Yang Du

Northeast Electric Power University

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Huiqing Wen

Xi’an Jiaotong-Liverpool University

Kambiz Samadi

Qualcomm (United States)

Eng Gee Lim

Xi’an Jiaotong-Liverpool University

Weidong Xiao

University of Sydney

Ke Yan

China Jiliang University

Sung Kyu Lim

Georgia Institute of Technology

Xingshuo Li

Nanjing Normal University

Xiaoyang Chen

Xi’an Jiaotong-Liverpool University

Lin Jiang

University of Liverpool

Shreepad Panth

Intel (United States)

Cooperative Institutions

Chinese Academy of Sciences

Xi’an Jiaotong-Liverpool University

Qualcomm (United States)

University of Chinese Academy of Sciences

Shanghai Electric (China)

Shanghai University of Electric Power

Qualcomm (United Kingdom)

Tsinghua University

Zhejiang University

Huazhong University of Science and Technology

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Battery-integrated boost converter utilizing distributed MPPT configuration for photovoltaic systems

Solar Energy (2011)

Yang Du Dylan Dah‐Chuan Lu

Maximum power principle

10.1016/j.solener.2011.05.008

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Citations (80)

Robust Proactive Power Smoothing Control of PV Systems Based on Deep Reinforcement Learning

IEEE Transactions on Sustainable Energy (2023)

Xiaoyang Chen Xu Xu Jia Wang Lurui Fang Yang Du

Efficient integration of photovoltaic (PV) energy into the power grid calls for a robust regulation of its intermittency. At present, the solar forecasting-assisted proactive power smoothing control (PPSC) has shown superiority in handling such PV intermittency due to its battery-less operations. However, the implementation of PPSC is largely dependent on the quality of solar forecasts, i.e, high accuracy over a long horizon, which has seriously limited its extensive application in practice. In this context, this paper proposes a novel PPSC method based on deep reinforcement learning (RL). In addition to the actor-critic structures, a new module, namely, compensator is developed to tackle the problems of sparse reward and state transition stochasticity that are typically associated with the PPSC control task. On top of it, a novel scenario recognized experience replay (SRER) is devised to deal with the data distribution mismatching issue in PPSC. The effectiveness of the proposed method is verified using real-world data from a solar measurement grid. Empirical studies show that compared with the conventional PPSC method, the proposed method can achieve more robust smoothing performance under various forecasting scenarios, rendering it more applicable to practical PV system operations.

Smoothing

Intermittency

10.1109/tste.2023.3239852

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Citations (9)

Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

Can Zhang Yang Du Xiaoyang Chen Eng Gee Lim

Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.

Tracking (education)

Intermittency

10.1109/ei2.2018.8582657

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Citations (11)

Comparing Spatio-Temporal Models for Aggregate PV Power Nowcasting

2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia) (2022)

Guoping Ruan Xiaoyang Chen Yang Du Eng Gee Lim Lurui Fang

The photovoltaic (PV) power fluctuations caused by passing clouds have become a major concern for grid operators. Consequently, utilities are requiring proper treatments to limit the intermittent PV generation. On this point, solar nowcasting provides a remedy by enabling the transition from reactive control to proactive, which often offers remarkable reliability to PV systems. Sensor networks that utilize spatio-temporal models are considered promising for solar nowcasting. However, current studies on sensor network nowcasting have dedicated much to point nowcasts, where the geographic smoothing effect that occurs in aggregate PV systems is generally left out. In this context, this paper presents a comparing study on spatio-temporal models for aggregate PV power nowcasting. Through empirical studies, the forecast skill of spatio-temporal models is found to decrease for a larger PV aggregation. In addition, the spatio-temporal regression shows competitive performance in various scenarios, yielding a priority for practical use.

Nowcasting

Smoothing

10.1109/isgtasia54193.2022.10003491

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Citations (0)

Investigating the 3D cardiomyocyte arrangement in human interventricular septum sample using X-ray phase-contrast microtomography

Wenfeng Li Zhaorui Li Yang Du Shunli Wang

X-ray microtomography

Sample (material)

Interventricular septum

10.1109/icsp62129.2024.10846596

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Citations (0)

Research on operation optimization strategy of grid-connected PV-battery system

2014 International Conference on Renewable Energy Research and Application (ICRERA) (2014)

Wei Cao Yang Du QI Xiao-qing Lijun Ji

The optimization strategy is proposed for the grid-connected PV-battery system in order to gain the maximum benefit. The proposed operation optimization is performed in two steps. In the first step, active power optimization is applied, which is aimed at the minimum operation cost (or the maximum system benefits). In the second step, reactive power optimization is applied based on the result of active power optimization, aimed at the minimum network loss. The charge-discharge cycle constraints and power limit constraints are considered in the battery model. IEEE-30 network is used for case study. Two kinds of electricity price schemes are used to examine the effect of the proposed operation optimization strategy.

