Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Internet-of-Things Approaches

To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform

A Novel MAC Protocol for Low Datarate Cooperative Mobile Robot Teams

Cooperative mobile robot applications enable robots to perform tasks that are more complex than those that each single robot can perform alone. In this application context, communication networks play a very important role, as they have to cope with strict requirements (e.g., in terms of mobility, reliability, and bounded latencies). Recent cooperative robot applications foresee the support of low datarate communication technologies, that provide, among other benefits, lower energy consumption and easy integration with Wireless Sensor Networks (WSNs). Unfortunately, the state-of-the-art solutions either entail high costs and complexity or are not suitable for low data rate communications. Consequently, novel solutions for cooperating robots are required. For this reason, this paper presents RoboMAC, a new MAC protocol for mobile cooperating robots that enables the integration of robots with WSNs, supports mobility and real-time communications, and provides high scalability. The paper also presents a proof-of-concept implementation that proves the feasibility of the RoboMAC protocol on COTS devices

Kinetics of isotropic to string-like phase switching in electrorheological fluids of nanocubes

Applying an electric field to polarisable colloidal particles, whose permittivity differs from that of the dispersing medium, generates induced dipoles that promote the formation of string-like clusters and ultimately alter the fluid mechanical and rheological properties. Complex systems of this kind, whose electric-field-induced rheology can be manipulated between that of viscous and elastic materials, are referred to as electrorheological fluids. By dynamic Monte Carlo simulations, we investigate the dynamics of self-assembly of dielectric nanocubes upon application of an electric field. Switching the field on induces in-particle dipoles and, at sufficiently large field intensity, leads to string-like clusters of variable length across a spectrum of volume fractions. The kinetics of switching from the isotropic to the string-like state suggests the existence of two mechanisms, the first related to the nucleation of chains and the second to the competition between further merging and separation. We characterise the transient unsteady state by following the chain length distribution and analysing the probability of transition of nanocubes from one chain to another over time. Additionally, we employ passive microrheology to gain an insight into the effect of the electric field on the viscoelastic response of our model fluid. Not only do we observe that it becomes more viscoelastic in the presence of the field, but also that its viscoelasticity assumes an anisotropic signature, with both viscous and elastic moduli in planes perpendicular to the external field being larger than those along it.Leverhulme Trust Research Project Grant RPG-2018-415“Maria Zambrano Senior” financed by the European Union within the NextGenerationEU program and the Spanish Ministry of Universitie

Active microrheology of colloidal suspensions of hard cuboids

By performing dynamic Monte Carlo simulations, we investigate the microrheology of isotropic suspensions of hard-core colloidal cuboids. In particular, we infer the local viscoelastic behaviour of these fluids by studying the dynamics of a probe spherical particle that is incorporated in the host phase and is dragged by an external force. This technique, known as active microrheology, allows one to characterise the microscopic response of soft materials upon application of a constant force, whose intensity spans here three orders of magnitude. By tuning the geometry of cuboids from oblate to prolate as well as the system density, we observe different responses that are quantified by measuring the effective friction perceived by the probe particle. The resulting friction coefficient exhibits a linear regime at forces that are much weaker and larger than the thermal forces, whereas a non-linear, force-thinning regime is observed at intermediate force intensities.Malaysian Government Agency Majlis Amanah RakyatLeverhulme Trust Research (Project Grant No. RPG-2018-415)NextGenerationEU progra

Design and development of a co-simulation platform for Multi-Energy System analysis

Multi-Energy Systems (MES) are complex systems where heterogenous energy vectors (e.g. electricity, heat exchanging fluids, natural gas) interact together in such a multi-faceted way that they are very difficult to be analysed comprehensively. Starting from a literature analysis, we identified the main challenges to be addressed to analyse in-depth these systems and let them interoperate in an efficient interconnection: i) the multi-fuel perspective to analyse the different input that a MES requires, ii) the multi-service perspective to identify the output of MES operations, iii) the multi-scale perspective to scale the analysis from small environments up to large scale scenarios (e.g. house, district, city, region, state), iv) the multi-time perspective to harmonize and synchronize different operational timings, v) the energy network perspective to take into account different vector’s distribution and transmission systems, vi) the ICT perspective to monitor and manage the overall system through data signalling, and vii) the economic and business perspective to study the impact of new solutions and services on the marketplace. These perspectives reflect on the difficult effort needed to simulate MES to assess their efficiency from an operational and planning viewpoint. Standalone solutions have been proposed in literature to analyse and simulate MES. However, these solutions focus only on some of the above-mentioned perspectives. Other solutions are more complete and allows analysis of all the aspects required by MES. Often, these solutions follow a vertical design in different field of technology (e.g. electrical and thermal engineering, distribution and transmission grid management and energy market analysis). Hence, MES scenario developers must dedicate a steep learning curve to master these solutions. In this work, we propose a co-simulation platform to simulate all the above-mentioned perspectives of a MES. The platform will allow to run energy-related simulations of specific elements of a MES, or to combine them in a homogenous simulation environment. The co-simulation platform will offer different functionalities to manage MES simulation, connecting in a plug-and-play fashion different software models, hardware and real-world devices. The functionalities will take into account: i) the scenario generation to design a MES interconnecting different ready-to-use models, ii) the simulation step and time management to manage the simulation of each model in a distributed simulation environment, iii) the exchange of information among different simulators, and iv) the optimization process to reach the best efficiency for a MES scenario

