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Titlebook: Integration of Low Carbon Technologies in Smart Grids; Donato Zarrilli Book 2019 Springer Nature Switzerland AG 2019 Voltage Control in Di

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发表于 2025-3-21 18:10:15 | 显示全部楼层 |阅读模式
书目名称Integration of Low Carbon Technologies in Smart Grids
编辑Donato Zarrilli
视频video
概述Nominated as an outstanding PhD thesis by The University of Siena, Italy.Describes predictive and optimization techniques for the control of smart grids with high penetration of renewables.Discusses h
丛书名称Springer Theses
图书封面Titlebook: Integration of Low Carbon Technologies in Smart Grids;  Donato Zarrilli Book 2019 Springer Nature Switzerland AG 2019 Voltage Control in Di
描述The thesis provides different opportunities and ideas to face some current challenges in the electricity systems.  It focuses on the effective and efficient integration of distributed low carbon technologies in the grid of the future. Planning and operation problems for different clean solutions, such as market bidding strategies for intermittent energy producers, demand side management algorithms for smart buildings, and electrical storage options for network operators, are studied for facilitating the integration of renewable energy sources in the power system chain.
出版日期Book 2019
关键词Voltage Control in Distribution Networks; Demand Response Management of Smart Buildings; Model Predict
版次1
doihttps://doi.org/10.1007/978-3-319-98358-5
isbn_softcover978-3-030-07487-6
isbn_ebook978-3-319-98358-5Series ISSN 2190-5053 Series E-ISSN 2190-5061
issn_series 2190-5053
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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978-3-030-07487-6Springer Nature Switzerland AG 2019
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Integration of Low Carbon Technologies in Smart Grids978-3-319-98358-5Series ISSN 2190-5053 Series E-ISSN 2190-5061
发表于 2025-3-22 05:01:20 | 显示全部楼层
https://doi.org/10.1007/978-3-319-98358-5Voltage Control in Distribution Networks; Demand Response Management of Smart Buildings; Model Predict
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,Bidding Renewable Energy in the Electricity Market,In this chapter the problem of designing optimal bidding strategies for renewable power producers exploiting weather forecasts is addressed.
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Demand Response Management in Smart Buildings,In this chapter an optimization approach based on Model Predictive Control (MPC) for allowing the temperature control system of large buildings to participate in a DR program is proposed.
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