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            Core Concepts and Methods in Load Forecasting

            With Applications in Distribution Networks

            Thumbnail
            Author(s)
            Haben, Stephen
            Voss, Marcus
            Holderbaum, William
            Language
            English
            Show full item record
            Abstract
            This comprehensive open access book enables readers to discover the essential techniques for load forecasting in electricity networks, particularly for active distribution networks. From statistical methods to deep learning and probabilistic approaches, the book covers a wide range of techniques and includes real-world applications and a worked examples using actual electricity data (including an example implemented through shared code). Advanced topics for further research are also included, as well as a detailed appendix on where to find data and additional reading. As the smart grid and low carbon economy continue to evolve, the proper development of forecasting methods is vital. This book is a must-read for students, industry professionals, and anyone interested in forecasting for smart control applications, demand-side response, energy markets, and renewable utilization.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/163843
            Keywords
            Load forecasting; Probabilistic forecasting; Smart grid applications; Distribution networks; Low voltage; Smart meter; Demand management; Time series analysis; Time series forecasting; Smart Storage; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
            DOI
            10.1007/978-3-031-27852-5
            ISBN
            9783031278525, 9783031278518
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Cham, 2023
            Grantor
            • University of Reading
            Imprint
            Springer International Publishing
            Pages
            331
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            • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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