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arXiv 2022年

作者： Wang, Limeng Yang, Ranran Qu, Yang Xu, Chengzhe Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Nanyang Power Supply Company Nanyang473000 China State Grid Jilin Power Supply Company Changchun130000 China

Demand-side management is very critical in China's energy systems because of its high fossil energy consumption and low system energy efficiency. A building shape factor is introduced in describing the architectural characteristics of different functional areas, which are combined with the characteristics of the energy consumed by users to investigate the features of heating load in different functional areas. A Stackelberg game-based optimal scheduling model is proposed for electro-thermal integrated energy systems, which seeks to maximize the revenue of integrated energy operator (IEO) and minimize the cost of users. Here, IEO and users are the Stackelberg game leader and followers, respectively. The leader uses real-time energy prices to guide loads to participate in demand response, while the followers make energy plans based on price feedback. Using the Karush-Kuhn-Tucker (KKT) condition and the big-M method, the model is transformed into a mixed-integer quadratic programming (MIQP) problem, which is solved by using MATLAB and CPLEX software. The results demonstrate that the proposal manages to balance the interests of IEO and users. Furthermore, the heating loads of public and residential areas can be managed separately based on the differences in energy consumption and building shape characteristics, thereby improving the system operational flexibility and promoting renewable energy consumption. © 2022, CC BY-NC-ND.

关键词： MATLAB

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Visualization of CNN Transient Voltage Classification Based on Feature Recognition and Enhancement

Visualization of CNN Transient Voltage Classification Based ...

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Sustainable power and energy Conference (iSPEC)

作者： Zhendong Li Yutian Liu Jun An Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781665414401

The deep learning algorithm represented by CNN has achieved remarkable results in complex feature extraction, classification and regression. Since the CNN adopts an end-to-end training process, the carrier of acquisition knowledge is a high-dimensional non-linear function, which is hard to understand by humans. Therefore, it is difficult to be widely used in online decision-making engineering scenarios such as the fast assessment of power system transient voltage stability. In this paper, the key input elements extracted by CNN are identified by Grad-CAM, and the key features captured by CNN in the assessment process are enhanced based on AM, so as to finally obtain the visual expression of key areas and variables of the original input data. Besides, a sample construction method based on single line diagram is proposed to improve the visualization effect of Grad-CAM and AM. simulation results and analyses of IEEE 39bus test system demonstrates the effectiveness of the proposed method.

关键词： Training Visualization simulation Data visualization Voltage power system stability Feature extraction

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Probabilistic prediction of short term wind power considering temporal and spatial dependence of prediction error

Probabilistic prediction of short term wind power considerin...

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作者： Yong Sun Zhenyuan Li Chaoyu Shi Baoju Li Mao Yang State Grid Jilin Electric Power Supply Company Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University)

The short-term probabilistic prediction of wind power has the characteristics of spatial dependence and time-series *** the two characteristics at the same time can improve the prediction level. In this paper, a probabilistic short-term wind power prediction model considering the temporal and spatial dependence of prediction error is proposed. Considering the coupling relationship between the two properties, the NWP(Numerical Weather Prediction) wind speed point prediction error in the historical period is hierarchical clustering, and the empirical distribution model is used to fit the probability distribution of the error under different wind conditions;the cumulative empirical distribution probability value corresponding to the NWP wind speed at the time to be predicted is bootstrap sampling;under the given confidence level, the possible wind speed at each time point to be predicted in the short term is calculated The power fluctuation range of the generator. The test results show that this method can ensure the statistical significance and fitting stability of the sub sample set at the same time, and improve the classification accuracy of the days to be predicted. Compared with considering a single property, the result of probability prediction performs better on multiple evaluation indexes.

关键词： Probabilistic prediction of short term wind power considering temporal and spatial dependence of prediction error

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Optimization control Strategy of Pumped Storage power Station Considering Cost Allocation

Optimization Control Strategy of Pumped Storage Power Statio...

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International Conference on power system technology (powerCON)

作者： Jun Yan Qinglong Song Qi Guo Lijian Xin Fancheng Meng Shuo Yu Jiaxu Zhou Cuiping Li Junhui Li Inner Mongolia Power (Group) Co. Ltd. Hohhot China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Power Dispatching and Control Branch Inner Mongolia Power (Group) Co. Ltd. Hohhot China Inner Mongolia Electric Power (Group) Co. Ltd. Inner Mongolia Electric Power Research Institute Branch Hohhot China

Against the backdrop of the increasing proportion of new energy generation, pumped storage, as the main energy storage method, face problems of low utilization and poor economic benefits. To improve the enthusiasm and overall efficiency of pumped storage power stations, this article proposes an optimized control strategy for pumped storage power stations that takes into account cost sharing. This strategy combines the PSS allocation system operation rules and control strategies to improve the utilization of PSS capacity by expanding its application scenario range, and to increase its enthusiasm for extraction by increasing rental income; This article takes a regional power grid in northwest China as an example for analysis, and the results show that the proposed strategy can effectively improve the utilization level and economic benefits of PSS.

