Spatial Load Forecasting With Communication Failure Using Time-Forward Kriging

Power transmission and distribution losses – A model based on available empirical data and future trends for all countries globally

“…The more years into the future the trend is approximated, the less accurate this method is. Usually, short-term prognoses are used [14], so there is need for a long-term estimation method.…”

Robust Restoration Decision-Making Model for Distribution Networks Based on Information Gap Decision Theory

“…Therefore, the final restoration results would be worse than expected or even unfeasible. Very short-term and short-term load forecasting methodologies have been developed [15]- [19] to predict load demand in hour-ahead with acceptable accuracy. However, the forecasted load is the total load of distribution network or substation but not individual load distributed on the feeders.…”

“…To make this constraint solvable, (19) can be replaced by the following, where sij are Boolean variables [10]:…”

From Load to Net Energy Forecasting: Short-Term Residential Forecasting for the Blend of Load and PV Behind the Meter

“…In other words, feature selection, such as determining the number of lagged and moving average variables, is the central task in such an approach [10]. Moreover, the idea of taking advantage of other regions' load profile to make the forecast for a specific location is studied in [11], where the time-forward kriging method is used for the spatial load forecasting concept. The method tries to find the cross-correlation and auto-correlation among various load profiles at the system level.…”