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Ultra-Short-Term Wind Power Interval Prediction Based on Fluctuating Process Partitioning and Quantile Regression Forest

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Sun, Yong Huang, Yutong Yang, Mao Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Jilin Electric Power Company Ltd. Changchun China

As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current interval prediction methods are still incomplete in terms of tapping into the physical variability of wind power, especially for the specific time scale of the ultra-short term. This paper therefore proposes a new framework for interval forecasting of ultra-short-term wind power that incorporates the power fluctuation process. Firstly, a fluctuating process of wind power series is defined and a Kalman-SOM method for clustering the fluctuating processes of wind power is constructed. Secondly, a quantile regression forest interval prediction model is constructed for multiple fluctuation processes for ultra-short-term time scales. Finally, the effectiveness of the overall framework is validated at a wind farm in Jilin Province, China. Compared with the traditional interval prediction method. The interval bandwidth is reduced by 0.86% on average, and the interval coverage is increased by 1.4% on average. The results demonstrate the effectiveness and feasibility of the method in this paper.

关键词： wind power ultra-short-term prediction self-organizing map fluctuation quantile regression forest

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Long-Foresight-Term Power Prediction Considering the Evolution of Significant Weather Information for Wind Farm Cluster

SSRN

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SSRN 2023年

作者： Yang, Mao Jiang, Renxian Zhang, Xiaobin Huang, Yutong Guo, Yunfeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Gansu Electric Power Company Gansu730030 China

The current wind power prediction horizon extends up to 7 days, and the research on power prediction for the 8 to 15 day-ahead is still lacking. However, with the increasing proportion of renewable energy in novel power systems, breaking through the long-foresight-term power prediction barrier is crucial support for guaranteeing the secure and stable operation of the power system. To address the aforementioned issues, this study presents a power prediction method for wind farm cluster (WFC) in long-foresight-term, based on the poor availability of existing numerical weather prediction (NWP) in long-foresight-term. Firstly, a significant wind process identification method considering autocorrelation analysis is employed to predict future power trends, and an optimal method is explored for power generation (PG) prediction in the 8 to 15 day-ahead. Secondly, under the constraint of predicted PG, the power corresponding to the historical similar wind process is selected as the predicted value. Finally, the proposed methodology is applied to a WFC in Gansu Province, China. The results indicate that the proposed method reduces the average RMSE and MAE by 4.15% and 3.3%, respectively, effectively tracking the changing trends of wind power. Moreover, it achieves long-foresight-term prediction and enhances the reliability of the prediction. © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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An Optimized control Strategy for Distributed Energy Storage system to Reduce the Peak-valley Difference of Distribution Network 4

An Optimized Control Strategy for Distributed Energy Storage...

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4th IEEE China International Electrical and Energy Conference, CIEEC 2021

作者： Saren, Gaowa Sun, Zhebin Liang, Tao Li, Hengzhen Liu, Pengxuan Ma, Dexuan Zhang, Hao Sun, Dapeng Yan, Jiaqi Li, Cuiping Li, Junhui Inner Mongolia Power Technology Research Institute Hohhot China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9781728171494

Accompanied by energy structure transformation and the depletion of fossil fuels, large-scale distributed power sources and electric vehicles are accessed to distribution network that result in the load peak-valley gap increasing. Energy storage system (ESS) possessed the characteristics such as quick response, precise control and energy bidirectional flow. Therefore, the configuration of ESS in grid is a feasible measure to reduce the difference between peak load and valley load. This paper presents a superior control strategy that uses distributed energy storage to smooth load fluctuation of grid. Set the time scale to one day, constraints such as energy storage capacity, power and state of charge are taken into account, and the calculation examples are designed based on the proposed the evaluation index compares the effect of optimized control strategy given in this paper with the current common constant power strategy, which proves the feasibility and effect of the presented method. © 2021 IEEE.