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Peaking Demand Analysis and Visualization simulation Platform Implementation of High Proportion of Wind power Infiltration Grid

Peaking Demand Analysis and Visualization Simulation Platfor...

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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Lv, Xiangyu Li, Dexin Li, Junhui Ge, Changxing Tian, Chunguang Wang, Jiarui Yan, Gangui Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd. Changchun China Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Jilin China

ISBN: (纸本)9781728143033

This paper proposes a analysis method of peak shaving demand for power grid, and analyzes the impact of wind power grid connection on power system peak shaving under different wind power permeability, and analysis the operational characteristics of energy storage assisted peak shaving to compare different energy storage systems. Finally, in order to facilitate the implementation and observation of the analysis results, a visual simulation platform was built. The results of the example show that the method described in this paper can accurately analyze the peaking shaving demand under different wind power permeability. At the same time, the total yield of lithium iron phosphate battery is the highest in the choice of energy storage type, which is 497 million yuan/year. All-vanadium redox flow batteries may benefit more than lithium iron phosphate batteries in the future due to battery characteristics. Finally, the visualization platform is true and effective and can fully express the method described in this paper. © 2020 IEEE.

关键词： Wind power

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Dc-Side Synchronous Active power control of Two-Stage Photovoltaic Generation for Frequency Support in Islanded Microgrids

SSRN

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SSRN 2022年

作者： Zhong, Cheng Zhou, Yang Chen, Jikai Liu, Zhanjie Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China State Grid Shandong Weihai Electric Power Co. Ltd Weihai China State Grid Energy Research Institute Co. Ltd Beijing102209 China

Virtual synchronous generator control (VSG) is an attractive method for the grid-tied inverter to provide inertia and frequency support. However, it brings some troubles on DC-link voltage control when it is applied to two-stage photovoltaic (PV) power generation. This study proposes a DC-Side synchronous active power control for two-stage photovoltaic (PV) power generation without energy storage. Synchronous active power control l is applied to DC-DC converters, while the grid-tied inverter still maintains the DC-link voltage constant. The DC-DC converters flexibly regulate active power to provide the simultaneous inertial and primary frequency response like a synchronous generator. A simple sensorless iterative maximum power estimation method is introduced and integrated into the DC-side VSG strategy. The maximum available power under variable irradiance conditions can be obtained. The effectiveness and advantages of the control strategy are validated through case studies on an island microgrid that included PV generations with a DC-bus collection system. © 2022, The Authors. All rights reserved.

关键词： power control

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FDCA-DSTGCN: A Wind Farm Cluster power Day-ahead Prediction Model Based on Frequency Domain Information Gain and Dynamic Trend Sensing

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IEEE Transactions on Sustainable energy 2025年

作者： Yang, Mao Niu, Jiajun Wang, Bo Huang, Dawei Su, Xin Ma, Chenglian Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing100912 China

Accurate wind farm cluster power prediction (WFCPP) is of vital significance for new power systems with large-scale wind power integration. The current WFCPP modeling method ignores the important role of wind direction and frequency domain information, resulting in insufficient use of spatial information and difficult to improve the prediction accuracy. In order to solve the above problems, a day-ahead power prediction model for wind farm cluster power is proposed based on information gain in frequency domain and dynamic trend sensing. Firstly, a cluster division method based on graph theory and progressive fusion of multiple information is proposed, and a virtual information node is set up. Secondly, a method to identify prevailing wind direction under time window is proposed for subsets, and a dynamic weighted directed graph structure is designed based on prevailing wind direction and wind speed. Thirdly, a dynamic spatio-temporal graph convolutional network model with frequency domain gain channel attention mechanism (FDCA-DSTGCN) is proposed to integrate the above information and complete the prediction. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia of China. Compared with the existing and traditional prediction methods, the normalized root mean square error of the proposed method is reduced by 1.13% -2.15%, which verifies the effectiveness of the proposed method. © 2010-2012 IEEE.

关键词： Mean square error

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Planning of active power distribution network based on source-network-load collaborative optimization 16

Planning of active power distribution network based on sourc...

