The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Tseryieth Chen - One of the best experts on this subject based on the ideXlab platform.

  • a comparative study of Energy Utilization efficiency between taiwan and china
    Energy Policy, 2010
    Co-Authors: Tseryieth Chen
    Abstract:

    This paper employs data envelopment analysis to evaluate Energy Utilization efficiency between China and Taiwan from 2002 to 2007. The most important contributions of this paper are the clear description of the systematic process of Energy Utilization efficiency, the efficiency comparison between China and Taiwan, the remarkable demonstration of their outputs through two non-desirable outputs (CO2 emissions and SO2 emissions) in the data envelopment analysis framework, and the valuable results and insights gained from the application of economic development and environmental protection. Empirical results show that the Eastern region of China enjoy higher Energy Utilization efficiency than the Western region. Energy Utilization efficiency in Taiwan is higher than that in the Eastern region of China. In China, CO2 emissions were 11.28% greater than they should be (from 2002 to 2007). By contrast, CO2 emissions in Taiwan were only 1.50% in excess of what they should be since Taiwan began conducting an uninterrupted Energy-saving policy and a CO2 emission regulation policy (Bureau of Energy, Ministry of Economic Affairs, 2009). Finally, this study employs the business strategy matrix constructed by the Boston Consulting Group (BCG Matrix) to illustrate individual evidence of the relationship between economic development efficiency and greenhouse gas efficiency.

B. Mu - One of the best experts on this subject based on the ideXlab platform.

  • Flexible Grouping for Enhanced Energy Utilization Efficiency in Battery Energy Storage Systems
    Energies, 2016
    Co-Authors: W. Diao, H Liang, Jiuchun Jiang, Caiping Zhang, Yan Jiang, Le Yi Wang, B. Mu
    Abstract:

    As a critical subsystem in electric vehicles and smart grids, a battery Energy storage system plays an essential role in enhancement of reliable operation and system performance. In such applications, a battery Energy storage system is required to provide high Energy Utilization efficiency, as well as reliability. However, capacity inconsistency of batteries affects Energy Utilization efficiency dramatically; and the situation becomes more severe after hundreds of cycles because battery capacities change randomly due to non-uniform aging. Capacity mismatch can be solved by decomposing a cluster of batteries in series into several low voltage battery packs. This paper introduces a new analysis method to optimize Energy Utilization efficiency by finding the best number of batteries in a pack, based on capacity distribution, order statistics, central limit theorem, and converter efficiency. Considering both battery Energy Utilization and power electronics efficiency, it establishes that there is a maximum Energy Utilization efficiency under a given capacity distribution among a certain number of batteries, which provides a basic analysis for system-level optimization of a battery system throughout its life cycle. Quantitative analysis results based on aging data are illustrated, and a prototype of flexible Energy storage systems is built to verify this analysis.

  • Flexible grouping for enhanced Energy Utilization efficiency in battery Energy storage systems
    Energies, 2016
    Co-Authors: W. Diao, Jishen Jiang, Chengning Zhang, L C Wang, H Liang, Yu Jiang, B. Mu
    Abstract:

    © 2016 by the authors; licensee MDPI.As a critical subsystem in electric vehicles and smart grids, a battery Energy storage system plays an essential role in enhancement of reliable operation and system performance. In such applications, a battery Energy storage system is required to provide high Energy Utilization efficiency, as well as reliability. However, capacity inconsistency of batteries affects Energy Utilization efficiency dramatically; and the situation becomes more severe after hundreds of cycles because battery capacities change randomly due to non-uniform aging. Capacity mismatch can be solved by decomposing a cluster of batteries in series into several low voltage battery packs. This paper introduces a new analysis method to optimize Energy Utilization efficiency by finding the best number of batteries in a pack, based on capacity distribution, order statistics, central limit theorem, and converter efficiency. Considering both battery Energy Utilization and power electronics efficiency, it establishes that there is a maximum Energy Utilization efficiency under a given capacity distribution among a certain number of batteries, which provides a basic analysis for system-level optimization of a battery system throughout its life cycle. Quantitative analysis results based on aging data are illustrated, and a prototype of flexible Energy storage systems is built to verify this analysis.

W. Diao - One of the best experts on this subject based on the ideXlab platform.

  • Flexible Grouping for Enhanced Energy Utilization Efficiency in Battery Energy Storage Systems
    Energies, 2016
    Co-Authors: W. Diao, H Liang, Jiuchun Jiang, Caiping Zhang, Yan Jiang, Le Yi Wang, B. Mu
    Abstract:

    As a critical subsystem in electric vehicles and smart grids, a battery Energy storage system plays an essential role in enhancement of reliable operation and system performance. In such applications, a battery Energy storage system is required to provide high Energy Utilization efficiency, as well as reliability. However, capacity inconsistency of batteries affects Energy Utilization efficiency dramatically; and the situation becomes more severe after hundreds of cycles because battery capacities change randomly due to non-uniform aging. Capacity mismatch can be solved by decomposing a cluster of batteries in series into several low voltage battery packs. This paper introduces a new analysis method to optimize Energy Utilization efficiency by finding the best number of batteries in a pack, based on capacity distribution, order statistics, central limit theorem, and converter efficiency. Considering both battery Energy Utilization and power electronics efficiency, it establishes that there is a maximum Energy Utilization efficiency under a given capacity distribution among a certain number of batteries, which provides a basic analysis for system-level optimization of a battery system throughout its life cycle. Quantitative analysis results based on aging data are illustrated, and a prototype of flexible Energy storage systems is built to verify this analysis.

