Search Results - "IEEE transactions on smart grid"

Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network by Kong, Weicong, Dong, Zhao Yang, Jia, Youwei, Hill, David J., Xu, Yan, Zhang, Yuan

“…As the power system is facing a transition toward a more intelligent, flexible, and interactive system with higher penetration of renewable energy generation,…”
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Peer-to-Peer Trading in Electricity Networks: An Overview by Tushar, Wayes, Saha, Tapan Kumar, Yuen, Chau, Smith, David, Poor, H. Vincent

“…Peer-to-peer trading is a next-generation energy management technique that economically benefits proactive consumers (prosumers) transacting their energy as…”
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Harmonic Stability in Power Electronic-Based Power Systems: Concept, Modeling, and Analysis by Wang, Xiongfei, Blaabjerg, Frede

“…The large-scale integration of power electronic-based systems poses new challenges to the stability and power quality of modern power grids. The wide timescale…”
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Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges by Wang, Yi, Chen, Qixin, Hong, Tao, Kang, Chongqing

“…The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation…”
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Deep Learning for Household Load Forecasting-A Novel Pooling Deep RNN by Shi, Heng, Xu, Minghao, Li, Ran

“…The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such…”
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A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids by Musleh, Ahmed S., Chen, Guo, Dong, Zhao Yang

“…Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks,…”
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Short-Term Load Forecasting With Deep Residual Networks by Chen, Kunjin, Chen, Kunlong, Wang, Qin, He, Ziyu, Hu, Jun, He, Jinliang

“…We present in this paper a model for forecasting short-term electric load based on deep residual networks. The proposed model is able to integrate domain…”
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A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems by Molzahn, Daniel K., Dorfler, Florian, Sandberg, Henrik, Low, Steven H., Chakrabarti, Sambuddha, Baldick, Ross, Lavaei, Javad

“…Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed…”
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On-Line Building Energy Optimization Using Deep Reinforcement Learning by Mocanu, Elena, Mocanu, Decebal Constantin, Nguyen, Phuong H., Liotta, Antonio, Webber, Michael E., Gibescu, Madeleine, Slootweg, J. G.

“…Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and…”
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Decentralized P2P Energy Trading Under Network Constraints in a Low-Voltage Network by Guerrero, Jaysson, Chapman, Archie C., Verbic, Gregor

“…The increasing uptake of distributed energy resources in distribution systems and the rapid advance of technology have established new scenarios in the…”
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A Multi-Agent Reinforcement Learning-Based Data-Driven Method for Home Energy Management by Xu, Xu, Jia, Youwei, Xu, Yan, Xu, Zhao, Chai, Songjian, Lai, Chun Sing

“…This paper proposes a novel framework for home energy management (HEM) based on reinforcement learning in achieving efficient home-based demand response (DR)…”
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Peer-to-Peer Energy Trading in Smart Grid Considering Power Losses and Network Fees by Paudel, Amrit, Sampath, L. P. M. I., Yang, Jiawei, Gooi, Hoay Beng

“…Peer-to-peer (P2P) energy trading is one of the promising approaches for implementing decentralized electricity market paradigms. In the P2P trading, each…”
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Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment by Xu, Bolun, Oudalov, Alexandre, Ulbig, Andreas, Andersson, Goran, Kirschen, Daniel S.

“…Rechargeable lithium-ion batteries are promising candidates for building grid-level storage systems because of their high energy and power density, low…”
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A Review of False Data Injection Attacks Against Modern Power Systems by Gaoqi Liang, Junhua Zhao, Fengji Luo, Weller, Steven R., Zhao Yang Dong

“…With rapid advances in sensor, computer, and communication networks, modern power systems have become complicated cyber-physical systems. Assessing and…”
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Adaptive Power System Emergency Control Using Deep Reinforcement Learning by Huang, Qiuhua, Huang, Renke, Hao, Weituo, Tan, Jie, Fan, Rui, Huang, Zhenyu

“…Power system emergency control is generally regarded as the last safety net for grid security and resiliency. Existing emergency control schemes are usually…”
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Intelligent Multi-Microgrid Energy Management Based on Deep Neural Network and Model-Free Reinforcement Learning by Du, Yan, Li, Fangxing

“…In this paper, an intelligent multi-microgrid (MMG) energy management method is proposed based on deep neural network (DNN) and model-free reinforcement…”
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Constrained EV Charging Scheduling Based on Safe Deep Reinforcement Learning by Li, Hepeng, Wan, Zhiqiang, He, Haibo

“…Electric vehicles (EVs) have been popularly adopted and deployed over the past few years because they are environment-friendly. When integrated into smart…”
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Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning by Wan, Zhiqiang, Li, Hepeng, He, Haibo, Prokhorov, Danil

“…Driven by the recent advances in electric vehicle (EV) technologies, EVs have become important for smart grid economy. When EVs participate in demand response…”
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Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges by Chen, Xin, Qu, Guannan, Tang, Yujie, Low, Steven, Li, Na

“…With large-scale integration of renewable generation and distributed energy resources, modern power systems are confronted with new operational challenges,…”
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Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement by Lei, Shunbo, Chen, Chen, Zhou, Hui, Hou, Yunhe

“…Mobile power sources (MPSs), including electric vehicle fleets, truck-mounted mobile energy storage systems, and mobile emergency generators, have great…”
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