Dazhi Yang

Dalian University of Technology

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Jan Kleissl

University of California, San Diego

Xiangao Xia

Institute of Atmospheric Physics

Christian A. Gueymard

National Renewable Energy Laboratory

Rita Marincsák

University of Debrecen

Stuart H. Yuspa

National Institutes of Health

Luowei Li

Cancer Genetics (United States)

Julia F. Velasquez

University of Debrecen

Noémi Kedei

National Institutes of Health

Balázs I. Tóth

University of Debrecen

Juan Tao

Huazhong Agricultural University

Cooperative Institutions

Harbin Institute of Technology

113

Chinese Academy of Sciences

Huazhong University of Science and Technology

University of Chinese Academy of Sciences

National University of Singapore

Dalian University of Technology

Sichuan University

Johns Hopkins University

University of Toronto

Peking University

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SoilingEdge: PV Soiling Power Loss Estimation at the Edge Using Surveillance Cameras

IEEE Transactions on Sustainable Energy (2023)

Wenjie Zhang Vaidheeswaran Archana Oktoviano Gandhi Carlos D. Rodríguez‐Gallegos Hao Quan

Solar panels are exposed to various pollutants in outdoor environments, such as dust, sediment, and bird excrement, which can cause the power generated by the panels to drop by up to 50%. To accurately estimate the power generated by photovoltaic (PV) systems, it is necessary to take into account the effects of soiling on the panels. In this article, we propose a deep learning approach that uses edge devices such as micro-controllers to estimate the power loss due to soiling based on images captured by surveillance cameras. The proposed model, called SoilingEdge, is based on MobileNet and has been implemented on several platforms, including CPUs, edge tensor processing units (EdgeTPUs), field programmable gate arrays (FPGAs), and vision processing units (VPUs). We present a comparative study of the performance of SoilingEdge on these different platforms and show that FPGA offers a balanced compromise between cost and inference performance, while VPU is the most cost-effective option, but has a slower execution time. Furthermore, the article also investigates the interpretability of the model through the visualization of attention maps, thus providing useful insights for researchers and engineers in understanding the model behaviors.

Power loss

10.1109/tste.2023.3320690

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Citations (10)

A broad-band top-cap monopole antenna

Dazhi Yang Yilong Lu Zexiang Shen

This paper presents the analysis and optimal design of a top-cap monopole antenna by using modal expansion analysis and a genetic algorithm. The accurate and efficient modal-expansion analysis is used to compute the electromagnetic fields and input impedance response of the proposed antenna. The effective emperor-selective genetic algorithm (EMS-GA) is used for automatic antenna design optimization. The optimally designed top-cap monopole antenna can achieve up to 95% bandwidth with VSWR/spl les/3.

Electrical length

10.1109/aps.2003.1219780

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Citations (7)

The Estimation of Clear Sky Global Horizontal Irradiance at the Equator

Energy Procedia (2012)

Dazhi Yang Panida Jirutitijaroen W. Walsh

We analyse Singapore global horizontal irradiance (GHI) measurements to estimate clear sky GHI in the equator region. The data consists of a one-year period of clear sky GHI at three solar irradiance monitoring stations in Singapore, namely, First Zero Energy House in Singapore (1.3094∘N, 103.9160∘E) located in the east of the country, Solar Energy Research Institute of Singapore (1.3007∘N, 103.7718∘E) in the mid-west, and Nanyang Technology University Intelligence Systems Center (1.3436∘N, 103.6792∘E) in the west. Several empirical clear sky models are considered for a Singapore case study. An regression method is proposed to parameterise the model of choice for Singapore's measured GHI. The developed model is validated using GHI measurements from difference stations over different time periods.

