Yaotang Lv

China Southern Power Grid (China)

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Baorong Zhou

China Southern Power Grid (China)

Lin Guan

South China University of Technology

Qi Zhao

University of Science and Technology Liaoning

Siyu Lu

Zhengzhou University

Tian Mao

China Southern Power Grid (China)

Yingjun Zhuo

China Southern Power Grid (China)

Chengwang Zi

China Southern Power Grid (China)

Xiaogang Wu

Peking University

Lin Guan

Central South University

Zhao Qi

Shandong University

Cooperative Institutions

China Southern Power Grid (China)

South China University of Technology

University of Electronic Science and Technology of China

Huazhong University of Science and Technology

Electric Power Research Institute

Zhejiang University

Nanjing University of Science and Technology

Shandong University

Southeast University

Xidian University

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Research on the modeling of EV charging station considering V2G and its optimal configuration in photovoltaic distribution network

2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific) (2017)

Yaotang Lv Lin Guan Zhao Qi Baorong Zhou

When EV charging stations access to the distribution network, the charge-discharge behavior responded to the grid demand (V2G) will exert a significant impact on the optimized operation of the distribution network. V2G behavior is often guided by the electrovalence policy. The paper proposes an electrovalence guiding principle based V2G response model to optimize the access feeders and access points of EV charging station. With the aim to reduce network loss and intraday voltage fluctuations, the paper also proposes an optimized planning model of charging station with embedded operation simulation in the distribution network of high photovoltaic permeability. According to the optimized results, the paper analyzes the influence of load curve and PV permeability on the optimization program of charging station, and puts forward the basic principle of charging station access planning. The example shows that the operating efficiency of distribution network is significantly affected by V2G behavior of EV charging station. The V2G behavior of charging station might bring a significant negative impact on the distribution network with inappropriate access program. Research results can be widely used in planning project of charging station connected to distribution network.

Charging station

10.1109/itec-ap.2017.8081018

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Citations (3)

Optimal Dynamic Reactive Power Reserve for Wind Farms Addressing Short-Term Voltage Issues Caused by Wind Turbines Tripping

Energies (2018)

Liang Wu Lin Guan Feng Li Qi Zhao Yingjun Zhuo

In regional power grids with high wind power penetration, wind turbine tripping poses great challenges to short-term voltage stability. Dynamic reactive power (VAR) compensation (DVC) plays an important role in securing wind farm operation. To address short-term voltage stability issues, voltage disturbance index (DI) and voltage supporting index (SI) are defined to evaluate the degree of voltage fluctuation and voltage supporting ability of a bus, respectively. Then corresponding vector-type features, called disturbance vector (DV) and supporting vector (SV) are proposed based on the defined indexes. The Kendall rank correlation coefficient is adopted to evaluate the matching degree of DV and SV, so as to determine the influenced area of each wind farm. Candidate locations for DVC are determined sequentially. By comprehensively considering the probability of combined disturbance in each wind farm, a site selection method is proposed and then genetic algorithm is applied to optimize the DVC capacity considering short-term voltage security. The proposed method is applied on a modified NE 39-bus system and a real power grid. Comparison with the engineering practice-based method validates its effectiveness.

Tripping

10.3390/en11071709

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A Lightweight Convolutional Network for Visual Tracking

Frontiers in artificial intelligence and applications (2024)

Jian Wang Yaotang Lv Kun Zhang Yaotang Lv Xiaogang Wu

Regression trackers have been shown to perform superiorly in visual tracking. However, existing researches in regression trackers mainly explore deep models for feature extraction, and then use sophisticated architectures for online detection. Such systems should optimize a massive number of trainable parameters. In this paper, we present a simple yet effective visual tracking system, called LiteCNT. Our algorithm only consists of three convolutional layers for the whole tracking process. In addition, a multi-region convolutional operator is introduced for regression output. This idea is simple but powerful as it enables our tracker to capture more details of target object. We further derive an efficient and effective operator to approximate multi-region aggregation.

BitTorrent tracker

Operator (biology)

Tracking (education)

Feature (linguistics)

10.3233/faia240139

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What is a Proper Face Registration for Face Recognition?

Communications in computer and information science (2024)

Yaotang Lv Zhantao Fan Kun Zhang Zhizhong Li Kun Sun

Distortion (music)

Three-dimensional face recognition

Image registration

10.1007/978-981-99-9109-9_48

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PV Power Characteristic Modeling based on Multi-scale Clustering and Its Application in Generation Prediction

2021 IEEE Power & Energy Society General Meeting (PESGM) (2018)

Baorong Zhou Wenmeng Zhao Xiangrui Su Siyu Lu Tong Wang

The modeling and prediction of stochastic photovoltaic (PV) power curve is a widely concerned issue in power grid operation and planning. Mining and utilization of the big data recorded by the PV stations provide a new method for the modeling of the fluctuating PV power. This paper presents a multi-scale analysis scheme to explore and model both the inherent and the stochastic characteristics of the PV power time sequence. The proposed scheme consists of the multiple clustering analysis at the large time-scale data, the standardized transformations on the small time-scale data, together with the probability distribution modeling. The clustering results are cross validated with the theoretical models from the Meteorology field, and the effectiveness of the proposed methods is verified through an example of day-ahead PV power forecast.

10.1109/pesgm.2018.8586060

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A Probability Model of PV for the Middle-term to Long-term Power System Analysis and Its Application

Energy Procedia (2016)

Yaotang Lv Lin Guan Zongshun Tang Qi Zhao

This paper proposes a probability model for the Photovoltaic (PV) power output which is adaptive for the middle-term to long-term power system analysis. In the first step, a discrete random time series model for the mean value of hourly solar irradiance is presented according to meteorology models. Then a Beta distribution model works to describe the stochastic vibration of the hourly solar irradiance around its mean value. The proposed model can describe the long term behavior of PV generator and has the advantages of less parameters and lower requirements on PV history data. It can also effectively reflect the correlation among PV generators and loads related to locations and life styles. An example of PV location and capacity selection on a distribution feeder is presented to illustrate the application and the feasibility of the model. The proposed model is applicable in power system planning, reliability analysis and many other power system long-term analyses with PV sources.

10.1016/j.egypro.2016.11.244

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Citations (25)