Electricity Consumption and Generation Forecasting with Artificial Neural Networks
| dc.creator | Bâra, Adela | |
| dc.creator | Vasilica Oprea, Simona | |
| dc.date.accessioned | 2021-01-21T18:01:26Z | |
| dc.date.available | 2021-01-21T18:01:26Z | |
| dc.date.created | 2017-12-20 | |
| dc.description.abstractenglish | Nowadays, smart meters, sensors and advanced electricity tariff mechanisms such as time-of-use tariff (ToUT), critical peak pricing tariff and real time tariff enable the electricity consumption optimization for residential consumers. Therefore, consumers will play an active role by shifting their peak consumption and change dynamically their behavior by scheduling home appliances, invest in small generation or storage devices (such as small wind turbines, photovoltaic (PV) panels and electrical vehicles). Thus, the current load profile curves for household consumers will become obsolete and electricity suppliers will require dynamical load profiles calculation and new advanced methods for consumption forecast. In this chapter, we aim to present some developments of artificial neural networks for energy demand side management system that determines consumers’ profiles and patterns, consumption forecasting and also small generation estimations | spa |
| dc.format.extent | 23 páginas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.doi | 10.5772/intechopen.71239 | |
| dc.identifier.other | https://www.intechopen.com/books/advanced-applications-for-artificial-neural-networks/electricity-consumption-and-generation-forecasting-with-artificial-neural-networks | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12010/16829 | |
| dc.language.iso | eng | spa |
| dc.publisher | IntechOpen | spa |
| dc.relation.references | Adela Bâra and Simona Vasilica Oprea (December 20th 2017). Electricity Consumption and Generation Forecasting with Artificial Neural Networks, Advanced Applications for Artificial Neural Networks, Adel El-Shahat, IntechOpen, DOI: 10.5772/intechopen.71239. | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.rights.creativecommons | https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode | |
| dc.rights.local | Abierto (Texto Completo) | spa |
| dc.subject | Ingeniería | spa |
| dc.subject.lemb | Redes neuronales artificiales | spa |
| dc.subject.lemb | Energía renovable | spa |
| dc.subject.lemb | Medidores inteligentes | spa |
| dc.title | Electricity Consumption and Generation Forecasting with Artificial Neural Networks | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_2f33 | spa |
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