Empirical modelling

10.1016/j.egypro.2012.07.019

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Citations (43)

On the impact of haze on the yield of photovoltaic systems in Singapore

Renewable Energy (2015)

André Nobre Shravan Karthik Haohui Liu Dazhi Yang Fernando Ramos Martins

Haze

Sunlight

Clearing

10.1016/j.renene.2015.11.079

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Citations (56)

Deep Learning-driven Forecasting of Daily Sea Surface Temperatures in the South China Sea

2022 Photonics & Electromagnetics Research Symposium (PIERS) (2024)

Jiafu Qi Bowen Xie Dazhi Yang Di Li Baoshu Yin

China sea

10.1109/piers62282.2024.10617964

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Citations (0)

Worldwide solar radiation benchmark of modelled surface irradiance

Anne Forstinger Stefan Wilbert Adam R. Jensen Birk Kraas Carlos M. Fernández-Peruchena

<p>Modelled irradiance data based on satellite products is frequently used in solar energy applications and atmospheric sciences. This kind of data is offered by many different institutional or commercial providers, and currently it is not possible for users to independently identify the best provider for their specific application and location. This work presents a benchmark of satellite-derived global horizontal irradiance (GHI) as well as direct normal irradiance (DNI) at 129 ground-based radiation measurement stations distributed globally. High temporal resolution data (1 min) from these stations from between 2015 and 2020 has been quality controlled by a team of experts using a comprehensive set of best practices and newly implemented quality control procedures. The ground stations provide measurements of GHI and DNI and/or diffuse horizontal irradiance (DIF) from 25 different providers or networks. The 129 stations are spread out worldwide with 31 stations in Africa, 31 in Asia, 27 in North America, 20 in Europe, 13 in Australia, 5 in South America and 2 in Antarctica. GHI and DNI data from eleven different commercial or open-access radiation models is compared against these stations&#8217; high-quality ground data. Additionally, one common measurement year is used to perform a site adaptation of the model datasets. The site adaptation is based on the empirical quantile mapping method and is the same for all test data sets. The comparison of the raw model data as well as the site adapted data is conducted at both 60-min and 15-min temporal resolutions. The performance of the raw and site-adapted data is analysed with respect to different regions and climate zones. Users can rely on the results of this work to make an informed decision about which surface radiation model(s) and data providers are most suited for their application.</p>

Benchmark (surveying)

Baseline (sea)

Data set

10.5194/ems2022-547

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Citations (2)

Transitioning from Face-to-Face to Online Instruction

IGI Global eBooks (2011)

Cindy S. York Dazhi Yang Melissa Dark

This article briefly reviews two important goals in online education: interaction and presence. These are important goals in online education because they are linked to learning and motiva-tion to learn. The article provides guidelines and an extended example of how to design an online course in information security in a manner that will enhance interaction and presence. This article's contribution is to provide guidelines with a corresponding extended and concrete example for those who are tasked with designing and delivering online courses. Although the guidelines and example were targeted to the field of information security, they can be readily adopted by other disciplines. Request access from your librarian to read this chapter's full text.

Face-to-face

10.4018/9781599049496.ch080

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Citations (0)

Predictability and forecast skill of solar irradiance over the contiguous United States

Renewable and Sustainable Energy Reviews (2023)

Bai Liu Dazhi Yang Martin János Mayer Carlos F.M. Coimbra Jan Kleissl

Predictability

Forecast verification

10.1016/j.rser.2023.113359

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Citations (15)

The role of short- and long-duration energy storage in reducing the cost of firm photovoltaic generation

Applied Energy (2024)

Guoming Yang Dazhi Yang Bai Liu Hao Zhang

10.1016/j.apenergy.2024.123914

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Citations (3)

Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching

Meng Wan Yufeng Guo Dazhi Yang Jan Kleissl

Accurate solar power forecasting has a decisive effect on the formulation of day-ahead power system dispatch strategies. At present, there is every confidence that paring numerical weather prediction with a physical model chain is the state-of-the-art solar forecasting method suitable for grid integration. Leveraging this two-stage solar power forecasting framework, the total cost benefits of day-ahead power system dispatch have been quantified based on a modified IEEE 24-bus system. The numerical experiment results reveal that the two-stage forecasting method saves 2.1 million dollars (1.33%) per year, as compared to the benchmark.

Benchmark (surveying)

Solar Power

Probabilistic Forecasting

10.1109/spies55999.2022.10082270

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Citations (1)