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16th IET International Conference on AC and DC power Transmission, ACDC 2020

作者： Jiang, Zhicheng Yu, Qingguang Li, Ang Xiong, Yufeng Long, Gaoxiang Liu, Yuming Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9781839533914

With the fast development of renewable energy generation, the randomness and volatility seriously threaten the stability of the power system. In order to improve the consumption rate of renewable energy and the economic benefit, the source-network-load collaborative optimization is put forward and widely used in the power system. And the active power distribution network which consists of the energy storage devices and flexible load is the best carrier to realize it. Based on the active power distribution network planning, this paper firstly designs an economic index covering construction cost and operation cost as the optimization objective. Then with the physical constraints consisting of the physical features of generation units, energy storage devices and flexible load, the source-network-load collaborative optimization model of active power distribution network is established. Finally, a case of city distribution network is presented to verify the effect of source-network-load collaborative optimization and the efficiency of the optimization model. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Optimization

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Fuzzy optimal scheduling of hydrogen-integrated energy systems with uncertainties of renewable generation considering hydrogen equipment under multiple conditions

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Applied energy 2025年 393卷

作者： Song, Jianzhao Wang, Na Zhang, Zhong Wu, Hao Ding, Yi Pan, Qingze Pan, Xingzuo Shui, Siyuan Chen, Haipeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Gansu Branch of Luneng New Energy Group Co. Ltd. Lanzhou730000 China Lanzhou Power Supply Company State Grid Gansu Electric Power Co. Ltd. Lanzhou730000 China TBEA Shenyang Transformer Group Co. Ltd. Shenyang110144 China Northeast Electric Power University Jilin132012 China

Developing hydrogen-integrated energy systems (HIES) represents a cutting-edge strategy for harnessing renewable energy (RE). However, the inherent unpredictability and variability of RE significantly increase the operational uncertainty of HIES, which leads to severe energy curtailment issues when HIES integrates large-scale RE, necessitating greater operational flexibility in the system. To address the challenges, this paper proposes a fuzzy optimal scheduling approach for HIES that considers the hydrogen equipment under multiple operating conditions. The analysis begins by examining the operational mechanisms of hydrogen equipment. Subsequently, a multi-conditions model is developed for electrolyzers, while a reserve model is established for hydrogen fuel cells. Furthermore, the fuzzy chance constraint (FCC) is employed to quantify the uncertainty of RE generation. An integrated demand response mechanism is implemented, incorporating human thermal comfort and building thermal inertia. Finally, a fuzzy optimization scheduling model for HIES is constructed to minimize the total operating costs. The crisp equivalent of FCC is derived to solve this model, thereby transforming the scheduling model based on fuzzy chance-constrained programming into a solvable mixed-integer programming model. The simulation results indicate that the proposed scheduling method can reduce the overall costs of the HIES by 17.98 % and increase the RE accommodation rate by 19.67 %, validating the effectiveness of the method in enhancing the operational flexibility of the HIES. In addition, this study achieves a balance between economic efficiency and reliability, offering a better economy, lower energy curtailment rates, and faster decision-making times compared to robust optimization, scenario analysis, and other common fuzzy optimization methods. © 2025

关键词： Risk perception

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Dual-layer economic dispatch method for electric fused magnesia loads participating in peak shaving guided by price compensation

Dual-layer economic dispatch method for electric fused magne...

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4th energy Conversion and Economics Annual Forum (ECE Forum 2024)

作者： Junhui Li Tianzhen Fan Jing Xu Wei Zheng Chupeng Xiao Chaoyang Xu Cuiping Li Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin People's Republic of China State Grid Electric Power Research Institute Co. State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Co. Ltd. Hubei People's Republic of China State Grid Liaoning Electric Power Supply Co. State Grid Fushun Electric Power Supply Co. Ltd. Liaoning People's Republic of China

ISBN: (数字)9781837242924

To address the severe challenge of increasing fluctuations in supply and demand due to the expansion of new energy installations, this paper proposes a hierarchical optimization control strategy for electric fused magnesia loads participating in peak shav ing, guided by a price compensation mechanism. In the upper-layer system control, a price mechanism is designed to enhance the flexibility of electric fused magnesia loads in participating in peak shaving, considering the overall benefit of the system. In the lower-layer enterprise net profit optimization model, the product revenue, demand response income, operation and maintenance costs, and carbon emission costs of the electric fused magnesia enterprise are balanced to ensure the maximization of the enterprise’s net profit. Finally, numerical examples are used to verify the effectiveness of this method in improving the system's peak shaving capability.

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