A Low Complexity Design Framework for NFC-RFID Inductive Coupled Antennas

International audienc

Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review

Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined with their use of large-scale data and the frequent need for near real-time de-cisions, means that Artificial Intelligence (AI) and Machine Learning (ML) — a branch of AI — have recently emerged as key technologies for enabling demand-side response. AI methods can be used to tackle various challenges, ranging from selecting the optimal set of consumers to respond, learning their attributes and pref-erences, dynamic pricing, scheduling and control of devices, learning how to incentivise participants in the DR schemes and how to reward them in a fair and economically efficient way. This work provides an overview of AI methods utilised for DR applications, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects. The papers are classified with regards to both the AI/ML algorithm(s) used and the application area in energy DR. Next, commercial initiatives are presented (including both start-ups and established companies) and large-scale innovation projects, where AI methods have been used for energy DR. The paper concludes with a discussion of advantages and potential limitations of reviewed AI techniques for different DR tasks, and outlines directions for future research in this fast-growing area

Responsive FLEXibility: a smart local energy system

The transition towards a more decarbonised, resilient and distributed energy system requires local initiatives, such as Smart Local Energy Systems (SLES), which lead communities to gain self-sufficiency and become electricity islands. Although many SLES projects have been recently deployed, only a few of them have managed to be successful, mostly due to an initial knowledge gap in the SLES planning and deployment phases. This paper leverages the knowledge from the UK’s largest SLES demonstrator in the Orkney Islands, named the Responsive FLEXibility (ReFLEX) project, to propose a framework that will help communities to successfully implement a SLES. First, this paper describes how the multi-services electrical SLES implemented in Orkney reduces the impact of the energy transition on the electrical infrastructure. We identify and discuss the main enablers and barriers to a successful SLES, based on a review of SLES projects in the UK. Second, to help future communities to implement SLES, we extend the Smart Grid Architecture Model (SGAM) into a comprehensive multi-vector Smart Local Energy Architecture Model (SLEAM) that includes all main energy services, namely power, heat and transport. This extended architecture model describes the main components and interaction layers that need to be addressed in a comprehensive SLES. Next, to inform successful deployment of SLES, an extensive list of key performance indicators for SLES is proposed and implemented for the ReFLEX project. Finally, we discuss lessons learnt from the ReFLEX project and we list required future technologies that enable communities, energy policy makers and regulatory bodies to best prepare for the energy transition

Decentralized Energy White Paper: Adaptive Local Energy Communities

No abstract available

Real-time control of distributed batteries with blockchain-enabled market export commitments

Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large UK-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator’s revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated

Angiotensin II Facilitates Breast Cancer Cell Migration and Metastasis

Breast cancer metastasis is a leading cause of death by malignancy in women worldwide. Efforts are being made to further characterize the rate-limiting steps of cancer metastasis, i.e. extravasation of circulating tumor cells and colonization of secondary organs. In this study, we investigated whether angiotensin II, a major vasoactive peptide both produced locally and released in the bloodstream, may trigger activating signals that contribute to cancer cell extravasation and metastasis. We used an experimental in vivo model of cancer metastasis in which bioluminescent breast tumor cells (D3H2LN) were injected intra-cardiacally into nude mice in order to recapitulate the late and essential steps of metastatic dissemination. Real-time intravital imaging studies revealed that angiotensin II accelerates the formation of metastatic foci at secondary sites. Pre-treatment of cancer cells with the peptide increases the number of mice with metastases, as well as the number and size of metastases per mouse. In vitro, angiotensin II contributes to each sequential step of cancer metastasis by promoting cancer cell adhesion to endothelial cells, trans-endothelial migration and tumor cell migration across extracellular matrix. At the molecular level, a total of 102 genes differentially expressed following angiotensin II pre-treatment were identified by comparative DNA microarray. Angiotensin II regulates two groups of connected genes related to its precursor angiotensinogen. Among those, up-regulated MMP2/MMP9 and ICAM1 stand at the crossroad of a network of genes involved in cell adhesion, migration and invasion. Our data suggest that targeting angiotensin II production or action may represent a valuable therapeutic option to prevent metastatic progression of invasive breast tumors

Optimisation des transferts d'énergie pour les systèmes connectés : application aux systèmes RFID communiquant en champ proche à très haut débit

The research work presented in this thesis provides solutions to help industrials to better design RFID readers and RFID tags that implement VHBR (Very High Bit Rate) protocols. Indeed, VHBR technology has a large drawback on the functionning of RFID tags as it lowers the energy available to supply the tag. First, this research work focuses on RFID reader design, and especially matching networks design. After describing a new way of assessing power transfer in Radio Frequency systems, it is shown that T matching networks as thoses proposed in ISO/IEC 10373-6 give the best results in terms of power transfer and signal integrity. Thus, a design method is proposed to correctly choose the three T matching network components that will optimize the power transfer and still meet the signal integrity requirements.Second, this thesis will focus on the design of RFID tags, by describing a new tag's antenna design method that optimize the energy harvested by the antenna and meanwhile reduce the power reflections between the antenna and the tag's chip. This design method is based on new explicit formula that compute a rectangular planar antenna inductance as a function of its geometric characteristics. This method showed very accurate results, and can become an interesting tool for industrials to speed up and optimize their antenna design procedure.Finally, a platform that measures RFID chip's impedance in every state of the chip has been designed, even during load modulation communication. The accuracy of this tool and its importance in order to achieve a good antenna design confer it a great usefulness.Dans le contexte de développement de produits sans-contact communiquant à très haut débit, dît systèmes VHBR (Very High Bit Rate), il s’avère que les cartes ou passeports VHBR, télé-alimentés à partir du lecteur qui communique avec eux, sont contraints de fonctionner avec une alimentation bien plus faible que les produits communiquant à des débits standards. Pour répondre à cette problématique de manque de puissance d’alimentation, il a été nécessaire de commencer par reprendre la théorie des lignes en l'orientant de manière à ce qu'elle permette de quantifier les transferts de puissance entre une source et une charge séparées par un média quelconque. Ensuite, ce nouveau moyen de quantification des transferts de puissance a été utilisé pour faire de l'aide à la conception des lecteurs VHBR. Ensuite, ce travail de recherche se concentre sur les cartes ou passeports VHBR. En effet, pour permettre à un tel système sans contact de fonctionner de manière télé-alimentée dans un environnement où la puissance disponible est réduite, il faut optimiser sa conception. Les solutions proposées ici consistent à déterminer la géométrie des antennes inductives qui optimisent la récupération d'énergie et le transfert de puissance vers la puce d'une carte VHBR. Ainsi, les travaux présentés dans ce manuscrit apportent des solutions globales à cette problématique de récupération d'énergie dans les objets connectés que sont les systèmes sans contact, en décrivant des méthodes de conception qui permettent d'une part de limiter les pertes de puissance au sein des lecteurs VHBR, et d'autre part d'optimiser la récupération d'énergie au sein des cartes VHBR

