Impact of Interdisciplinary Research on Planning, Running, and Managing Electromobility as a Smart Grid Extension

Abstract

The smart grid is concerned with energy efficiency and with the environment, being a countermeasure against the territory devastations that may originate by the fossil fuel mining industry feeding the conventional power grids. This paper deals with the integration between the electromobility and the urban power distribution network in a smart grid framework, i.e., a multi-stakeholder and multi-Internet ecosystem (Internet of Information, Internet of Energy, and Internet of Things) with edge computing capabilities supported by cloud-level services and with clean mapping between the logical and physical entities involved and their stakeholders. In particular, this paper presents some of the results obtained by us in several European projects that refer to the development of a traffic and power network co-simulation tool for electro mobility planning, platforms for recharging services, and communication and service management architectures supporting interoperability and other qualities required for the implementation of the smart grid framework. For each contribution, this paper describes the inter-disciplinary characteristics of the proposed approaches.INDEX TERMS Smart grid, co-simulation, electro mobility, power distribution, service infrastructure, Internet of Things, arrowhead.

Big data analytics in smart grids: state‐of‐the‐art, challenges, opportunities, and future directions

“…Therefore, the future power grid should implement distributed computing and data mining architecture to reduce the computational burden at the centralised processor [115]. Recently, edge computing, a method of optimising computing performance by processing data at the edge of the network near the data source, has been gaining attention in big data applications [7, 116]. Edge computing primarily relives the communication bandwidth needed between the data source and central processing system, whereas distributed computing reduces data handling burdens by parallel processing of the information [117, 118].…”

The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm

“…This platform represents a powerful tool for assessing the effects of the transients caused by the concurrent charging of many electric vehicles on the operating conditions of the MV network and designing countermeasures against the overload of the power network components. As an example, [61,64] present the analysis of a MAS composed, on the one hand, by the intelligent electronic devices (IEDs) installed both at the HV/MV substation and near those critical branches of the network that may be overloaded due to EVs charging and, on the other hand, by the control units, connected to the communication network, each associated to the cluster of EV supply equipments (EVSEs) of a parking lot. When an IED detects an overcurrent condition (in general undervoltage conditions are quite rare in urban MV power networks), it starts to send appropriate congestion indexes to the control units of the EVSE clusters connected to a downstream bus so to reduce the maximum available power for the EVs charging and to counteract the congestion.…”

“…Each control unit communicates also with each single EVSE of the parking lot in order to allocate among the various charging EVs the maximum power that can be absorbed from the MV network taking into account the EVs specific charging characteristics and requirements. The co-simulation platform allows also for the assessment of the influence of the loss of information (represented by the block error rate) and the latency caused by background traffic in the communication links on the performances of the MAS (see [61,64] for some results relevant to the city of Bologna, Italy, and related discussion).…”

C Minor: a Semantic Publish/Subscribe Broker for the Internet of Musical Things

“…In this paper we exploit a lightweight IoT protocol for M2M communication, the Constrained Application Protocol (CoAP) [16], to build a semantic context broker, named C Minor, which is suitable for fog computing applications involving constrained devices [17]. C Minor leverages the authors' experience on the development of semantic publish/subscribe brokers (e.g., for the Smart-M3 interoperability platform [18], [19] and the SPARQL Event Processing Architecture [15]) for context-aware and IoT applications [20], [21]. The proposed approach combines the expressive power of Semantic Web technologies (RDF, RDFS, OWL and SPARQL) with the advantages of a top-class IoT protocol such as CoAP (binary data sent over UDP, resource/observe interaction pattern).…”