关键词： simulation platform

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simulation Testing of Large-Scale Grid-Connected Wind Power with Energy Storage system Based on Active Support Performance Evaluation Indices

Simulation Testing of Large-Scale Grid-Connected Wind Power ...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yihua Zhu Yun Hu Liang Tu Mingzhang Su Chao Luo State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

This paper establishes simulation modeling for large-scale grid connected wind power with energy storage system (ESS). The conventional grid-following (GFL) based ESS is used as a reference object to test the active support performance of large-scale grid-connected wind power with grid-forming (GFM) based ESS with active support performance evaluation indices in different scenarios. (1) Small disturbance evaluation indices: The point of common coupling (PCC) frequency/voltage drop depth and recovery time. (2) Large disturbance evaluation indices: The PCC frequency/voltage drop depth and rise height after fault removal. The output active/reactive power drop depth and rise height/recovery time after fault removal. (3) Island capability evaluation indices: The PCC frequency/voltage fluctuation amplitude at the moment of switching and system stability after switching.

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Bald Eagle Search Algorithm for Parameter Identification of Proton Exchange Membrane Fuel Cell

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Yang, Bo Li, Danyang Zeng, Chunyuan Han, Yiming Li, Junhui Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Faculty of Electric Power Engineering Kunming University of Science and Technology Kunming China

A precise and reliable proton exchange membrane fuel cell (PEMFC) parameter identification performs an essential function in simulation analysis, optimal control, and performance research of actual PEMFC systems. Unfortunately, achieving an accurate, efficient, and stable parameter identification can sometimes be problematic for traditional optimization methods, owing to its strong coupling, inherent nonlinear, and multi-variable characteristics. Therefore, an advanced bald eagle search (BES) algorithm is designed to dependably identify the unknown parameters of the electrochemical PEMFC model in this work. For evaluating and analyzing the overall optimization performance of the BES comprehensively, it is compared with the genetic algorithm (GA) based on MATLAB under three cases. According to the simulation results, the optimum root mean square error (RMSE) achieved by BES is 96.27% less than that achieved by GA in parameter identification, which fully indicates that the precision, accuracy, and stability of the optimization results can be remarkably improved via the application of BES.

关键词： proton exchange membrane fuel cell parameter identification bald eagle search algorithm metaheuristic algorithm MATLAB

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Partial Discharge Fault Diagnosis in Power Transformer Based on Symplectic Geometry Mode Decomposition and Optimized Convolutional Neural Networks

SSRN

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SSRN 2023年

作者： Shang, Haikun Liu, Zhidong Huang, Tao Zhang, Ranzhe Li, Feng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Electric Power Research Institute Xinjiang830011 China

To address challenges in feature extraction, such as difficulty in accurately extracting valuable information and low recognition accuracy during pattern recognition, this paper proposes a novel method for power transformer PD fault diagnosis based on symplectic geometry mode decomposition (SGMD) and optimized Convolutional Neural Networks (CNN). First, three different types of power transformer PD fault signals are extracted, namely floating discharge (FD), corona discharge (CD), and bubble discharge (BD), in a laboratory environment. Second, PD signals are decomposed using SGMD to obtain different symplectic geometric components (SGCs). Afterwards, approximate entropy (ApEn) values of each SGC are calculated as PD feature parameters. Subsequently, the sparrow search algorithm (SSA) algorithm is utilized to optimize and configure the CNN parameters to enhance the diagnostic accuracy and stability. Finally, the obtained feature parameters are fed into the optimized CNN for fault diagnosis. simulation and experimental analysis verify the effectiveness of the proposed method. © 2023, The Authors. All rights reserved.

关键词： Mode decomposition

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Exergic Perspective of Low Carbon Economy Dispatch of Carbon Capture Power Plant and Power to Gas Synergistic Operation

SSRN

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SSRN 2023年

作者： Wang, Xiuyun Zhang, Wanyu Wang, Rutian Wen, Xiangyun Cui, Benwang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Tianjin Electric Power Company Tianjin300010 China

In order to improve the system economy and low carbon, the power to gas-carbon capture power plants joint operation system is introduced in the integrated energy system to reduce carbon emissions while increasing the consumption of renewable energy. From the perspective of exergy, both the quantity and quality of energy were taken into account, the calculation methods of different exergy values of energy flow were refined, and the sub-model of exergy flow calculation was established. To further achieve low carbon emission reduction, the costs of carbon emission trading, carbon capture energy consumption and carbon storage were included in the non-energy costs, and the exergoeconomic cost distribution model was established. Compared with the traditional pricing method, this paper considers the impact of carbon cost and energy grade difference on unit exergic cost of cooling, heating and electricity in the system, reflecting the principle of higher quality and higher price. Finally, the constructed model is solved with the total cost as the objective function. The simulation example shows that the proposed scheduling method can improve the low-carbon emission reduction capacity of the system and achieve reasonable cost distribution. © 2023, The Authors. All rights reserved.