  • Flexible grouping for enhanced Energy Utilization efficiency in battery Energy storage systems
    Energies, 2016
    Co-Authors: W. Diao, Jishen Jiang, Chengning Zhang, L C Wang, H Liang, Yu Jiang, B. Mu
    Abstract:

    © 2016 by the authors; licensee MDPI.As a critical subsystem in electric vehicles and smart grids, a battery Energy storage system plays an essential role in enhancement of reliable operation and system performance. In such applications, a battery Energy storage system is required to provide high Energy Utilization efficiency, as well as reliability. However, capacity inconsistency of batteries affects Energy Utilization efficiency dramatically; and the situation becomes more severe after hundreds of cycles because battery capacities change randomly due to non-uniform aging. Capacity mismatch can be solved by decomposing a cluster of batteries in series into several low voltage battery packs. This paper introduces a new analysis method to optimize Energy Utilization efficiency by finding the best number of batteries in a pack, based on capacity distribution, order statistics, central limit theorem, and converter efficiency. Considering both battery Energy Utilization and power electronics efficiency, it establishes that there is a maximum Energy Utilization efficiency under a given capacity distribution among a certain number of batteries, which provides a basic analysis for system-level optimization of a battery system throughout its life cycle. Quantitative analysis results based on aging data are illustrated, and a prototype of flexible Energy storage systems is built to verify this analysis.

Jong-moon Chung - One of the best experts on this subject based on the ideXlab platform.

  • Efficient Energy Utilization with time constraints in mobile time varying channels
    IEEE Transactions on Vehicular Technology, 2000
    Co-Authors: J.j. Metzner, Jong-moon Chung
    Abstract:

    In this paper, the efficiency in Energy Utilization under time constraints is compared between two data transmission strategies: (1) transmission through sending a fixed number of copies, and (2) the ARQ technique. The analysis includes a case where each packet repetition is decoded separately, and cases where a combined decision is used. (1) For constant channel conditions and no combining, results are compared for various specifications of probability of failure (P) and maximum number (n) of transmissions. There is a large saving of Energy for the ARQ technique, which increases greatly for smaller P values and significantly for larger n. (2) Variable channel conditions and decision combining techniques are assumed for two sub-cases: (a) fast fading channel with a Rayleigh distribution, where it is assumed that successive transmissions or copies relating to a given packet experience independent channel conditions. (b) lognormally shadowed Rayleigh slow fading channel, where successive transmissions or copies relating to a given packet experience identical channel conditions. The (2a) case yields a substantial Energy saving compared to sending fixed multiple copies, though not as great as the noncombining case (1). The (2b) case shows a very large saving in Energy Utilization with some examples of about a 20:1 or more factor reduction in Energy Utilization when the strategy includes increasing the Energy increments with successive transmissions.

Dongyuan Zhao - One of the best experts on this subject based on the ideXlab platform.

  • core shell structured titanium dioxide nanomaterials for solar Energy Utilization
    Chemical Society Reviews, 2018
    Co-Authors: Wei Li, Ahmed A Elzatahry, Dhaifallah Aldhayan, Dongyuan Zhao
    Abstract:

    Because of its unmatched resource potential, solar Energy Utilization currently is one of the hottest research areas. Much effort has been devoted to developing advanced materials for converting solar Energy into electricity, solar fuels, active chemicals, or heat. Among them, TiO2 nanomaterials have attracted much attention due to their unique properties such as low cost, nontoxicity, good stability and excellent optical and electrical properties. Great progress has been made, but research opportunities are still present for creating new nanostructured TiO2 materials. Core–shell structured nanomaterials are of great interest as they provide a platform to integrate multiple components into a functional system, showing improved or new physical and chemical properties, which are unavailable from the isolated components. Consequently, significant effort is underway to design, fabricate and evaluate core–shell structured TiO2 nanomaterials for solar Energy Utilization to overcome the remaining challenges, for example, insufficient light absorption and low quantum efficiency. This review strives to provide a comprehensive overview of major advances in the synthesis of core–shell structured TiO2 nanomaterials for solar Energy Utilization. This review starts from the general protocols to construct core–shell structured TiO2 nanomaterials, and then discusses their applications in photocatalysis, water splitting, photocatalytic CO2 reduction, solar cells and photothermal conversion. Finally, we conclude with an outlook section to offer some insights on the future directions and prospects of core–shell structured TiO2 nanomaterials and solar Energy conversion.