检索结果-内蒙古大学图书馆

37th Annual Conference on power system and Automation in Chinese Universities, CUS-EPSA 2022

作者： Wang, Yong Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan250061 China

ISBN: (纸本)9789819914388

This paper investigates the small signal synchronization stability problem of grid-connected converter based on phase-locked control in weak grid. Firstly, with the objective of mechanically revealing the synchronization characteristics of the grid-connected converter, a Heffron-Phillips dynamics model is established for the analysis of the synchronization stability of the grid-connected converter by analogizing its synchronization dynamics with that of the traditional synchronous machine. By referring to the traditional low-frequency oscillation analysis idea of power system, the damping of synchronous oscillation mode dominated by phase-locked loop (PLL) is divided into two parts: the inherent damping component of PLL itself and the additional damping component introduced by complex control coupling in weak grid. Then the synchronous stability mechanism of the grid-connected converter in weak grid is revealed from the perspective of the damping characteristics. And from the perspective of the influence of the inherent or additional damping components, the influence of the controller parameters on the synchronous stability of small signal is investigated. The results of this paper clearly reveal the mechanism of synchronous instability of grid-connected converter in weak power grid, and indicate the way for the subsequent synchronous stability control. © 2023, State Grid Electric power.

关键词： Phase locked loops

来源：评论

学校读者我要写书评

暂无评论

Joint planning for PV-SESS-MESS in distribution network towards 100% self-consumption of PV via consensus-based ADMM

引用

JOURNAL OF ENERGY STORAGE 2024年 90卷

作者： Liu, Tianqi Chen, Jian Zhang, Wen Zhang, Yicheng Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China ASTAR Inst Infocomm Res I2R Singapore 138632 Singapore

The integration of distributed photovoltaic (PV) has become a prominent characteristic of distribution network (DN). However, achieving 100% PV self-consumption poses challenges due to intermittent generation and varying load demands. To address these challenges, this paper proposes an innovative joint planning method for PV, stationary energy storage system (SESS), and mobile energy storage system (MESS) using the consensus-based alternating directional multiplier method (ADMM). First, to account for multiple scenarios with real-world variations, a two-stage clustering method with clustering by fast search and finding of density peaks and k-means is employed. Second, a joint planning model for PV, SESS, and MESS is developed to minimize the total cost of DN, including installation, operation, and maintenance costs. The model optimizes the PV capacity, SESS capacity, and MESS capacity, as well as their locations. Third, a distributed planning framework is proposed using consensus-based ADMM, which decomposes the problem into a PV planning subproblem under the worst-case scenario and energy storage system planning subproblems under multiple scenarios. Finally, the proposed method is demonstrated on an IEEE-33 node system, and the results show the method effectively enhances the access capacity of PV by 11.80% and leads to a reduction in the total cost.

关键词： Distribution network Photovoltaic Energy storage system Self-consumption Consensus-based ADMM

来源：评论

学校读者我要写书评

暂无评论

Day-Ahead Optimal dispatch Strategy for Active Distribution Network Based on Improved Deep Reinforcement Learning

引用

IEEE ACCESS 2022年 10卷 9357-9370页

作者： Li, Xiaoyu Han, Xueshan Yang, Ming Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

To effectively deal with the challenge of optimal dispatch caused by uncertainties such as renewable energy in active distribution network, a day-ahead optimal dispatch strategy for active distribution network based on improved deep reinforcement learning is proposed. First, the day-ahead optimal dispatch problem for the active distribution network is modeled as a multistage stochastic programming model. Multistage models attempt to capture the dynamics of unfolding uncertainties over time, so that the interaction between decision making and uncertainty unfolding is represented more accurately and realistically, and the decision can be adjusted dynamically and adaptively. Second, with the help of deep neural network to approximate the power flow model of the active distribution network in a data-driven manner, an improved deep reinforcement learning algorithm is proposed to solve the corresponding multistage stochastic programming problem. The proposed improved deep reinforcement learning algorithm effectively solves the problem that trial-and-error information acquisition methods are difficult to apply to high-cost power systems. Finally, the effectiveness of the proposed day-ahead optimization dispatch strategy for active distribution network based on improved deep reinforcement learning is verified by a modified IEEE33 case.

