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5th IEEE Advanced Information Management, Communicates, Electronic and automation Control Conference, IMCEC 2022

作者： Feng, Chaohan Cui, Can Di, Fangchun Tao, Lei Song, Zhibin Qi, Huiwen Zhang, Xiangyu Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology Beijing100192 China State Grid Shanxi Electric Power Company Economic and Technological Research Institute Shanxi Taiyuan030602 China

ISBN: (纸本)9781665479677

Power dispatching is an important link in the direct production, transmission and distribution of electric energy, and is one of the core components of the power system. It has the characteristics of many types of equipment, complex data structure attributes, and high data acquisition density. At present, the operation data of power grid dispatching and control has been gradually collected in the cloud, and the data assets have begun to take shape. However, the management and operation mode of these data is rough, and they are still used and managed by various business departments. As an intangible asset, the value of data has not been paid enough attention and deeply excavated. From inside and outside the industry, the concept of data as an asset has become a consensus, but in the field of power, the management and application of data assets is still in the exploratory stage. At the same time, in the construction of data capitalization, many methods of other industries are difficult to be directly applied in the field of dispatching and control, so it is urgent to integrate the characteristics of power grid dispatching and control business needs and propose a data capitalization mode with business characteristics. This paper gradually focuses on the scope of power data assets from the broad sense of data assets, and regulates the big data capitalization management. The planning method of dispatching data assets analyzes and summarizes the construction of dispatching data assets, and provides data asset management support for subsequent big data applications and data mining. © 2022 IEEE.

关键词： Big data

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GARL: A Generative Adversarial Reinforcement Learning for Transferable Power Grid Dispatch

GARL: A Generative Adversarial Reinforcement Learning for Tr...

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IEEE Information technology and Mechatronics Engineering Conference (ITOEC)

作者： Nan Yang Liang Dong Yichen Wei Xingwei Liu Weitong Chen Zhejun Zhang Xinhang Li Yupeng Huang Lei Li Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

This paper proposes a novel deep reinforcement learning approach, named GARL (Generative Adversarial Reinforcement Learning), for intra-day optimization dispatch in high-proportion new energy grid. The proposed method embeds a Generative Adversarial Network (GAN) within the Deep Deterministic Policy Gradient (DDPG) framework to learn the reward distribution of the power grid in the future operation situation, so as to realize the cumulative reward prediction in the dispatching period and ensure the optimization of the dispatching decision. Comprehensive experiments are conducted on the SG-126 power grid simulator under three representative scenarios to evaluate the performance and generalization capability of GARL. The results show that GARL can learn the distribution characteristics of stateaction-reward sequence from historical experience, establish the mapping relationship between current state and future cumulative reward, and improve the accuracy of future power grid operation trend prediction, which is always better than the independent DDPG algorithm. Furthermore, the study explores the potential of transfer learning between scenarios and finds that GARL exhibits a promising generalization capability.

关键词： Renewable energy sources Uncertainty Transfer learning Generative adversarial networks Deep reinforcement learning Market research Prediction algorithms Power grids dispatching Optimization

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Detecting and Exploiting Unit Commitment Structures in MIPs 6

Detecting and Exploiting Unit Commitment Structures in MIPs

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6th International Conference on Power and Energy technology, ICPET 2024

作者： Su, Zhao-Gang Chen, Sheng-Jie Li, Yu-Fei Chen, Liang Kou, Caixia Cai, Zhi Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Institute of Applied Mathematics Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China College of Sciences Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (纸本)9798350375855

The unit commitment (UC) problem has been extensively researched in the literature, which is typically formulated as a mixed integer programming (MIP) problem. However, current studies lack effective methods to identify potential UC problem structures within a general MIP problem, making it challenging to leverage well-established valid inequalities for UC problems to accelerate the solution process. In this paper, we present a novel detection method that automatically identifies UC structures within an MIP problem by analyzing the relationships between variables and constraints. Moreover, we enhance the MIP formulation by incorporating three well-studied classes of valid inequalities as cutting planes, based on the identified UC structures. Our experiments demonstrate that our proposed UC detection method greatly improves computational efficacy of a standard MIP solver compared to the default setting. © 2024 IEEE.

关键词： Mixed-integer linear programming

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Wasserstein Distance-Based Renewable Scenario Generation Method

Wasserstein Distance-Based Renewable Scenario Generation Met...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Zhi Cai Shengnan Xu Linghao Li Wei Wang Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

In order to address the uncertainty associated with renewable energy sources, this study develops a scenario construction method. An initialization of the Gaussian Mixture Model (GMM) is achieved through the K-medoids clustering method. Subsequently, a large set of foundational scenarios generated through sampling is subjected to scenario reduction using the Wasserstein distance. The effectiveness of the proposed methodology is validated using wind and solar data from the PJM electricity market.

