Solar energy forecasting and optimization system for efficient renewable energy integration
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2017
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Springer Verlag
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Abstract
Solar energy forecasting represents a key issue in order to efficiently manage the supply-demand balance and promote an effective renewable energy integration. In this regard, an accurate solar energy forecast is of utmoss importance for avoiding large voltage variations into the electricity network and providing the system with mechanisms for managing the produced energy in an optimal way. This paper presents a novel solar energy forecasting and optimization approach called SUNSET which efficiently determines the optimal energy management for the next 24 h in terms of: self-consumption, energy purchase and battery energy storage for later consumption. The proposed SUNSET approach has been tested in a real solar PV system plant installed in Zamudio (Spain) and compared towards a Real-Time (RT) strategy in terms of price and energy savings obtaining attractive results.
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Publisher Copyright: © Springer International Publishing AG 2017.
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Manjarres , D , Alonso , R , Gil-Lopez , S & Landa-Torres , I 2017 , Solar energy forecasting and optimization system for efficient renewable energy integration . in O Kramer , S Madnick , W L Woon & Z Aung (eds) , Data Analytics for Renewable Energy Integration : Informing the Generation and Distribution of Renewable Energy - 5th ECML PKDD Workshop, DARE 2017, Revised Selected Papers . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 10691 LNAI , Springer Verlag , pp. 1-12 , 5th International Workshop on Data Analytics for Renewable Energy Integration, DARE 2017 , Skopje , Macedonia, The Former Yugoslav Republic of , 22/09/17 . https://doi.org/10.1007/978-3-319-71643-5_1
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