving equal distribution of currents and temperatures among multiple branches at different power levels.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Medicine, General & Internal
Tao Cai, Lianghui Zhao, Ling Kong, Xianli Du
Summary: During the COVID-19 pandemic, the decline in outdoor activities and increase in exposure time to digital screens accelerated myopia progression by approximately one-third. Risk factors for myopia progression included heredity, prolonged indoor work, and electronic device usage, while protective factors included age, rest time after continuous eye usage, sleep duration, and distance from the eyes to computer screens.
FRONTIERS IN MEDICINE
(2022)
Article
Engineering, Electrical & Electronic
Han Fu, Qikang Wei, Hao Fu, Bangyin Liu, Shanxu Duan
Summary: This paper analyzes a fault-tolerant strategy for multiphase interleaved inverters based on a short-circuiting coupled inductor. By establishing an equivalent magnetic circuit model and calculating the windings open-circuit voltage, short-circuit current, and circulation current, it can guide the engineering design and application.
JOURNAL OF POWER ELECTRONICS
(2023)
Article
Engineering, Multidisciplinary
Yadong Wang, Wencheng Zhao, Bangyin Liu, Wanjing Li
Summary: This article proposes an optimized design method for the dc transformer based on CLLC resonant converter, which minimizes conduction losses while achieving zero voltage switching. Parametric design and deadtime selection principles are derived based on the time-domain models, and the corresponding design method and procedure are developed.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Shabnam Mohammadshahi, Hadi Samsam-Khayani, Binqi Chen, Tao Cai, Kyung Chun Kim
Summary: This article explores a cost-effective two-dimensional temperature measurement method based on the lifetime technique, which utilizes thermographic phosphor materials to measure surface temperatures. The study analyzes different phosphor-coated samples to study emitted light intensity and temperatures at discrete points. Additionally, a high-speed camera is used to measure surface temperature distributions to ensure coating stability for temperature sensing applications.
JOURNAL OF VISUALIZATION
(2023)
Article
Computer Science, Information Systems
Zhaocheng Zhang, Tao Cai, Aote Yuan
Summary: This study proposes a SOC estimation method for batteries based on VMD technique and TCN model. The voltage values are decomposed into different frequency domains using time-frequency analysis, and the features obtained from VMD technique are used as input for the TCN model. Experimental results show that the proposed method outperforms existing methods in terms of mean absolute error and root mean square error, and the error between the estimated and actual values is bounded by 2%.
IET CYBER-PHYSICAL SYSTEMS: THEORY & APPLICATIONS
(2023)
Letter
Dermatology
Ping Wang, Jian-Xia Xiong, Ai-Jun Chen, Tao Cai
ANNALS OF DERMATOLOGY
(2022)
Article
Computer Science, Information Systems
Xiaosheng Peng, Qiyou Xu, Hongyu Wang, Jianxun Lang, Wenze Li, Tao Cai, Shanxu Duan, Yuying Xie, Chaoshun Li
Summary: A novel lower upper bound estimation model based on the gated recurrent unit was proposed for clustered wind power forecasting. The model directly realizes interval prediction and introduces an unsupervised learning strategy to construct error interval coefficients. Additionally, loss functions related to the characteristics of the prediction interval are designed and an effective gradient descent algorithm is adopted to optimize the model.
