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oapen-20.500.12657-630022024-03-28T08:18:50Z Core Concepts and Methods in Load Forecasting Haben, Stephen Voss, Marcus Holderbaum, William 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 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. 2023-05-16T15:06:41Z 2023-05-16T15:06:41Z 2023 book ONIX_20230516_9783031278525_31 9783031278525 9783031278518 https://library.oapen.org/handle/20.500.12657/63002 eng application/pdf n/a 978-3-031-27852-5.pdf https://link.springer.com/978-3-031-27852-5 Springer Nature Springer International Publishing 10.1007/978-3-031-27852-5 10.1007/978-3-031-27852-5 6c6992af-b843-4f46-859c-f6e9998e40d5 fb471c48-61d1-40b5-a8d7-7abd9278f351 9783031278525 9783031278518 Springer International Publishing 331 Cham [...] University of Reading UoR open access
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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.
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