Power Optimization

10.1109/icrera.2014.7016569

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Citations (3)

Placement-Driven Partitioning for Congestion Mitigation in Monolithic 3D IC Designs

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2015)

Shreepad Panth Kambiz Samadi Yang Du Sung Kyu Lim

Monolithic 3D (M3D) is an emerging technology that enables integration density which is orders of magnitude higher than that offered by through-silicon-vias. In this paper, we demonstrate that a modified 2D placement technique coupled with a post-placement partitioning step is sufficient to produce high-quality M3D placement solutions. We also present a commercial router-based monolithic intertier via insertion methodology that improves the routability of M3D ICs. We demonstrate that, unlike in 2D ICs, the routing supply and demand in M3D ICs are not completely independent of each other. We develop a routing demand model for M3D ICs, and use it to develop an O(N) min-overflow partitioner that enhances routability by off-loading demand from one tier to another. This technique reduces the routed wirelength and the power delay product by up to 7.44% and 4.31%, respectively. This allows a two-tier M3D IC to achieve, on average, 19.9% and 11.8% improvement in routed wirelength and power delay product over 2D, even with reduced metal layer usage.

Three-dimensional integrated circuit

10.1109/tcad.2014.2387827

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Citations (54)

Sampling grating approach for X-ray differential phase contrast imaging

Optics Express (2015)

Yang Du Xin Liu Jianheng Huang Yaohu Lei Zhigang Zhao

Grating-based X-ray differential phase contrast imaging (GDPCI) typically employs the phase-stepping technique to extract an object's phase information. This method requires heavy radiation dosage and is time consuming. Another potential approach is the reverse projection (RP) method, which, however, relies on a synchrotron radiation source to obtain highly sensitive differential phase contrast(DPC) signal. Here, we present an alternative approach that enables the RP method to be used with a conventional X-ray source and substantially improves the sensitivity of the DPC signal by replacing the analyzer grating of the GDPCI with a sampling grating. This development represents a significant step towards obtaining fast and low-dosage DPC images in medical, biological, and industrial applications.

X-Ray Phase-Contrast Imaging

SIGNAL (programming language)

10.1364/oe.23.012712

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Citations (8)

Coordinated Frequency Regulation Using Solar Forecasting Based Virtual Inertia Control for Islanded Microgrids

IEEE Transactions on Sustainable Energy (2021)

Jiaming Chang Yang Du Eng Gee Lim Huiqing Wen Xingshuo Li

Power system inertia helps the grid to maintain frequency stability. However, as photovoltaic (PV) generation continuously displaces synchronous generators (SGs) and reduces system inertia, it may result in system failure. Virtual inertia control (VIC) technology has drawn increasing attention because it enables PVs to increase system inertia by mimicking the characteristics of SGs. Energy sources are needed to implement the VIC strategy. Energy storage systems (ESS) can be used to provide such energy. However, the high-cost is still hindering its large-scale adoption. Although constant reserve power in PV has recently been proposed as an alternative for ESS, it can cause unnecessary power losses during the PV system working at a stable state. This paper proposes a forecasting-based VIC (FB-VIC) and coordinated reserve strategy. FB-VIC enables the PVs to serve as an alternative inertia supplier without using ESS. PV generation is pre-reserved based on the solar forecasting results, either at PV plant about to be shaded for local curtailment or other unshaded PV plants providing virtual inertia. The coordinated reserve strategy decides how much to reserve at the selected PV plant. It makes the system more robust to forecasting errors. The simulation results reveal that the proposed method can improve system inertia and suppress the frequency variation in a shorter time.

Virtual power plant

Automatic Generation Control

10.1109/tste.2021.3095928

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Citations (20)

Forecasting Based Virtual Inertia Control of PV Systems for Islanded Micro-Grid

Jiaming Chang Yang Du Xiaoyang Chen Eng Gee Lim Ke Yan

Grid frequency stability is maintained by the power system inertia. However, as the converter interfaced photovoltaic (PV) generation increases, the system inertia reduces. This may result in system failures, especially for islanded micro-grid. Virtual inertial control (VIC) technology, which enables PVs to mimic the characteristics of synchronous generators (SG), has drawn increasing attention. Nevertheless, the implementation of a traditional VSG strategy typically requires a constant PV power reserve, causing unnecessary production loss during system steady states. Although VIC can also be effectively implemented by utilizing an energy storage system (ESS). The high cost is still hindering its large-scale integration. In this paper, a forecasting based virtual inertia control (FB-VIC) strategy is proposed, which enables the PV system to serve as an alternative inertia supplier without using any ESS. PV generation is pre-reserved based on the load forecasting results. The reserved PV power and SG are coordinated to perform frequency regulation. A simulation model is built to simulate the proposed FB-VIC method during a system contingency. The simulation results reveal that the proposed method can reduce the instantaneous SG power capacity over 40%. In addition, the proposed control method limits the frequency oscillation in a smaller range, which improves the system dynamic stability.

10.1109/aupec48547.2019.211843

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Citations (10)