关键词： Renewable energy sources Uncertainty Accuracy Energy Internet system integration Wind power generation Probabilistic logic Scenario generation Gaussian mixture model Load modeling

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Design and implementation of power grid operation environment simulation system based on Reinforcement Learning 2

Design and implementation of power grid operation environmen...

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2nd IEEE International Conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2021

作者： Ling, Yu Jiaqi, Wang Nan, Yang Wenyue, Xia Dapeng, Li Qiong, Feng Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665428767

With the rapid and profound changes in all aspects of power system, the control scale increases exponentially, the characteristics of control objects vary greatly, the bilateral uncertainty of source load increases, and the power grid real-time dispatching will be more complex and frequent. In this paper, we combine current advanced artificial intelligence technology and power grid dispatching business needs, design and develop power grid operation environment simulation system based on reinforcement learning. The system determines the power grid scenario according to the user's choice, applies the real-time power grid operation data, directly interacts with the decision agent, realizes the agent's autonomous learning and continuously improves its regulation and decision-making ability. The system has good feasibility, practicability and scalability, realizes the standardization of workflow, and provides an effective decision support tool for power grid dispatching. © 2021 IEEE.

关键词： Reinforcement learning

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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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Journal of systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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Power Grid Fault Localtion Method Based on Graph Neural Network

Power Grid Fault Localtion Method Based on Graph Neural Netw...

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Information technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xingwei Liu Xuri Song Yijun Yu Fengbin Zhang Shixiong Fan Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology Beijing China China Electric Power Research Institute Beijing China

With the improvement of the interconnection degree of the power grid and the massive grid-connected operation of new energy, the fault characteristics of power grid have changed. After the fault occurs, quickly locating the fault components will help improve the fault handling efficiency of the dispatchers. In this paper, a graph neural network used for fault component identification is designed. The fault label is classified and marked in multiple levels to facilitate the focus identification of fault components. The empirical constraints of dispatchers are integrated into the loss function to further improve the accuracy of fault identification. An IEEE30 example is used for simulation verification. The results show that the fault element identification method based on graph neural network proposed in this paper has the advantages of high accuracy and strong resistance to interference.

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Discussion on key technologies and model for hydropower-dominated electricity spot market in sichuan 9

Discussion on key technologies and model for hydropower-domi...

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9th China International Conference on Electricity Distribution, CICED 2021

作者： Cai, Zhi Li, Qiang Dai, Sai Beijing Key Laboratory of Research System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (纸本)9781728192291

Different from other provincial electricity spot markets in China where hydropower account for a small proportion, the hydropower-dominated energy structure of Sichuan Power Grid presents unique characteristics. It is necessary to create a spot market sample for large hydropower provinces in combination with its energy characteristics. In this paper, the author analyzes the main characteristics of Sichuan power grid, establishes the evaluation index of the Sichuan electricity market model selection based on the discussion of Sichuan power system operation status, basic electricity market model and experiences in construction of foreign electricity markets, demonstrates the feasibility of developing "centralized spot trading market + medium- and long-term contract for difference"in Sichuan, and discusses the key technical problems in its electricity market construction, providing a useful reference for the follow-up construction of electricity spot market with the characteristics of "cascade hydropower playing a dominant role". © 2021 IEEE.

关键词： Power markets

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Analysis and Design of Inter-provincial Electricity Spot Market Model in China

Analysis and Design of Inter-provincial Electricity Spot Mar...

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Dai, Sai Cai, Zhi Li, Qiang Ding, Qiang China Electric Power Research Institute Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology Beijing China

ISBN: (纸本)9781728190037

China's administration proposes to carry out reform by taking a province as a unit and gradually establish a market-oriented inter-provincial electricity trading mechanism. Since then, eight provincial spot market pilots have entered the phase of settlement trial operation, and electricity market reform has been widely carried out. On this basis, how to further build the inter-provincial electricity spot market and coordinate with the provincial markets is an important issue in the construction of electricity spot markets in China. Based on mainstream market models abroad, this paper analyzes the trans-regional trading models in Europe and the United States and their inspiration to China. Then it introduces the current situation of construction of a trans-regional electricity spot market in China and analyzes its existing problems. Based on this, combined with the actual situation of dispatching management and operation in China, it is pointed out that the spot market in China shall adopt the market model of 'unified market and two-level operation' and adopt the market process of 'inter-provincial before intra-provincial The benefits produced by this model are analyzed. The main market framework is designed from three aspects of market participants, trading timing and optimization process. Finally, the key technical requirements for building the inter-provincial electricity spot market in China are abstracted. © 2021 IEEE.

关键词： Power markets

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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