Non-Intrusive Load Disaggregation of Industrial Cooling Demand with LSTM Neural Network

As the telecommunication industry becomes more and more energy intensive, energy efficiency actions are crucial and urgent measures to achieve energy savings. The main contribution to the energy demand of buildings devoted to the operation of the telecommunication network is cooling. The main issue in order to assess the impact of cooling equipment energy consumption to support energy managers with awareness over the buildings energy outlook is the lack of monitoring devices providing disaggregated load measurements. This work proposes a Non-Intrusive Load Disaggregation (NILD) tool that exploits a literature-based decomposition with an innovative LSTM Neural Network-based decomposition algorithm to assess cooling demand. The proposed methodology has been employed to analyze a real-case dataset containing aggregated load profiles from around sixty telecommunication buildings, resulting in accurate, compliant, and meaningful outcomes

A comparison study of co-simulation frameworks for multi-energy systems: the scalability problem

The transition to a low-carbon society will completely change the structure of energy systems from a standalone hierarchical centralised vision to cooperative and dis- tributed Multi-Energy Systems. The analysis of these complex systems requires the collaboration of researchers from different disciplines in the energy, ICT, social, economic, and political sectors. Combining such disparate disciplines into a single tool for modeling and analyzing such a complex environment as a Multi-Energy System requires tremendous effort. Researchers have overcome this effort by using co-simulation techniques that give the possibility of integrating existing domain-specific simulators in a single environment. Co-simulation frameworks, such as Mosaik and HELICS, have been developed to ease such integration. In this context, an additional challenge is the different temporal and spatial scales that are involved in the real world and that must be addressed during co-simulation. In particular, the huge number of heterogeneous actors populating the system makes it difficult to represent the system as a whole. In this paper, we propose a comparison of the scalability performance of two major co-simulation frameworks (i.e. HELICS and Mosaik) and a particular implementation of a well-known multi-agent systems library (i.e. AIOMAS). After describing a generic co-simulation framework infrastructure and its related challenges in managing a distributed co-simulation environment, the three selected frameworks are introduced and compared with each other to highlight their principal structure. Then, the scalability problem of co-simulation frameworks is introduced presenting four benchmark configurations to test their ability to scale in terms of a number of running instances. To carry out this comparison, a simplified multi-model energy scenario was used as a common testing environment. This work helps to understand which of the three frameworks and four configurations to select depending on the scenario to analyse. Experimental results show that a Multi-processing configuration of HELICS reaches the best performance in terms of KPIs defined to assess the scalability among the co-simu- lation frameworks

COMET: Co-simulation of Multi-Energy Systems for Energy Transition

The ongoing energy transition to reduce carbon emissions presents some of the most formidable challenges the energy sector has ever experienced, requiring a paradigm change that involves diverse players and heterogeneous concerns, includ- ing regulations, economic drivers, societal, and environmental aspects. Central to this transition is the adoption of integrated multi-energy systems (MES) to efficiently produce, distribute, store, and convert energy among different vectors. A deep understanding of MES is fundamental to harness the potential for energy savings and foster energy transition towards a low carbon future. Unfortunately, the inherent complexity of MES makes them extremely difficult to analyze, understand, design and optimize. This work proposes a digital twin co-simulation platform that provides a structured basis to design, develop and validate novel solutions and technologies for multi-energy system. The platform will enable the definition of a virtual representation of the real-world (digital twin) as a composition of models (co-simulation) that analyze the environment from multiple viewpoints and at different spatio-temporal scales

Multi-Hop Real-Time Communications Over Bluetooth Low Energy Industrial Wireless Mesh Networks

Industrial wireless sensor networks (IWSNs) are used to acquire sensor data that need real-time processing, therefore they require predictable behavior and real-time guarantees. To be cost effective, IWSNs are also expected to be low cost and low power. In this context, Bluetooth low energy (BLE) is a promising technology, as it allows implementing low-cost industrial networks. As BLE is a short-range technology, a multihop mesh network is needed to cover a large area. Nevertheless, the recently published Bluetooth mesh networking specifications do not provide support for real-time communications over multihop mesh networks. To overcome this limitation, this paper proposes the multihop real-time BLE (MRT-BLE) protocol, a real-time protocol developed on top of BLE, that allows for bounded packet delays over mesh networks. MRT-BLE also provides priority support. This paper describes in detail the MRT-BLE protocol and how to implement it on commercial-off-the-shelf devices. Two kinds of performance evaluation for the MRT-BLE protocol are provided. The first one is a worst case end-to-end delay analysis, while the second one is based on the experimental results obtained through measurements on a real testbed