The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform

Maxime Montaru - One of the best experts on this subject based on the ideXlab platform.

  • From a novel classification of the Battery state of charge estimators toward a conception of an ideal one
    Journal of Power Sources, 2015
    Co-Authors: Jana Kalawoun, Frédéric Suard, Krystyna Biletska, Maxime Montaru
    Abstract:

    An efficient estimation of the State of Charge (SoC) of an Electrical Battery in a real-time context is essential for the development of an intelligent management of the Battery energy. The main performance limitations of a SoC estimator originate in limited Battery Management System hardware resources as well as in the Battery behavior cross-dependence on the Battery chemistry and its cycling conditions. This paper presents a review of methods and models used for SoC estimation and discusses their concept, adaptability and performances in real-time applications. It introduces a novel classification of SoC estimation methods to facilitate the identification of aspects to be improved to create an ideal SoC model. An ideal model is defined as the model that provides a reliable SoC for any Battery type and cycling condition , online. The benefits of the machine learning methods in providing an online adaptive SoC estimator are thoroughly detailed. Remaining challenges are specified, through which the characteristics of an ideal model can emerge.

  • Statistical analysis for understanding and predicting Battery degradations in real-life electric vehicle use
    Journal of Power Sources, 2014
    Co-Authors: Anthony Barré, Frédéric Suard, Mathias Gerard, Maxime Montaru
    Abstract:

    This paper describes the statistical analysis of recorded data parameters of Electrical Battery ageing during electric vehicle use. These data permit traditional Battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between Battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on Battery ageing phenomena. Predictive Battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and Battery ageing global observations, and also allow accurate Battery ageing diagnosis through predictive models.

  • Statistical Method Tools to Analyze Ageing Effects on Li-Ion Battery Performances
    2013
    Co-Authors: Anthony Barré, Frédéric Suard, Mathias Gerard, Maxime Montaru, Delphine Riu
    Abstract:

    This paper describes the analysis of recorded data parameters from Electrical Battery ageing during electric vehicle use. These data allow traditional Battery ageing investigation based on resulting capacity fade and resistance raise. The measured variables are examined in order to explain the Battery ageing obtained during the experiment. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present results on Battery ageing phenomena. All studies are done on real data collected from Lithium-ion Battery; thereby results demonstrate and quantify a relationship between variables and Battery ageing mechanisms.

Tamotsu Minakawa - One of the best experts on this subject based on the ideXlab platform.

  • mitigation of wind power fluctuation by combined use of energy storages with different response characteristics
    Energy Procedia, 2011
    Co-Authors: Yutaka Yoshida, Tamotsu Minakawa
    Abstract:

    Abstract This paper presents a method to deal with the fluctuation problems caused by large-scale wind power integration to a distribution power system. Two types of energy storage devices which have different response characteristics and costs - EDLC (Electrical Double Layer Capacitor) with extremely high response, long life cycle but costly and Secondary Electrical Battery with relatively low response and low cost, are considered for the purpose of mitigation of fast wind power fluctuation and power leveling, respectively. Digital simulations with a typical wind farm distribution power system model are conducted in this study, and these simulation results have illustrated the validity of the combined use of these energy storage systems.

Harumi Mcclure - One of the best experts on this subject based on the ideXlab platform.

H. Vincent Poor - One of the best experts on this subject based on the ideXlab platform.

  • Privacy‐cost trade‐offs in smart electricity metering systems
    IET Smart Grid, 2020
    Co-Authors: Giulio Giaconi, Deniz Gündüz, H. Vincent Poor
    Abstract:

    Trade-offs between privacy and cost are studied for a smart grid consumer, whose electricity consumption is monitored in almost real time by the utility provider (UP) through smart meter (SM) readings. It is assumed that an Electrical Battery is available to the consumer, which can be utilised both to achieve privacy and to reduce the energy cost by demand shaping. Privacy is measured via the mean squared distance between the SM readings and a target load profile, while time-of-use pricing is considered to compute the cost incurred. The consumer can also sell electricity back to the UP to further improve the privacy-cost trade-off. Two privacy-preserving energy management policies (EMPs) are proposed, which differ in the way the target load profile is characterised. A more practical EMP, which optimises the energy management less frequently, is also considered. Numerical results are presented to compare the privacy-cost trade-off of these EMPs, considering various privacy indicators.

