Searched for: author%3A%22van+der+Heijden%2C+T.J.T.%22
(1 - 8 of 8)
document
van der Heijden, T.J.T. (author), van de Giesen, N.C. (author), Palensky, P. (author), Abraham, E. (author)
The Netherlands is a low-lying country situated in the Rhine-Meuse delta. A significant portion of the Netherlands is located below sea level, making the proper management of local and national waterways essential. Polders are used to manage groundwater levels, drain excess rainwater, and store water during times of drought. These polders often...
conference paper 2023
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
document
van der Heijden, T.J.T. (author), van de Giesen, N.C. (author), Palensky, P. (author), Abraham, E. (author)
The Netherlands is a low-lying country in the Rhine-Meuse delta. Because a large part of the Netherlands is situated below sea level, proper management of local and national waterways is a necessity. Polders are used to manage groundwater levels, drain excess rainwater and store water for droughts. Typically, pumping stations in local Dutch...
conference paper 2022
document
van der Heijden, T.J.T. (author), Palensky, P. (author), van de Giesen, N.C. (author), Abraham, E. (author)
In this manuscript we propose a methodology to generate electricity price scenarios from probabilistic forecasts. Using a Combined Quantile Regression Deep Neural Network, we forecast hourly marginal price distribution quantiles for the DAM on which we fit parametric distributions. A Non-parametric Bayesian Network (BN) is applied to sample from...
conference paper 2022
document
van der Heijden, T.J.T. (author), Lugt, D. (author), van Nooijen, R.R.P. (author), Palensky, P. (author), Abraham, E. (author)
Participation in demand response (DR) has been explored for many large energy-using assets based on day ahead electricity markets. In this manuscript, we propose the use of multiple electricity spot markets to enable price-based DR for open canal systems in the Netherlands, where many large pumping stations are used for flood mitigation and...
journal article 2022
document
van der Heijden, T.J.T. (author), Palensky, P. (author), Abraham, E. (author)
In this paper we propose a Quantile Regression Deep Neural Network capable of forecasting multiple quantiles in one model using a combined quantile loss function, and apply it to probabilistically forecast the prices of 8 European Day Ahead Markets. We show that the proposed loss function significantly reduces the quantile crossing problem to ...
conference paper 2021
document
van der Heijden, T.J.T. (author), Lago, Jesus (author), Palensky, P. (author), Abraham, E. (author)
In this manuscript we explore European feature importance in Day Ahead Market (DAM) price forecasting models, and show that model performance can deteriorate when too many features are included due to over-fitting. We propose a greedy algorithm to search over candidate countries for European features to be used in a DAM price forecasting model,...
journal article 2021
document
van der Heijden, T.J.T. (author), Abraham, E. (author)
Among the barriers for renewable energy penetration (SDG 7 and SDG 13) are lack of large scale storage and irregularity and unpredictability of supply. Ties van der Heijden and Edo Abraham have a vision on how water infrastructure in the Dutch delta can contribute to the energy transition with model-based optimisation and ‘demand response...
journal article 2019
Searched for: author%3A%22van+der+Heijden%2C+T.J.T.%22
(1 - 8 of 8)