TY - JOUR
T1 - Energy Consumption Prediction in a Novel Automated Photovoltaic Design Platform
AU - Pereira, Tiago Cardoso
AU - Murta-Pina, João
AU - Amaral-Lopes, Rui
AU - Monteiro, Fernando
AU - Moraes, Samuel
AU - Oliveira, Francisco
N1 -
LISBOA-01-0247-FEDER-039846
PY - 2021/2/10
Y1 - 2021/2/10
N2 - This paper describes a multi-step algorithm used to predict and typify the energy consumption profile of a prosumer, allowing the automation of the design of self-consumption photovoltaic (PV) power systems in a novel platform called PV SPREAD. The algorithm uses different methodologies to address various possible scenarios of data availability. In this paper, those scenarios are addressed using nonlinear autoregressive artificial neural networks (ANN) with external inputs (NARX) to predict energy consumption. Results reveal that the proposed algorithm successfully addresses data gaps in a hotel load profile used as a case study. The results also show the limitations of NARX when residential clients are analyzed.
AB - This paper describes a multi-step algorithm used to predict and typify the energy consumption profile of a prosumer, allowing the automation of the design of self-consumption photovoltaic (PV) power systems in a novel platform called PV SPREAD. The algorithm uses different methodologies to address various possible scenarios of data availability. In this paper, those scenarios are addressed using nonlinear autoregressive artificial neural networks (ANN) with external inputs (NARX) to predict energy consumption. Results reveal that the proposed algorithm successfully addresses data gaps in a hotel load profile used as a case study. The results also show the limitations of NARX when residential clients are analyzed.
UR - http://www.scopus.com/inward/record.url?scp=85101532845&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/202123900014
DO - 10.1051/e3sconf/202123900014
M3 - Conference article
VL - 239
JO - E3S Web of Conferences
JF - E3S Web of Conferences
SN - 2555-0403
M1 - 00014
T2 - 2020 International Conference on Renewable Energy, ICREN 2020
Y2 - 25 November 2020 through 27 November 2020
ER -