关键词： Carbon capture

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Synergetic roadmap of carbon neutrality and clean air for China

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Environmental Science and Ecotechnology 2023年第4期16卷 1-25页

作者： Qiang Zhang Zhicong Yin Xi Lu Jicheng Gong Yu Lei Bofeng Cai Cilan Cai Qimin Chai Huopo Chen Hancheng Dai Zhanfeng Dong Guannan Geng Dabo Guan Jianlin Hu Cunrui Huang Jianing Kang Tiantian Li Wei Li Yongsheng Lin Jun Liu Xin Liu Zhu Liu Jinghui Ma Guofeng Shen Dan Tong Xuhui Wang Xuying Wang Zhili Wang Yang Xie Honglei Xu Tao Xue Bing Zhang Da Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Bo Zheng Yixuan Zheng Tong Zhu Jinnan Wang Kebin He Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100012China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100012China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Institute of Environmental Policy Management Chinese Academy of Environmental PlanningBeijing100012China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control School of Environmental Science and EngineeringCollaborative Innovation Center of Atmospheric Environment and Equipment TechnologyNanjing University of Information Science and TechnologyNanjing210044China Vanke School of Public Health Tsinghua UniversityBeijing100084China Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing100081China China CDC Key Laboratory of Environment and Population Health National Institute of En

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction,air quality improvement,and improved *** the context of carbon peak,carbon neutrality,and clean air policies,this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 *** 18 indicators cover the following five aspects:air pollution and associated weather-climate conditions,progress in structural transition,sources,inks,and mitigation pathway of atmospheric composition,health impacts and benefits of coordinated control,and synergetic governance system and *** tracking the progress in each indicator,this perspective presents the major accomplishment of coordinated control,identifies the emerging challenges toward the synergetic governance,and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

关键词： Carbon neutrality Clean air Synergetic roadmap

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A Data-driven Method for Transient Stability Margin Prediction Based on Security Region

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Journal of Modern Power systems and Clean Energy 2020年第6期8卷 1060-1069页

作者： Jun An Jiachen Yu Zonghan Li Yibo Zhou Gang Mu the Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Northeast Electric Power University) Ministry of EducationJilin 132012China China Electric Power Research Institute Beijing 100192China

Transient stability assessment(TSA)based on security region is of great significance to the security of power *** this paper,we propose a novel methodology for the assessment of online transient stability *** with a geographic information system(GIS)and transformation rules,the topology information and pre-fault power flow characteristics can be extracted by 2 D computer-vision-based power flow images(CVPFIs).Then,a convolutional neural network(CNN)-based comprehensive network is constructed to map the relationship between the steady-state power flow and the generator stability indices under the anticipated contingency *** network consists of two components:the classification network classifies the input samples into the credibly stable/unstable and uncertain categories,and the prediction network is utilized to further predict the generator stability indices of the categorized samples,which improves the network ability to distinguish between the samples with similar *** proposed methodology can be used to quickly and quantitatively evaluate the transient stability margin of a power system,and the simulation results validate the effectiveness of the method.

关键词： Security region computer-vision-based power flow image(CVPFI) transient stability margin convolutional neural network(CNN) comprehensive network

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Coordinated optimal configuration scheme of wind-solar ratio and energy storage considering wind-solar complementary characteristics

Coordinated optimal configuration scheme of wind-solar ratio...

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Energy, Power and Grid (ICEPG), International Conference on

作者： Xiuyu Yang Zhiwen Li Jian Peng Gang Miu Shaowei Yuan Zhengyin Zhu Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeasst Electric Power University Jilin China State Grid Xinjiang Power Supply Company State Grid Urumqi Power Supply Company Urumqi City China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

This study proposes a collaborative optimization configuration scheme of wind-solar ratio and energy storage based on the complementary characteristics of wind and light. On the premise of maintaining the stability of the wind-solar hybrid power generation system, the optimal allocation model of wind-solar ratio and energy storage considering the complementary characteristics of wind-solar is established with the minimum total cost of planning. At the same time, three indicators of power fluctuation index, wind-solar permeability and new energy abandonment rate are proposed to evaluate the scheme.

关键词： Wind energy generation Costs Stability criteria Wind power generation Power system stability Planning Permeability Resource management Optimization Energy storage

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