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Situation Awareness for Smart Distribution Systems

Edited by
June 2022
214 pages
  • ISBN978-3-0365-4525-7 (Hardback)
  • ISBN978-3-0365-4526-4 (PDF)
https://doi.org/10.3390/books978-3-0365-4526-4
Free download (PDF)

This book is a reprint of the Special Issue Situation Awareness for Smart Distribution Systems that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

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.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
community integrated energy system; energy management; user dominated demand side response; conditional value-at-risk; electric heating; load forecasting; thermal comfort; attention mechanism; LSTM neural network; smart distribution network; situation awareness; high-quality operation and maintenance; critical technology; comprehensive framework; distributionally robust optimization (DRO); integrated energy system (IES); joint chance constraints; linear decision rules (LDRs); Wasserstein distance; load disaggregation; denoising auto-encoder; REDD dataset; TraceBase dataset; machine learning; secondary equipment; CNN; short text classification; electric vehicle; short-term load forecasting; convolutional neural network; temporal convolutional network; climate factors; correlation analysis; sustainable wind-PV-hydrogen-storage microgrid; energy management; power-to-hydrogen; receding horizon optimization; storage; photovoltaic (PV) system; DC series arc fault; power spectrum estimation; attentional mechanism; lightweight convolutional neural network; situation awareness; capacity configuration; wind-photovoltaic-thermal power system; carbon emission; multi-objective optimization; inertia security region; n/a