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7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering

作者： Liu, Zhao Gao, Zhanjun Yang, Tao Yu, Chengao Key Laboratary of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9781510656437

The access of distributed power sources has changed the structure and operation of distribution networks, which makes protection methods currently no longer applicable, and the small probability of extreme disasters makes protections of distribution network face new challenges. In order to make the protection of active distribution network response to different fault types at the same time, a new method of active distribution network pilot protection based on the comparison of the projected and actual values of voltage fault components is proposed based on the analysis of the voltage fault component characteristics of the distribution network when a fault occurs. The method can effectively identify the faults in the zone under different fault types, and has the advantages of not being affected by unmeasurable branches, not being affected by distributed power penetration, and having strong ability to withstand transition resistance. © 2022 SPIE. All rights reserved.

关键词： Probability distributions

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Short-Term Load Prediction of EV Charging Station Based on LSTM Recursion 2

Short-Term Load Prediction of EV Charging Station Based on L...

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IEEE 2nd International Conference on power Science and Technology (ICPST)

作者： Xu, Ziyu Cao, Kuan Liu, Yutian Wang, Chunyi Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China State Grid Shandong Elect Power Co Dev Planning Dept Jinan Peoples R China

ISBN: (纸本)9798350349047;9798350349030

With the rapidly increasing market share of electric vehicles (EV) in recent years, the randomness and uncertainty of EV charging load have posed challenges to the operation of distribution networks. To improve accuracy in load prediction of EV charging station, a short-term load prediction method based on the long short-term memory (LSTM) recursive neural network is proposed in the paper. First, the Canopy-based K-means clustering algorithm is improved to divide the similarly daily load sets of EV charging station. Then, the characteristic information of load days, such as meteorological data, is processed to obtain the typical feature vector of each load set. Next, the bidirectional long short-term memory (BiLSTM) models corresponding to each load set are trained based on the sliding window principle and phase space reconstruction. By calculating the Euclidean distance of the feature vectors between the predicted day and each load set, the most suitable pre-trained BiLSTM model is selected to predict the charging station load. Finally, simulation results demonstrate that the proposed method can effectively improve the load prediction accuracy.

关键词： EV charging K-means clustering LSTM neural network Short-term load prediction Sliding window principle

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A Forecast Error Correction Method Based on Seq2Seq and Auto Encoder for Short-term Wind power Forecast Enhancement

A Forecast Error Correction Method Based on Seq2Seq and Auto...

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2024 IEEE IAS Industrial and Commercial power system Asia, I and CPS Asia 2024

作者： Ma, Haoyu Yang, Ming Han, Zifen Wang, Bo Che, Jianfeng Li, Menglin Control Shandong University Key Laboratory of Power System Intelligent Dispatch Jinan China State Grid Gansu Power Grid Corporation Lanzhou China China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Beijing China

ISBN: (纸本)9798350352290

Accurate wind power forecast (WPF) is highly significant for the safe and economic operation of power systems, and implementing error correction is a common and effective manner to further enhance the forecasting performance. Nonetheless, existing error correction methods fail to consider temporal relationship and may inadvertently increase the error under certain circumstances, thereby compromising the local precision of forecast. In order to address these issues, this paper proposes an error correction model based on Seq2Seq and auto encoder (AE) to improve forecasting accuracy. Firstly, the seq2seq with attention mechanism is introduced to infer the probable error sequence through learning the temporal relationship between the numerical weather prediction sequence and the actual error sequence. Secondly, the samples that the seq2seq providing a positive error inference are collected and the AE model is employed to extract the meteorological features at these moments. Finally, on the basis of the above two models, the error correction method is constructed consisting of preliminary error inference and posterior correction determination. Using operational data from Ningxia province, the proposed method is validated for its remarkable superiority based on the evaluation metrics. © 2024 IEEE.

关键词： Wind forecasting

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Continuous Feature Representation of Fault Location Based on Electrical Distance for Generalizable Data-Driven Dynamic Security Assessment

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IEEE Transactions on power systems 2025年

作者： Qi, Hang Li, Changgang Liu, Yutian Sun, Runjia Yan, Jiongcheng Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Jinan250061 China

Pre-fault dynamic security assessment (DSA) of power systems needs to consider different fault locations. Existing data-driven DSA methods lack generalizable fault location features, failing to accurately assess unlearned fault locations, i.e., fault locations not in the training set. To address this issue, this paper proposes a continuous feature representation method of fault location based on electrical distance, aiming to construct a pre-fault DSA model generalizable to unlearned fault locations. Firstly, fault location is represented continuously as an electrical coordinate with the electrical distance to preselected reference nodes. Then, the representation ability of electrical coordinates to fault locations is optimized by reference node selection and metric learning. Finally, with electrical coordinates and steady-state features as input, a hybrid DSA model composed of convolutional and radial basis function networks is constructed to assess system angular and voltage dynamics with different fault locations. The generalization performance of the proposed DSA method on unlearned fault locations is verified on New England 39-bus system and a provincial system of China. © 1969-2012 IEEE.

