Searched for: subject%3A%22batteries%22
(1 - 1 of 1)
document
van der Heijden, T.J.T. (author), Palensky, P. (author), van de Giesen, N.C. (author), Abraham, E. (author)
In this manuscript, we test the operational performance decrease of a probabilistic framework for Demand Response (DR). We use Day Ahead Market (DAM) price scenarios generated by a Combined Quantile Regression Deep Neural Network (CQR-DNN) and a Non-parametric Bayesian Network (NPBN) to maximise profit of a Battery Energy Storage System (BESS)...
conference paper 2023