  • Joint Privacy-Cost Optimization in Smart Electricity Metering Systems
    arXiv: Information Theory, 2018
    Co-Authors: Giulio Giaconi, Deniz Gündüz, H. Vincent Poor
    Abstract:

    Joint privacy-cost optimization is studied for a smart grid consumer, whose electricity consumption is monitored in almost real time by the utility provider (UP). It is assumed that an energy storage device, e.g., an Electrical Battery, is available to the consumer, which can be utilized both to achieve privacy and to reduce the energy cost by modifying the electricity consumption. Privacy is measured via the mean squared distance between the smart meter readings and a target load profile, while time-of-use pricing is considered to compute the electricity cost. The consumer also has the possibility to sell electricity back to the UP to further improve the privacy-cost trade-off. Two privacy-preserving energy management policies (EMPs) are proposed, which differ in the way the target load profile is characterized. Additionally, a simplified and more practical EMP, which optimizes the energy management less frequently, is considered. Numerical results are presented to compare the performances of these EMPs in terms of the privacy-cost trade-off they achieve, considering a number of privacy indicators.

  • SmartGridComm - Optimal demand-side management for joint privacy-cost optimization with energy storage
    2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2017
    Co-Authors: Giulio Giaconi, Deniz Gündüz, H. Vincent Poor
    Abstract:

    The smart meter (SM) privacy problem is addressed together with the cost of energy for the user. It is assumed that a storage device, e.g., an Electrical Battery, is available to the user, which can be utilized both to achieve privacy and to reduce the energy cost by modifying the energy consumption profile. Privacy is measured via the mean squared-error between the SM readings, which are reported to the utility provider (UP), and a target load; while time-of-use pricing is considered for energy cost calculation. The optimal trade-off between the achievable privacy and the energy cost is characterized by taking into account the limited capacity of the Battery as well as the capability to sell energy to the UP. Extensive numerical simulations are presented to evaluate the performance of the proposed strategy for different system settings.

Frédéric Suard - One of the best experts on this subject based on the ideXlab platform.

  • From a novel classification of the Battery state of charge estimators toward a conception of an ideal one
    Journal of Power Sources, 2015
    Co-Authors: Jana Kalawoun, Frédéric Suard, Krystyna Biletska, Maxime Montaru
    Abstract:

    An efficient estimation of the State of Charge (SoC) of an Electrical Battery in a real-time context is essential for the development of an intelligent management of the Battery energy. The main performance limitations of a SoC estimator originate in limited Battery Management System hardware resources as well as in the Battery behavior cross-dependence on the Battery chemistry and its cycling conditions. This paper presents a review of methods and models used for SoC estimation and discusses their concept, adaptability and performances in real-time applications. It introduces a novel classification of SoC estimation methods to facilitate the identification of aspects to be improved to create an ideal SoC model. An ideal model is defined as the model that provides a reliable SoC for any Battery type and cycling condition , online. The benefits of the machine learning methods in providing an online adaptive SoC estimator are thoroughly detailed. Remaining challenges are specified, through which the characteristics of an ideal model can emerge.

  • Statistical analysis for understanding and predicting Battery degradations in real-life electric vehicle use
    Journal of Power Sources, 2014
    Co-Authors: Anthony Barré, Frédéric Suard, Mathias Gerard, Maxime Montaru
    Abstract:

    This paper describes the statistical analysis of recorded data parameters of Electrical Battery ageing during electric vehicle use. These data permit traditional Battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between Battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on Battery ageing phenomena. Predictive Battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and Battery ageing global observations, and also allow accurate Battery ageing diagnosis through predictive models.

  • Statistical Method Tools to Analyze Ageing Effects on Li-Ion Battery Performances
    2013
    Co-Authors: Anthony Barré, Frédéric Suard, Mathias Gerard, Maxime Montaru, Delphine Riu
    Abstract:

    This paper describes the analysis of recorded data parameters from Electrical Battery ageing during electric vehicle use. These data allow traditional Battery ageing investigation based on resulting capacity fade and resistance raise. The measured variables are examined in order to explain the Battery ageing obtained during the experiment. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present results on Battery ageing phenomena. All studies are done on real data collected from Lithium-ion Battery; thereby results demonstrate and quantify a relationship between variables and Battery ageing mechanisms.