关键词： data-driven Fault location feature representation power system pre-fault dynamic security assessment

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Online assessment of allowable temperature rise time of overhead conductor after a step change of current in the operating environment

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ENERGY REPORTS 2022年 8卷 332-339页

作者： Wang, Mengxia Wang, Haitian Wang, Mingqiang Zhang, Qiang Wang, Shihao Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Shandong Elect Power Dispatching & Control Ctr Jinan 250001 Shandong Peoples R China

In operating power systems, when the current of the transmission component has a step change caused by outage events, it is of great significance to assess the allowable temperature rise time (ATRT) of the current violated transmission components online for ensuring the effectiveness of the corrective control decision of the power system in emergency. The traditional calculation of the ATRT of overhead conductor after a step change of current does not consider the variability and uncertainty of micro-meteorological environment around the conductor in the temperature rise process, which is inconsistent with the actual condition and leads to conservative or aggressive results. In this paper, based on the data of operating environment and state of the overhead conductor obtained by the dynamic terminal rating (DTR) technique, the distribution laws of the micro-meteorological elements within thermal inertia time of the overhead conductor are analyzed, and a method for generating scenarios of the time series of meteorological elements is proposed. On this basis, the Monte Carlo simulation method is used to simulate the thermal dynamic processes of the overhead conductor during the temperature rise time, and then the probability distributions of the ATRT are obtained, which provides a reference for the operator to determine the allowable time for corrective control in emergency. The effectiveness of the proposed method is verified by numerical simulations in this paper. With the application of DTR technique, the proposed method has engineering application potential and values. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/). Peer-review under responsibility of the scientific committee of the 2021 The 2nd International Conference on power Engineering, ICPE, 2021.

关键词： power system Emergency Corrective control Overhead conductor Allowable temperable rise time

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Longitudinal Protection Method Based on Voltage Wave Comparison in AC/DC Hybrid system

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2022年第2期58卷 1564-1572页

作者： Cong, Wei Zhang, Hongzhe Kong, Hao Chen, Ming Wei, Zhen Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Qingdao Power Supply Co Qingdao 266002 Shandong Peoples R China

When a fault occurs on the tie line of ac/dc hybrid system, the change rule of electrical quantity on the inverter side is different from that of infinite ac power source. Sensitivity and reliability of the traditional relay protection methods will be affected. A longitudinal protection method for ac/dc hybrid system based on voltage wave similarity comparison is proposed. The protection compares the similarity of the measuring voltage wave and the calculated reference voltage wave, and determines the fault location roughly. By comparing the judgment results of voltage similarity between both ends of line, a reliable judgment can be made to distinguish between internal and external faults. In order to improve the reliability of voltage wave similarity comparison, dynamic time warping method is used to overcome the influence caused by phase error, and Pearson correlation coefficient method is used to judge the similarity of voltage wave. The simulation results of real time digital simulation system (RTDS) show that the proposed method can identify the fault which occurs on the tie line of ac/dc hybrid system accurately which has high reliability and good applicability.

关键词： Voltage measurement Mathematical models Correlation coefficient Transmission line measurements Current measurement Sensitivity Inverters AC DC hybrid system dynamic time warping (DTW) longitudinal protection Pearson correlation coefficient voltage wave comparison

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Prediction and Preventive control Scheme for Wind and PV power Ramp Events 9

Prediction and Preventive Control Scheme for Wind and PV Pow...

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9th International Conference on power and Renewable Energy

作者： Zhai, Yifei Wang, Zengwei Zhang, Kunpeng Ma, Huan Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Shandong Peoples R China State Grid Shandong Elect Power Res Inst Power Grid Technol Ctr Jinan Peoples R China

ISBN: (纸本)9798350377477;9798350377460

As the large scale integration of photovoltaic and wind power into the grid increases, renewable energy ramp events have become a potential threat to the secure operation of the power grid. To effectively address renewable energy power ramp events, this paper proposes a prediction and preventive control scheme. First, a rolling warning approach is achieved by the long short-term memory network and fuzzy logic, which provides warning levels and guides decision-making for preventive control. Second, a two-stage optimization scheduling model is proposed, including a day-ahead and an intra-day sub-model. The two-stage scheduling model comprehensively considers power support from interconnectors and preventive control costs. Simulation results demonstrate that the proposed scheme can provide adaptive preventive control strategies for power ramp events with varying risk levels, thereby enhancing the utilization of renewable energy and improving the security of power system.

