Short term Markov corrector for building load forecasting system - Concept and case study of day-ahead load forecasting under the impact of the COVID-19 pandemic.
Energy Build
; 270: 112286, 2022 Sep 01.
Article
em En
| MEDLINE
| ID: mdl-35814481
ABSTRACT
In this paper, we present the concept and formulation of a short-term Markov corrector to an underlying day-ahead building load forecasting model. The models and the correctors are then integrated to the building supervision, control and data acquisition system to automate the self-updating and retraining processes. The proposed Markov corrector is experimentally proven to significantly improve the reactivity of the forecasting models with respect to untaught variations. Developed in a discrete manner over a continuous forecasting model, the corrector also helps to capture better the consumption peaks during the activity days. A proof-of-concept is demonstrated via the case study of the GreenER building, where the impact of the Markov correctors to the performance of the existing day-ahead load forecasting system (based on Prophet model) was analyzed during the 2021/2022 winter, under the influences of the Omicron wave of the COVID-19 pandemic.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
1_ASSA2030
Base de dados:
MEDLINE
Tipo de estudo:
Health_economic_evaluation
Idioma:
En
Revista:
Energy Build
Ano de publicação:
2022
Tipo de documento:
Article