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Multi-Lever EarlyWarning forWind and Photovoltaic power Ramp Events Based on Neural Network and Fuzzy Logic

Energy Engineering 2024年第11期121卷 3133-3160页

作者： Huan Ma Linlin Ma Zengwei Wang Zhendong Li Yuanzhen Zhu Yutian Liu Power Grid Technology Center State Grid Shandong Electric Power Research InstituteJinan250003China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power CompanyJinan250012China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan250061China

With the increasing penetration of renewable energy in power system,renewable energy power ramp events(REPREs),dominated by wind power and photovoltaic power,pose significant threats to the secure and stable operation of power *** paper presents an early warning method for REPREs based on long short-term memory(LSTM)network and fuzzy ***,the warning levels of REPREs are defined by assessing the control costs of various power control ***,the next 4-h power support capability of external grid is estimated by a tie line power predictionmodel,which is constructed based on the ***,considering the risk attitudes of dispatchers,fuzzy rules are employed to address the boundary value attribution of the early warning interval,improving the rationality of power ramp event early *** results demonstrate that the proposed method can generate reasonable early warning levels for REPREs,guiding decision-making for control strategy.

关键词： Early warning machine learning power system security renewable energy power ramp event smart grid

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Multimodal Representation Learning by Hybrid Transformer with Multi-level Fusion 5

Multimodal Representation Learning by Hybrid Transformer wit...

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5th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2024

作者： Wu, Yi Xu, Hongquan Zhang, Jiaqing State Grid Quzhou Power Supply Company Power Dispatch Control Center QuZhou China

ISBN: (纸本)9798331506612

Multimodal learning, which integrates data from various sensory sources, is essential for advancing artificial intelligence. However, current methods often face issues where certain modalities dominate others, leading to reduced effectiveness. In this paper, we introduce ML-Former, a new hybrid transformer architecture designed to harmonize representation learning across multiple modalities. ML-Former employs a unified input system that reduces interference between modalities, ensuring balanced contributions. It also enables deep interaction and perceptual learning to enhance the integration of diverse modalities, resulting in a more robust and nuanced representation. Extensive experiments on five diverse datasets show that ML-Former outperforms existing methods. © 2024 IEEE.

关键词： Adversarial machine learning

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Design of Integrated Energy System Based on IEC 61499 and OPC UA 41

Design of Integrated Energy System Based on IEC 61499 and OP...

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第41届中国控制会议

作者： Yue Wang Ningxuan Guo Gangfeng Yan Jianing Liu College of Electrical Engineering Zhejiang University Guangdong Power Grid Power Dispatch Control Center

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Integrated Energy System(IES) is a key component of energy internet,which has made great progress in multienergy supplementation,energy conservation and emission *** 61499 standard and OPC UA communication are powerful cyber-physical system technologies for dynamic reconfiguration,interoperability,and *** this paper,we propose a modular design and development approach for IES,based on the reconfiguration-supporting distributed architecture of IEC *** data integration and transmission,we use OPC UA on the communication level to support multiple devices and communication *** program design is implemented on an IEC 61499 compliant software *** build a photovoltaic simulation system with real-time electric meter data acquisition through an OPC UA gateway *** and simulation results show that the proposed approach is effective in realizing a unified,robust and efficient integrated energy control system.

关键词： Integrated Energy System IEC 61499 OPC UA

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Stochastic Voltage/Var Optimization of Active Distribution Networks using Customer-Owned PV Inverters 1

Stochastic Voltage/Var Optimization of Active Distribution N...

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1st IEEE International power Electronics and Application Symposium, PEAS 2021

作者： Wang, Ke Du, Bin Zeng, Kaiwen Lin, Bin Liu, Jianing Guangdong Power Grid Power Dispatch Control Center Guangzhou China

ISBN: (纸本)9781665413596

Voltage/Var optimization (VVO) is an important operational practice for distribution networks. In recent years, the distribution networks have been evolving towards more active systems, called active distribution networks (ADNs). In particular, as a power-electronic device, the solar PV inverters are have a very fast-acting and flexible reactive power support capability. Therefore, they can also be employed for VVO purposes. On the other hand, the solar PV has a highly random power generation characteristic, which would make the bus voltage fluctuation also highly random and may even violate the voltage magnitude constraints. In order to address such random voltage fluctuation problem, stochastic VVO is needed. In this paper, a stochastic optimization based VVO approach is proposed for ADNs with customer-owned solar PV units. The PV inverters are utilized to provide reactive power support in addition to the OLTC and capacitor banks. A sampling average approximation (SAA) method is also proposed to solve the stochastic optimization problem. The proposed approach is tested on the IEEE 33-bus system, and the simulation results validate its effectiveness and advantages over the traditional deterministic VVO method. © 2021 IEEE.

关键词： Stochastic programming

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Optimal Load control for Mitigating Short-Term Voltage Instability of power Systems 1

Optimal Load Control for Mitigating Short-Term Voltage Insta...

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1st IEEE International power Electronics and Application Symposium, PEAS 2021

作者： Zeng, Kaiwen Du, Bin Wang, Ke Liu, Jianing Lin, Bin Guangdong Power Grid Power Dispatch Control Center Guangzhou China

ISBN: (纸本)9781665413596

The short term voltage stability (STVS) of is a critical problem for the power system especially with an highlevel of penetration of renewable energy resources including solar and wind power. In order to improve the STVS, the load control, i.e., load curtailment, is an effective solution. This paper proposes a trajectory sensitivity-based optimization method to optimize the load control. Firstly, the mathematical model of the optimal load control problem is formulated as a STVS constrained optimization model. To quantitively evaluate the STVS, the transient voltage stability index (TVSI) is used. Secondly, a trajectory sensitivity method is designed to calculate the sensitivity of the load control location and the amount with respect to the TVSI. Thirdly, based on the trajectory sensitivity, the optimal load control can be obtained through a step-by-step calculation manner. The proposed method is validated on the New England 39-bus system. Simulation results show that the method can effectively minimize the required load control while satisfying the STVS requirements. © 2021 IEEE.

