Situation Awareness for Smart Distribution Systems

In recent years, the global climate has become variable due to intensification of the greenhouse effect, and natural disasters are frequently occurring, which poses challenges to the situation awareness of intelligent distribution networks. Aside from the continuous grid connection of distributed ge...

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Other Authors: Ge, Leijiao (Editor), Yan, Jun (Editor), Sun, Yonghui (Editor), Wang, Zhongguan (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
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100 1 |a Ge, Leijiao  |4 edt 
700 1 |a Yan, Jun  |4 edt 
700 1 |a Sun, Yonghui  |4 edt 
700 1 |a Wang, Zhongguan  |4 edt 
700 1 |a Ge, Leijiao  |4 oth 
700 1 |a Yan, Jun  |4 oth 
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245 1 0 |a Situation Awareness for Smart Distribution Systems 
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520 |a In recent years, the global climate has become variable due to intensification of the greenhouse effect, and natural disasters are frequently occurring, which poses challenges to the situation awareness of intelligent distribution networks. Aside from the continuous grid connection of distributed generation, energy storage and new energy generation not only reduces the power supply pressure of distribution network to a certain extent but also brings new consumption pressure and load impact. Situation awareness is a technology based on the overall dynamic insight of environment and covering perception, understanding, and prediction. Such means have been widely used in security, intelligence, justice, intelligent transportation, and other fields and gradually become the research direction of digitization and informatization in the future. We hope this Special Issue represents a useful contribution. We present 10 interesting papers that cover a wide range of topics all focused on problems and solutions related to situation awareness for smart distribution systems. We sincerely hope the papers included in this Special Issue will inspire more researchers to further develop situation awareness for smart distribution systems. We strongly believe that there is a need for more work to be carried out, and we hope this issue provides a useful open-access platform for the dissemination of new ideas. 
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546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
650 7 |a History of engineering & technology  |2 bicssc 
653 |a community integrated energy system 
653 |a energy management 
653 |a user dominated demand side response 
653 |a conditional value-at-risk 
653 |a electric heating 
653 |a load forecasting 
653 |a thermal comfort 
653 |a attention mechanism 
653 |a LSTM neural network 
653 |a smart distribution network 
653 |a situation awareness 
653 |a high-quality operation and maintenance 
653 |a critical technology 
653 |a comprehensive framework 
653 |a distributionally robust optimization (DRO) 
653 |a integrated energy system (IES) 
653 |a joint chance constraints 
653 |a linear decision rules (LDRs) 
653 |a Wasserstein distance 
653 |a load disaggregation 
653 |a denoising auto-encoder 
653 |a REDD dataset 
653 |a TraceBase dataset 
653 |a machine learning 
653 |a secondary equipment 
653 |a CNN 
653 |a short text classification 
653 |a electric vehicle 
653 |a short-term load forecasting 
653 |a convolutional neural network 
653 |a temporal convolutional network 
653 |a climate factors 
653 |a correlation analysis 
653 |a sustainable wind-PV-hydrogen-storage microgrid 
653 |a power-to-hydrogen 
653 |a receding horizon optimization 
653 |a storage 
653 |a photovoltaic (PV) system 
653 |a DC series arc fault 
653 |a power spectrum estimation 
653 |a attentional mechanism 
653 |a lightweight convolutional neural network 
653 |a capacity configuration 
653 |a wind-photovoltaic-thermal power system 
653 |a carbon emission 
653 |a multi-objective optimization 
653 |a inertia security region 
653 |a n/a 
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