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Intelligent steady-state operation dispatching strategy for power grid based on deep reinforcement learning 4

Intelligent steady-state operation dispatching strategy for ...

引用

4th international conference on electrical engineering and Mechatronics Technology, ICeeMT 2024

作者： Shi, Xincong Guo, Chuangxin Wang, Weiru Zhao, Jin Zhejiang University College of Electrical Engineering Zhejiang Province Hangzhou City China State Grid Shanxi Electric Power Research Institute Shanxi Province Taiyuan City China

ISBN: (纸本)9798350356472

With the construction of new-type power systems, the proportion of renewable energy access continues to increase, and the uncertainty of the power grid increases. The current power grid dispatch plan based on physical models has slow and time-consuming optimization decision-making calculations. To this end, this paper proposes an intelligent decision-making method for power grid forward-looking dispatch based on deep reinforcement learning. The offline training module utilizes grid data and historical scenarios to evolve dispatch strategies, while the online module implements these strategies based on real-time data, ensuring compliance with operational and safety standards. The adoption of an Actor-Critic framework, particularly the Deep Deterministic Policy Gradient algorithm, demonstrates significant improvements in computational efficiency and decision-making speed compared to traditional optimization methods. The case study verifies the effectiveness of the proposed algorithm and technology based on the ieee 30-bus test system. © 2024 ieee.

关键词： Deep reinforcement learning

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Study on Building Thermal Characteristics for Smart grid 7

Study on Building Thermal Characteristics for Smart Grid

引用

7th international conference on energy, electrical and Power engineering (CeePe)

作者： Xue, Xue Wang, Weiming Sun, Xue Jiangxi Boku Informat Technol Co Ltd Nanchang Peoples R China Nanchang Inst Technol Smart City & IoT Res Inst Nanchang Peoples R China Hong Kong Metropolitan Univ Sch Sci & Technol Hong Kong Peoples R China

ISBN: (纸本)9798350375794;9798350375800

energy shortage and environment degradation have become critical issues for sustainable development. Both electrical grid as major energy supplier and buildings as major energy end-users play important roles in energy saving and emission reduction. This paper presents a brief review of smart grid and building demand response in recent years. electrical grid has been upgrading to smart grid aims to avoid blackout in extensive areas (e.g. USA blackout in 2003 and India blackout in 2012) and improve energy efficiency including developments of distributed generation (e.g. renewable energies) and distributed storage (e.g. electrical storages). Buildings contribute their energy potentials using demand side management. However, energy information and potentials of both buildings and electrical grid have been seldom estimated and communicated with each other. In order to achieve the overall energy performance of both buildings and smart grid, this paper proposes a concept of interactive strategy between buildings at demand side and smart grid at power supply side by considering the energy processes (generation, storage, consumption) of participants. Alterative electricity load profile of buildings and dynamic electricity price of smart grid become the key factors of estimating building thermal characteristics and smart grid energy status (i.e. power surplus/shortage) in the interactive strategy. A case study of simulation is also presented to illustrate processes of interaction and characterization.

关键词： thermal characteristics building smart grid thermal energy storage alterative load profile dynamic pricing interactive strategy

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Design and Implementation of energy Data Multi-party Privacy Query Scheme Based on Privacy Information Retrieval 4

Design and Implementation of Energy Data Multi-party Privacy...

引用

4th ieee international conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Sheng, Liu Hangxuan, Song Fang, Shang Ze, Yuan Xiaoyu, Wang Yingying, Wang Xinyue, Shi State Grid Heilongjiang Electric Power Research Institute Harbin China

ISBN: (纸本)9798350363586

With the development of energy Internet, the privacy protection of energy data has become an important issue. In this paper a multi-party privacy query scheme for energy data based on privacy information retrieval (PIR) technology is proposed, aiming at solving the privacy leakage problem in the process of energy data sharing. By analyzing the current demand of energy data privacy protection, a complete business process is designed in this paper, including data collection, preprocessing, analysis model construction and output. For different privacy requirements, this paper discusses three PIR schemes based on oblivious transfer (OT), homomorphic encryption and keyword PIR, and compares their technical characteristics, communication overhead and computational overhead. Simulation experiments verify the feasibility of the proposed scheme. The results show that the proposed scheme can effectively protect query privacy. The research in this paper provides technical support for the sustainable development of new power systems and is of great significance to promote the safe sharing of energy data. © 2024 ieee.

关键词： Differential privacy

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GeckoDAG: Towards a Lightweight DAG-based Blockchain via Reducing Data Redundancy 43

GeckoDAG: Towards a Lightweight DAG-based Blockchain via Red...