关键词： Wind power

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Optimal Emergency Demand Response for power Distribution System Security control 1

Optimal Emergency Demand Response for Power Distribution Sys...

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1st IEEE International power Electronics and Application Symposium, PEAS 2021

作者： Su, Zhuo Wang, Ke Zeng, Kaiwen Liu, Jianing Lin, Bin Dispatch Control Center Guangdong Power Grid Power Guangzhou China

ISBN: (纸本)9781665413596

This paper proposes an optimal strategy for EDR implementation in the power distribution system against large contingencies. First of all, the evaluation methods and application steps are developed and presented to determine the maximum potentials of EDR, which are serving as the constraints for the system security dispatch. Secondly, the mathematical problem is formulated as an optimization model where the objective is to minimize the total cost of the EDR program, and the constraints include the network power flow and bus voltage, as well as other operational limits such as the upper bound of the EDR for different buses. Finally, an optimal power flow (OPF) method is employed to solve the optimization model. Numerical case studies results show that the proposed method can achieve the minimum EDR amount while satisfying the security control requirements. © 2021 IEEE.

关键词： Optimization

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TPE-based Short-Term Load Forecasting Neural Network Structure Design and Parameter Optimization Method

TPE-based Short-Term Load Forecasting Neural Network Structu...

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2022 International Conference on power System and Energy Technology, ICPSET 2022

作者： Ling, Wuneng Li, Ling Li, Li Huang, Kui Wu, Yin Zhuo, Yixin Wu, Jianfeng Guangxi Power Grid Dispatch and Control Center Nanning China

Short-term load forecasting is generally applied in power system real-time dispatching and day-ahead generation planning, which is of great significance for power system economic dispatching and safe operation of the system. Much research on short-term load forecasting using neural networks has been carried out at home and abroad. However, how to obtain the optimal network and structure evolution accurately and quickly has evolved into a key challenge for short-term load forecasting, because the prediction effect of the neural network method is more easily affected by the existing network structure and parameters, and the personality difference of the prediction object itself makes it difficult for the parameters to be reused. Aiming at this problem, this paper proposes a TPE-based neural network structure design and parameter optimization method for short-term load forecasting. This method realizes fast optimization of parameters of different types, structures, parameters, and input and output of deep neural networks, and is widely applied in Guangxi power grid. It is verified by an actual example that the method can effectively improve prediction accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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A Deep Learning Short-Term Load Forecasting Method for Extreme Scenarios 8

A Deep Learning Short-Term Load Forecasting Method for Extre...

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8th International Conference on Electromechanical control Technology and Transportation, ICECTT 2023

作者： Ling, Wuneng Sun, Yan Li, Qiuwen Lin, Jie Hu, Jiaqiu Liang, Zhencheng Xiong, Li Guangxi Power Grid Dispatch and Control Center Nanning China

ISBN: (纸本)9781510668331

Short-term load forecasting is a crucial for improving the level of power grid dispatching and operation. In recent years, extreme weather occurs frequently, and deep learning is a method that depends on data volume, which leads to low accuracy of load forecasting in extreme scenarios. In this paper, the regularization technique is used to avoid the over-fitting of deep learning in extreme scenes, by adding the regularization term to the objective function of the neural network, and improving the back propagation algorithm. Finally, this paper proves that regularization can effectively improve the load forecasting accuracy in extremely small sample scenarios through the comparison of actual examples. © 2023 SPIE.

关键词： Forecasting

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Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

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Energy Engineering 2024年第9期121卷 2655-2680页

作者： Jiaxin Qiao Yuchen Hao Yingqi Liao Fang Liang Jing Bian Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy TechnologyMinistry of EducationJilin132011China State Grid Jiangsu Electric Power Co. Ltd.Power Dispatch Control CenterNanjing210017China State Grid Jiangsu Electric Power Co. Ltd.Nanjing Power Supply BranchPower Dispatch Control CenterNanjing210019China

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution *** accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response ***,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation *** this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation ***,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within ***,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of *** model can provide scientific guidance for the economic dispatch of the distribution station ***,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of th

关键词： Distributed photovoltaic distribution station area assessment of adjustment capacity line transmission capacity economic optimization

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Research on the Construction of Security Constrained Economic dispatch Scenarios for Large-scale power grid 3

Research on the Construction of Security Constrained Economi...

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3rd International Conference on Sustainable and Renewable Energy Engineering, ICSREE 2018

作者： Huang, Guodong Xu, Dan Luo, Zhiqiang Ding, Qiang Li, Min Zhang, Hongtu Power Automation Department China Electric Power Research Institute Beijing China Power Dispatch and Control Center State Grid Corporation of China Beijing China Power Dispatch and Control Center State Grid SICHUAN Electric Power Company State Grid Corporation of China Chengdu China

Large-scale power grid security constrained economic dispatch is an effective technical means to solve the optimal allocation of resources in a large area. Based on the characteristics of dispatching plan in the state grid Corporation, a processing strategy for optimizing objectives, planning adjustments, and basic data integration is proposed. A method of constructing a large-scale power grid security constrained economic dispatching scenario based on strategies combination is established, and the adaptability of different scenarios and the difficulty in constructing the corresponding model are analyzed. Multi-scenario construction aims at solving different problems in different scenarios and is a useful method for improving the availability and practicality of large-scale power grid security constrained economic dispatching technologies. © 2018 The Authors, published by EDP Sciences.

关键词： Data integration

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