TY - CONF A1 - Lang, Christian A1 - Steinborn, Florian A1 - Steffens, Oliver A1 - Lang, Elmar Wolfgang T1 - Electricity Load Forecasting - An Evaluation of Simple 1D-CNN Network Structures T2 - International Conference on Time Series and Forecasting (ITISE 2019), Proceedings of Papers Vol. 2, 25-27 September 2019, Granada (Spain) N2 - This paper presents a convolutional neural network (CNN)which can be used for forecasting electricity load profiles 36 hours intothe future. In contrast to well established CNN architectures, the inputdata is one-dimensional. A parameter scanning of network parameters isconducted in order to gain information about the influence of the kernelsize, number of filters, and dense size. The results show that a goodforecast quality can already be achieved with basic CNN architectures.The method works not only for smooth sum loads of many hundredconsumers, but also for the load of apartment buildings KW - energy load forecasting KW - STLF KW - neural networks KW - CNN KW - con-volutional networks Y1 - 2021 UR - https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/1664 UR - https://nbn-resolving.org/urn:nbn:de:bvb:898-opus4-16649 UR - https://arxiv.org/abs/1911.11536 UR - http://itise.ugr.es/ITISE2019_vol2.pdf SN - 978-84-17970-78-9 SP - 797 EP - 806 ER -