引用

43rd ieee international conference on Distributed computing Systems (ICDCS)

作者： Dai, Xiaohai Zhou, Yifan Xiao, Jiang Cheng, Feng Xie, Xia Jin, Hai Li, Bo Huazhong Univ Sci & Technol Natl Engn Res Ctr Big Data Technol & Syst Wuhan Peoples R China Huazhong Univ Sci & Technol Cluster & Grid Comp Lab Serv Comp Technol & Syst Lab Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Peoples R China Hainan Univ Sch Comp Sci & Technol Haikou Hainan Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China

ISBN: (纸本)9798350339864

To overcome the scaling and performance limitations, the Directed Acyclic Graph (DAG) is utilized as the underlying storage model of blockchain systems, which enables concurrent transaction processing and confirmation. However, accompanied by high performance, DAG-based blockchains still suffer from the severe challenge of constrained storage scalability, i.e., expensive storage overhead. Based on an in-depth analysis of the data, we discover that the root cause of storage overhead stems from the considerable data redundancy in the DAG-based blockchains. In this paper, we propose GeckoDAG, a lightweight DAG-based blockchain, whose design consists of two steps. First, we abstract a storage model named Basic from the existing DAG-based blockchain systems, which offers both high performance and security. On top of Basic, we then devise GeckoDAG, which merges previous transactions into Transaction Union (TU) and reduces the data redundancy in TU, thus lowering the storage overhead. To evaluate our design, we implement a prototype of GeckoDAG and conduct various experiments on it. The experimental results demonstrate that GeckoDAG can offer storage scalability while maintaining the security and efficiency of DAG-based blockchains.

关键词： Blockchain Directed Acyclic Graph Lightweight Redundancy Storage scalability

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Bat-FG: A Broad Attention Based Fine-Grained Offloading in Green computing Power Networks

Bat-FG: A Broad Attention Based Fine-Grained Offloading in G...

引用

ieee international conference on Communications (ieee ICC)

作者： Liu, Zhutao Qiu, Chao Zhao, Yunfeng Wang, Xiaofei Jiang, Jing Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Xian Univ Posts & Telecommun Shaanxi Key Lab Informat Commun Network & Secur Xian Peoples R China

ISBN: (纸本)9781538674628

computing Power Network (CPN) is an evolution of multi-access edge computing. Since the skyrocketing proliferation of CPNs, energy consumption aggravates explosively. However, majority of energy is wasted due to the incomplete analysis of tasks and resources, such as coarse-grained tasks consideration, coarse-grained resources integration, and unfocused complex information. In this paper, we propose a broad attention based fine-grained task offloading approach in green CPNs, i.e., Bat-FG. Specifically, for fine-grained tasks, we establish directed acyclic graphs (DAGs) subtasks offloading problem for green CPNs under the dependency and service constraints. For fine-grained resources, decentralized resources are integrated into resource pools. Bridging the gap between fine-grained tasks and resource pools, we design a novel broad attention meta-reinforcement learning approach, i.e., Bat-MRL to focus on the main information for reducing the tasks' latency and energy consumption. Finally, extensive simulations show that Bat-FG significantly reduces 25.6% task latency and 72.9% energy consumption.

关键词： Green computing power network DAGs task offloading broad attention Meta-reinforcement learning

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Real Time Data-based Demand Side Management Techniques for a Microgrid to Minify the grid Dependency 14

Real Time Data-based Demand Side Management Techniques for a...

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14th international conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Saini, Krishna Kumar Yadav, Chinmay Sharma, Pavitra Mathur, H.D. Birla Institute of Technology and Science Pilani Department of Electrical and Electronics Engineering Rajasthan Pilani India Birla Institute of Technology and Science Dept. of Electrical & Electronics Engineering Pilani India

ISBN: (纸本)9798350335095

Renewable energy sources (ReS) based microgrids (MGs) are the future of the growing electrical industry. Numerous government and private organizations are working in this sector to increase its penetration to the conventional electrical system. But this expanding industry is hindered by its intermittent nature and expensive cost of storage. To make MG based electrical industry sector more sustainable and promising, a technique, demand side management (DSM) is integrated with the system. This paper proposes the development of two DSM based techniques i.e., non-essential load shifting technique (NeLST) and direct load shifting technique (DLST) to maximize the solar photovoltaic (PV) usage and to minimize the operational cost of the MG. These techniques were analyzed with the real time data collected from the installed MG at BITS Pilani, Pilani campus, India and it was found that there was a significant decrement in grid import (GI) and grid export (Ge). It was observed from the results that there was a significant increase in the solar PV utilization and significant decrease in the operational cost of the MG. © 2023 ieee.

关键词： Demand side management

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A Priority-based Online Container Placement Strategy for 5G MeC Cloud enabled Smart grid 23

A Priority-based Online Container Placement Strategy for 5G ...

