Forecasting household electricity demand with hybrid machine learning-based methods: Effects of residents’ psychological preferences and calendar variables

•Forecast electricity demand considering residents’ psychological preferences.•Stationarity time series are established to avoid the impact of irregular factors.•Personalizes exogenous variables, combines correlations and importance.•A hybrid machine learning based model is built to improve forecasting performance.•Multiple implications are provided for the government and institutions.