关键词： Uncertainty Optimization Renewable energy sources Reinforcement learning Heuristic algorithms Adaptation models Active distribution networks Active distribution network multistage stochastic programming optimal dispatch data driven deep learning deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

An efficient approach for diagnosing faults in photovoltaic array using 1D-CNN and feature selection Techniques

引用

INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 166卷

作者： Ali, Yousif Mahmoud Ding, Lei Qin, Shiyao Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China China Elect Power Res Inst 15 Xiaoying East Rd Beijing 100192 Peoples R China

Diagnosing faults in Photovoltaic (PV) systems is essential for operation and maintenance. Selecting relevant features is necessary for successful fault diagnosis because redundant and irrelevant features reduce fault diagnosing accuracy. This paper proposes a novel and efficient approach to diagnosing faults in PV systems. The Feature Selection and Fault Diagnosis (FSFD) method is executed for diagnosing five types of faults in PV array (PVA): partial shading condition, line-line fault, arc fault, open-circuit fault, and degradation fault. Firstly, a PVA modeling method using MATlab/Simulink is employed to simulate I-V curves and extract their features. Next, a feature permutation technique-based method is proposed for selecting the most relevant features. A simple and accurate one-dimensional convolutional neural network (1D-CNN) model is developed to classify the faults based on the selected features. Finally, a confusion matrix is utilized to evaluate the performance of the trained model. Three datasets of PVAs have been utilized to evaluate the effectiveness of the proposed FSFD method. The results indicate that the FSFD method has effectively identified the best five features out of eight for training the 1DCNN model. The trained model has achieved diagnosing accuracy rates of 99.85%, 99.73%, and 99.97% in series-parallel PVA, total cross-tied PVA, and series PVA datasets, respectively. The proposed method accurately diagnoses single faults in three PVA configurations. Therefore, we recommend conducting additional studies to improve the proposed method for diagnosing hybrid faults.

关键词： Photovoltaic array Current-voltage curve Fault diagnosis Convolutional Neural Network Feature selection

来源：评论

学校读者我要写书评

暂无评论

Low-Carbon Economic dispatch of Integrated Energy systems Considering Full-Process Carbon Emission Tracking and Low Carbon Demand Response

引用

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第6期11卷 5417-5431页

作者： Zhang, Yumin Sun, Pengkai Ji, Xingquan Yang, Ming Ye, Pingfeng Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

While reducing the carbon emissions of traditional coal-fired units, carbon capture and storage (CCS) technology can also provide sufficient carbon raw materials for power to gas (P2G) equipment, which helps to achieve the low-carbon dispatch of an integrated energy system (IES). In this paper, an extended carbon emission flow (ECEF) model integrating CCS-P2G coordinated operation and low-carbon characteristics of an energy storage system (ESS) is proposed. On the energy supply side, the coupling relationship between CCS and P2G is established to realize the low-carbon economic operation of P2G. On the energy storage side, the concept of "state of carbon (SOCB)" is introduced to describe the carbon emission characteristics of ESS to exploit the potential of coordinated low-carbon dispatch on both sides of energy release and energy storage. On the load side, a new carbon emission reduction mechanism that guides users to actively respond and reduce carbon emissions is proposed, namely a low-carbon demand response mechanism. This mechanism uses the node carbon intensity as guiding signals, and the willingness of carbon emission reduction or the price in the carbon market as incentive signals. Furthermore, a low-carbon economic dispatch model considering multiple uncertainties such as wind power output, electricity price, and load demands is established. In order to solve the model efficiently, the parallel multi-dimensional approximate dynamic programming (PMADP) algorithm is adopted, and the solution efficiency is significantly improved compared with stochastic optimization, without losing solution accuracy under a multi-layer parallel loop nesting framework. The effectiveness of the proposed model and method is verified on an E14-H6-G6 system and an E57-H12-G12 system.

关键词： Low-carbon economic dispatch carbon emission flow state of carbon (SOCB) state of carbon (SOCB) carbon emission flow low carbon demand response low carbon demand response parallel multidimensional approximate dynamic programming (PMADP) low carbon demand response

来源：评论

学校读者我要写书评

暂无评论

Adaptive Internal Time-Step Adjustment of Elementary Transfer Function Blocks for Trapezoidal Integration in power system Dynamic Simulations

Adaptive Internal Time-Step Adjustment of Elementary Transfe...

引用

2023 International Conference on power system Technology, powerCon 2023

作者： Hang, Yun Li, Changgang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong Jinan China

ISBN: (纸本)9798350300222

With the development of renewable energy sources, the scale and complexity of power systems are continuously increasing, resulting in a high requirement for the efficiency of dynamic simulation. To enhance the overall simulation speed, this paper proposes an adaptive internal time-step adjustment method of elementary transfer function blocks for Trapezoidal integration in power system dynamic simulations. For blocks with different time constants, three integration modes are defined, including single-step integration, multiple-step integration, and static approximation. Each block can select an appropriate integration mode and adaptively adjust its internal time-step. Implementation of static approximation for blocks with small time constants is given. The proposed method is applied to the open-source Simulation Toolkit for Electrical power systems (STEPS). The IEEE 9-bus test system is tested to obtain the maximum simulation time-step that can maintain numerical stability and validate the efficiency of the proposed method. © 2023 IEEE.

关键词： Integration

来源：评论

学校读者我要写书评

暂无评论

Forecasting-Aided Voltage Estimation for Distribution Network Considering the Integrated Management of Virtual power Plants Platform 7

Forecasting-Aided Voltage Estimation for Distribution Networ...