引用

ieee 23rd international conference on High Performance Switching and Routing (ieee HPSR)

作者： Jiang, Jing Xin, Peizhe Wang, Yudong Zhang, Yi State Grid Econ & Technol Res Inst Co Ltd Beijing Peoples R China State Grid Zhejiang Elect Power Co LTD Informat & Telecommun Co Hangzhou Peoples R China

ISBN: (纸本)9781665406079

As the rising of computation-intensive applications, such as AI-enabled monitoring, real-time video analysis, lower latency is required by the smart grid. Mobile edge computing (MeC) cloud of 5G, which has the advantages of edge computing and cloud computing, is a promising technology to solve the latency problem through local task computing. However, considering the various requirements of the applications in smart grid, the resource utilization efficiency of MeC cloud is largely restricted to the containers with low flexibility and scalability. In this circumstances, we study the container placement strategy for 5G MeC cloud enabled Smart grid. Within this strategy, we firstly formulate a latency optimization problem, where the applications are classified to different priorities. And then, We use the algorithm CVH, which combines vertical resizing and horizontal scaling, to figure out the appropriate edge nodes for the container and match the variability of the application QoS. Finally, we simulate our proposed strategy and demonstrate that the proposed algorithm performs better in terms of response time compared to various other baselines.

关键词： Smart grid Container placement 5G MeC Cloud Reinforcement learning DDQN

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effective and efficient Cross-media Knowledge Transfer Through Adapted Invertible Intermediate Space Construction 20th

Effective and Efficient Cross-media Knowledge Transfer Throu...

引用

20th international conference on Intelligent computing (ICIC)

作者： Zheng, Min Wang, Yue Zheng, Dianbo Ye, Qinghe Liu, Weiwei Shi, Cuncun Wu, Chunpeng Zhou, Fei State Grid Smart Grid Res Inst Co Ltd State Grid Lab Grid Adv Comp & Applicat Beijing 102209 Peoples R China

ISBN: (纸本)9789819755905;9789819755912

Cross-media knowledge transfer endeavors to utilize the knowledge or features obtained from the source modality to enhance performance in the target modality. However, the challenge arises from the modality shift that occurs within heterogeneous data. In this paper, we solve the modality shift by introducing a novel adapted invertible intermediate space construction method. Unlike traditional conventional approaches, which typically support limited data domains or tasks, the proposed method explicitly enables knowledge transfer across diverse data domains (e.g., visual images and textual descriptions) and tasks (e.g., single-modal image retrieval and cross-modal image-text retrieval tasks). Particularly, this method extracts multiple features of source and target domains, and then projects them into a shared intermediate space through matrix transformations. Additionally, a discriminative function is utilized to achieve structural alignment. Finally, pairwise similarity is applied in the intermediate space to achieve invertible adaptation across different modalities and tasks. experiments show that our approach surpasses state-of-the-art methods in both image retrieval and image-text retrieval tasks, validating its competitive effectiveness and efficiency.

关键词： Cross-media Knowledge Transfer Invertible Intermediate Space Construction efficient Optimization

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grid-Metaverse: The Path From Digital Twins and Prototype Tests on DC Microgrids

Grid-Metaverse: The Path From Digital Twins and Prototype Te...

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2023 ieee international conference on Metaverse computing, Networking and Applications, MetaCom 2023

作者： Ma, Wenxuan Liu, Mengxiang Hong, Guangrun Yang, Shuo Deng, Ruilong Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou310027 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom

ISBN: (纸本)9798350333336

With the development of cutting-edge technologies and the efforts of business giants, Metaverse is becoming increasingly reachable. In addition to the fields of healthcare, education and cultural tourism, Metaverse will also have a profound impact on the power grid. The digital twin (DT) is regarded as the foundation of Metaverse, but its high cost hinders the broad application of DTs in power grids. In this paper, we propose a path to build the DTs in the direct current (DC) microgrid, which is a representative block in the future power grid with the penetration of renewable energy sources, forming grid-Metaverse that can significantly reduce the cost and improve the interactivity. A model-based DT, which is originated from the physical model, and a data-driven DT, using the graph neural network with the data from the model-based one, are built together to illustrate this path and to show their roles in the grid-Metaverse. Moreover, in the prototype tests, the threats of denial-of-service (DoS) and false data injection (FDI) attacks are validated through the developed DTs. © 2023 ieee.

关键词： Renewable energy resources

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Speech enhancement using IOT for the Mute Community 7

Speech Enhancement using IOT for the Mute Community

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7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Thangam, S. Gurupriya, M. Manyam, Yashaswini Sundaram, Srinidhi Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350350067

Speech enhancement system focuses on improving people's communication with speech impairments by converting unclear speech into a clear and intelligible output using a Rasp- berry Pi with a microphone. The speech is recorded using the microphone, processed for Mel-Frequency Cepstral Coefficient extraction and logistic regression reconstruction of classified speech features. The system works in real time and gives output through a speaker. Initializations had been done, including noise reduction and feature extraction for quality inputs to the logistic regression, which is modelled for indomitable setup through grid search with cross-validation. Testing was carried out in relation to effectiveness, which the system profiles through different metrics, especially accuracy, precision, recall, and F1-score. The results obtained are, in fact, that the model would be of help in increasing the clarity of the speech and hence providing quality in enhancing communication to real-time interactors with a speech defect. The system has the potential of impacting enhancing the quality of life for the user through enhanced communication. © 2024 ieee.

关键词： Microphones

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