关键词： renewable energy ramp event early warning preventive control fuzzy logic

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Four-Stage Space-Time Hybrid Model For Distributed Photovoltaic power Forecasting

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2023年第1期59卷 1129-1138页

作者： Shi, Jie Chen, Yaobang Cheng, Xingong Yang, Ming Wang, Mingqiang Univ Jinan Sch Phys & Technol Jinan Peoples R China Univ ofJinan Sch Elect Engn Jinan Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

The precision and reliability of distributed photovoltaic (PV) power forecasting play a crucial role in commercial PV plants for power integration and operation. However, the stochastic and intermittent nature of solar radiation affects forecasting accuracy. What's more, the diverse location and various meteorological information have brought challenges to real-time distributed forecasting. Therefore, it is more difficult for forecasting distributed power than centralized power. To solve this problem, we propose a four-stage space-time hybrid method for power forecasting of distributed PV plants. Firstly, Global and Local Feature Fusion Network (GLFFNet) is proposed to forecast the power output of centralized PV plants. Secondly, the weather clustering type is obtained to get ready for studying the relationship between centralized and distributed PV plants. Then, uncovered coefficients are figured out to show the distribution features of PV power both in the time and space domain. Finally, the correlation models are established based on Copula analysis. According to the above steps, the centralized forecasting results are transformed to obtain the distributed forecasting model. The case study shows that the proposed GLFFNet is more suitable for 1-hour ahead forecasting. Compared to 9 different neural models, MAPE reductions of GLFFNet model (time steps of 1 hour and 15 minutes) are 12.17%-23.23% and 3.18%-18.22%, respectively. Thus, MAPE of the case distributed PV power forecasting models are 0.62% (Type A), 0.96% (Type B) and 3.21% (Type C), respectively.

关键词： Forecasting Predictive models Convolutional neural networks Photovoltaic systems Computational modeling Correlation Analytical models Copula distributed forecasting hybrid models neural network photovoltaic (pv) power forecasting

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power system Loss Reduction Strategy Considering Security Constraints Based on Improved Particle Swarm Algorithm and Coordinated dispatch of Source-Grid-Load-Storage

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PROCESSES 2025年第3期13卷 831-831页

作者： Zhang, Shuolin Yan, Jiongcheng Xie, Pengteng Zhai, Pengming Tao, Ye Shandong Univ Sch Elect Engn Jinan 250061 Shandong Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Yunnan Power Grid Co LTD Diqing Power Supply Bur Jinghong 666100 Peoples R China Wenshan Power Supply Bur Yunnan Power Grid Co Ltd Wenshan 663000 Peoples R China

Coordinating various controllable distributed resources to reduce network losses is crucial to the secure and economical operation of modern power systems. This paper proposes a bi-level optimization model for power system loss reduction based on "source-grid-load-storage" coordinated optimization. The upper level aims to minimize the total annual planning cost of the system, determining the location and capacity of distributed photovoltaic systems, energy storage devices, and electric vehicle charging stations. The lower level aims to minimize the load curve smoothness and node voltage deviation of the distribution network, optimizing intraday operation strategies. For this complex optimization problem, this paper designs a particle swarm optimization (PSO) algorithm with adaptive weights and improved evolutionary strategies. The simulation results of case studies demonstrate that the proposed method has significant loss reduction effects in distribution networks of various scales and complexities. The algorithm performance comparison results show that the improved particle swarm algorithm outperforms traditional algorithms in terms of solution quality and computational efficiency, providing an effective solution for the coordinated optimization of "source-grid-load-storage".

关键词： bi-level optimization power system loss reduction "source-grid-load-storage" coordinated optimization particle swarm optimization

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Accurate Stability Analysis of Modular Multilevel Converters Modeled as Delayed Periodic systems 2

Accurate Stability Analysis of Modular Multilevel Converters...

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IEEE 2nd International Conference on power Science and Technology (ICPST)

作者： Jia, Xiaofan Ye, Hua Gao, Lei Hou, Kaiyuan Wang, Kefei Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China China Elect Power Res Inst Power Syst Dept Beijing Peoples R China State Grid Cooperat China Dispatch & Commun Ctr Northeast Branch Shenyang Peoples R China

ISBN: (纸本)9798350349047;9798350349030

The increasing use of modular multilevel converters (MMCs) raises system stability concerns, such as instability in a wide frequency range. Accurate stability analysis of such systems thus is urgently demanded. In this regard, the small signal modeling of the system can be described by a set of linear time-periodic (LTP) differential equations involving time delays, which requires much more effort. A generalization of the ordinary differential equation (ODE)-based harmonic state space (HSS) framework to delayed differential equations (DDEs), HSS-DDE for short, has been proposed to tackle time delays and periodicity within a unified framework. However, the authors found in practical application that this model produces erroneous results when the time delay involved is not an integer multiple of the period. Therefore, this paper first intensively analyzes the limitations of the HSS-DDE model, and then introduces the time-periodic infinitesimal generator and partial discretization idea to reconstruct an improved model that is not affect by the relationship between time delays and period. Thus, the stability of delayed periodic systems can be readily studied. The results of a numerical example and the grid-connected MMC system verify the accuracy and validity of the proposed model.

关键词： harmonic state-space linear time-periodic system time delays modular multilevel converter small signal stability analysis

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