Probabilistic forecasting of power system imbalance using neural network-based ensembles

arXiv:2404.14836v1 Announce Type: cross
Abstract: Keeping the balance between electricity generation and consumption is becoming increasingly challenging and costly, mainly due to the rising share of renewables, electric vehicles and heat pumps and electrification of industrial processes. Accurate imbalance forecasts, along with reliable uncertainty estimations, enable transmission system operators (TSOs) to dispatch appropriate reserve volumes, reducing balancing costs. Further, market parties can use these probabilistic forecasts to design strategies that exploit asset flexibility to help balance the grid, generating revenue …

abstract arxiv balance consumption cs.lg cs.sy eess.sy electric electricity electric vehicles electrification estimations forecasting heat industrial network neural network operators power processes renewables type uncertainty vehicles