The energy systems are evolving from passive to active networks embedded in complex cyber-physical systems. A proper management of such systems requires an integrated paradigm for energy management and distributed control based on various (big) data resources. Up till now, only limited effort has been done in exploring the full potential of using field data from the increasing number of advanced sensors and smart meters installed in the grids. The fast-evolving development of the Internet of things (IoT), machine learning/ artificial intelligence, and digital twins enables possibilities to unblock potential from available energy data for resilience and self-management in the distribution grid and other infrastructures (heat, gas, water). A synergy between energy system integration and data analytics under this emerging digital transformation at the grid edges, if developed properly, will lay the foundation for integral solutions to smoothen the whole energy transition. This ambition requires, on the one hand, an enhanced coupling of the electrical system, both AC and DC, with other energy carriers (heat, gas, water) within integrated energy communities. On the other hand, an accurate analysis of the interactions between distribution networks and local markets is required, targeting the optimization of the entire energy system and not of the single energy layers.
This special issue aims to collect original contributions to address and disseminate the state of the art research and development results in developing modelling, control and operation approaches at the grid edges, where multi-dimension integration of digital technologies is one of the core issues. Topics of interest for this special issue include:
stochastic models of integrated local energy communities (e.g. buildings, industry parks, university campus); physics aware neural network models to release energy flexibility resources; deep and/or reinforcement learning to counter uncertainty with advanced flexibility dispatching;assessment and control of DERs impacts on distribution networks;control strategies for compensating shortterm power fluctuations of non-programmable renewable energy sources; optimal coordination of integrated local energy communities enabled by predictive models;realtime and faster-than-real time models and their automated controllers based on twinning models for distributed energy resources (e.g. solar PV, electric vehicles, stationary batteries);faultinitiated islanding microgrids and switching behaviors of DERs;coordinated control strategies for enhancing isolated smartgrids stability; innovative control strategies for ensuring seamless transition of a smart grid from ongrid to off-grid mode and vice versa; data driven modelling and control of multi-modal networks and components; ICT based protection systems for hybrid AC and DC grids; peer to-peer energy management systems and energy trading in community smart grid; building (nanogrid) integrated energy management and monitoring systems; applied IoT architecture and communication technologies for smartgrids; agent based distributed and coordinated voltage control.
All proposed papers must be submitted via https://www.editorialmanager.com/elen/Default.aspx by selecting “SI – grid edges”.
Three-pages extended summary with the description of the main contribution and some results is due by 10 August 2020
Invitation to provide the full paper: 1 September 2020
Full manuscript due: 15 October 2020
Acceptance notification: 1 December 2020
Phuong Nguyen – email@example.com
Eindhoven University of Technology, The Netherlands
Giovanni De Carne – firstname.lastname@example.org
Karlsruhe Institute of Technology, Germany
Yassine Amirat – email@example.com
ISEN Yncréa Ouest, France
Quoc-Tuan Tran – QuocTuan.TRAN@cea.fr
Anh-Tuan Le – firstname.lastname@example.org
Chalmers University of Technology, Sweden
Alessia Cagnano – email@example.com
Politecnico di Bari, Italy
Enrico De Tuglie – firstname.lastname@example.org
Politecnico di Bari, Italy