Optimisation des transferts d'énergie pour les systèmes connectés : application aux systèmes RFID communiquant en champ proche à très haut débit

The research work presented in this thesis provides solutions to help industrials to better design RFID readers and RFID tags that implement VHBR (Very High Bit Rate) protocols. Indeed, VHBR technology has a large drawback on the functionning of RFID tags as it lowers the energy available to supply the tag. First, this research work focuses on RFID reader design, and especially matching networks design. After describing a new way of assessing power transfer in Radio Frequency systems, it is shown that T matching networks as thoses proposed in ISO/IEC 10373-6 give the best results in terms of power transfer and signal integrity. Thus, a design method is proposed to correctly choose the three T matching network components that will optimize the power transfer and still meet the signal integrity requirements.Second, this thesis will focus on the design of RFID tags, by describing a new tag's antenna design method that optimize the energy harvested by the antenna and meanwhile reduce the power reflections between the antenna and the tag's chip. This design method is based on new explicit formula that compute a rectangular planar antenna inductance as a function of its geometric characteristics. This method showed very accurate results, and can become an interesting tool for industrials to speed up and optimize their antenna design procedure.Finally, a platform that measures RFID chip's impedance in every state of the chip has been designed, even during load modulation communication. The accuracy of this tool and its importance in order to achieve a good antenna design confer it a great usefulness.Dans le contexte de développement de produits sans-contact communiquant à très haut débit, dît systèmes VHBR (Very High Bit Rate), il s’avère que les cartes ou passeports VHBR, télé-alimentés à partir du lecteur qui communique avec eux, sont contraints de fonctionner avec une alimentation bien plus faible que les produits communiquant à des débits standards. Pour répondre à cette problématique de manque de puissance d’alimentation, il a été nécessaire de commencer par reprendre la théorie des lignes en l'orientant de manière à ce qu'elle permette de quantifier les transferts de puissance entre une source et une charge séparées par un média quelconque. Ensuite, ce nouveau moyen de quantification des transferts de puissance a été utilisé pour faire de l'aide à la conception des lecteurs VHBR. Ensuite, ce travail de recherche se concentre sur les cartes ou passeports VHBR. En effet, pour permettre à un tel système sans contact de fonctionner de manière télé-alimentée dans un environnement où la puissance disponible est réduite, il faut optimiser sa conception. Les solutions proposées ici consistent à déterminer la géométrie des antennes inductives qui optimisent la récupération d'énergie et le transfert de puissance vers la puce d'une carte VHBR. Ainsi, les travaux présentés dans ce manuscrit apportent des solutions globales à cette problématique de récupération d'énergie dans les objets connectés que sont les systèmes sans contact, en décrivant des méthodes de conception qui permettent d'une part de limiter les pertes de puissance au sein des lecteurs VHBR, et d'autre part d'optimiser la récupération d'énergie au sein des cartes VHBR

A very high bit rate test platform for ISO 14443 and interoperability tests

International audienc

Data-driven modelling of energy demand response behaviour based on a large-scale residential trial

Recent years have seen an increasing interest in Demand Response (DR), as a means to satisfy the growing flexibility needs of modern power grids. This increased flexibility is required due to the growing proportion of intermittent renewable energy generation into the energy mix, and increasing complexity in demand profiles from the electrification of transport networks. Currently, less than 2% of the global potential for demand-side flexibility is currently utilised, but a more widespread adoption of residential consumers as flexibility resources can lead to substantially higher utilisation of the demand-side flexibility potential. In order to achieve this target, acquiring a better understanding of how residential DR participants respond in DR events is essential – and recent advances in novel machine learning and statistical AI provide promising tools to address this challenge. This study provides an in-depth analysis of how residential customers have responded in incentive-based DR, utilising household-related data from a large-scale, real-world trial: the Smart Grid, Smart City (SGSC) project. Using a number of different machine learning approaches, we model the relationship between a household’s response and household-related features. Moreover, we examine the potential effects of households’ features on the residential response behaviour, and highlight a number of key insights which raise questions about the reported level of consumers’ engagement in DR schemes, and the motivation for different customers’ response level. Finally, we explore the temporal structure of the response – and although we found no supporting evidence of DR responders learning over time for the available data from this trial, the proposed methodologies could be used for longer-term longitudinal DR studies. Our study concludes with a broader discussion of our findings and potential paths for future research in this emerging area