引用

7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Jia, Yujian Liu, Zhao Kan, Changtao Yu, Yue Li, Changgang State Grid Jinan Power Supply Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798350366945

As more distributed energy sources integrate into distribution networks, issues such as voltage fluctuations and reduced observability become increasingly prominent. Therefore, this paper proposes an algorithm for forecasting-aided state estimation (FASE) in virtual power plants' integrated operation management platform. Firstly, a Bidirectional Long Short-Term Memory (BiLSTM)-Extended Kalman Filter (EKF) algorithm for distribution network FASE is introduced. Secondly, the integrated management of virtual power plant platforms (IM-VPPP) enhances the observability of distribution networks. To evaluate the performance of the proposed method, simulations are conducted using the IEEE 33-bus standard distribution system. Results demonstrate significant advantages of the algorithm in terms of accuracy and robustness. © 2024 IEEE.

关键词： power distribution networks

来源：评论

学校读者我要写书评

暂无评论

Bayesian Network Based Imprecise Probability Estimation Method for Wind power Ramp Events

引用

Journal of Modern power systems and Clean Energy 2021年第6期9卷 1510-1519页

作者： Yuanchun Zhao Wenli Zhu Ming Yang Mengxia Wang Key Laboratory of Power System Intelligent Dispatch and Control Shandong University State Grid Jinan Power Company

Although wind power ramp events(WPREs)are relatively scarce,they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity *** this paper,an imprecise conditional probability estimation method for WPREs is proposed based on the Bayesian network(BN)*** method uses the maximum weight spanning tree(MWST)and greedy search(GS)to build a BN that has the highest fitting degree with the observed ***,an extended imprecise Dirichlet model(IDM)is developed to estimate the parameters of the BN,which quantificationally reflect the ambiguous dependencies among the random ramp event and various meteorological *** BN is then applied to predict the interval probability of each possible ramp state under the given meteorological conditions,which is expected to cover the target probability at a specified confidence *** proposed method can quantify the uncertainty of the probabilistic ramp event ***,by using the extracted dependencies and Bayesian rules,the method can simplify the conditional probability estimation and perform reliable prediction even with scarce *** results on a real wind farm with three-year operation data illustrate the effectiveness of the proposed method.

关键词： Bayesian network(BN) conditional probability imprecise Dirichlet model(IDM) imprecise probability wind power ramp events

来源：评论

学校读者我要写书评

暂无评论

Online Cascading Failure Searching Based on Gradient Boosting Decision Tree

Online Cascading Failure Searching Based on Gradient Boostin...

引用

IEEE Belgrade powerTech Conference

作者： Liu, Tianhao Liu, Yutian Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China

ISBN: (纸本)9781665487788

With the penetration of renewable energy sources (RES) increasing rapidly, cascading failures become more complex due to the uncertainty and vulnerability of RES. This paper presents an online cascading failure searching method based on gradient boosting decision tree (GBDT) for the hybrid AC/DC system with high penetration of wind power. First, the cascading failure risk index is established, which considers the impact, probability, and loss of failures. Then, a cascading failure searching based on Monte Carlo tree search and dynamic simulation is performed to acquire the high-risk cascading failures, which are utilized as the training samples. Finally, GBDT is deployed to construct the relationship between operating conditions and failure propagation directions. Online cascading failure searching is realized by combining GBDT failure estimation and dynamic failure simulation. Simulation results of the modified New England 39-bus test system demonstrate that the proposed method can fast and accurately online screen the high-risk cascading failures considering the uncertainty of wind power.

关键词： cascading failure search fault chain gradient boosting decision tree high renewable energy penetration risk estimation index Monte-Carlo tree search

来源：评论

学校读者我要写书评

暂无评论

Low-Carbon dispatch Strategy for Virtual power Plant Based on Bagging Ensemble Learning Forecasting Method 7

Low-Carbon Dispatch Strategy for Virtual Power Plant Based o...

引用

7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Li, Guang Dong, Xin Li, Li Yu, Yue Li, Changgang State Grid Jinan Power Supply Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798350366945

Virtual power plants (VPPs) struggle with peak-shaving due to unreliable distributed generation (DG) data and the intermittent nature of wind and solar power, impacting carbon emissions. This paper proposes a low-carbon dispatch strategy for VPPs based on a Bagging ensemble forecasting model. Firstly, a VPP dispatch framework based on DG output and load forecasting is established, and a Bagging ensemble forecasting model with feature selection is proposed. Secondly, the control characteristics of flexible industrial, commercial, and residential loads are analyzed to establish a control cost model, which is then integrated with the balanced relationship between wind, photovoltaic, and energy storage, as well as the carbon emission mechanism, to formulate a low-carbon dispatch model. Finally, the simulation results show that the proposed strategy can improve the accuracy of DG output and load forecasting in complex feature environments while realizing the interaction between source-grid-load and reducing the generation and operation costs of the grid. © 2024 IEEE.

关键词： Carbon capture and utilization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：