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Vatandoust, Behzad (author), Zad, Bashir Bakhshideh (author), Vallée, François (author), Toubeau, Jean François (author), Bruninx, K. (author)Demand Response (DR) programs offer flexibility that is considered to hold significant potential for enhancing power system reliability and promoting the integration of renewable energy sources. Nevertheless, the distributed nature of DR resources presents challenges in developing scalable optimization tools. This paper explores a novel data...conference paper 2023
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Vohra, Rushil (author), Rajaei, A. (author), Cremer, Jochen (author)With the increasing penetration of renewable power sources such as wind and solar, accurate short-term, nowcasting renewable power prediction is becoming increasingly important. This paper investigates the multi-modal (MM) learning and end-to-end (E2E) learning for nowcasting renewable power as an intermediate to energy management systems. MM...conference paper 2023
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Raman, C.A. (author), Hung, H.S. (author), Loog, M. (author)Free-standing social conversations constitute a yet underexplored setting for human behavior forecasting. While the task of predicting pedestrian trajectories has received much recent attention, an intrinsic difference between these settings is how groups form and disband. Evidence from social psychology suggests that group members in a...conference paper 2023
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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
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van der Hoeven, Jelmer (author), Natali, A. (author), Leus, G.J.T. (author)Forecasting time series on graphs is a fundamental problem in graph signal processing. When each entity of the network carries a vector of values for each time stamp instead of a scalar one, existing approaches resort to the use of product graphs to combine this multidimensional information, at the expense of creating a larger graph. In this...conference paper 2023
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Goedegebure, Niels (author), Hennig, R.J. (author)A higher share of renewables and electric vehicles increase the risk of congestion in electricity distribution systems. New distribution tariff designs have been proposed to prevent congestion. However, most modeling of tariff performance assumes deterministic price information. This paper proposes a method to assess the impact of price...conference paper 2022
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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
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Habeeb, B. (author), Bastidas-Arteaga, E. (author), Gervásio, H. (author), Nogal Macho, M. (author)Over the Earth’s history, the climate has changed considerably due to natural processes affecting directly the earth. In the last century, these changes have perpetrated global warming. Carbon dioxide is the main trigger for climate change as it represents approximately up to 80% of the total greenhouse gas emissions. Climate change and concrete...conference paper 2021
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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
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Arends, Eric Lacoa (author), Watson, S.J. (author), Basu, S. (author), Cheneka, B.R. (author)A series of probabilistic models were bench-marked during the European Energy Markets forecasting Competition 2020 to assess their relative accuracy in predicting aggregated Swedish wind power generation using as input historic weather forecasts from a numerical weather prediction model. In this paper, we report the results of one of these...conference paper 2020
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Shen, Qiaomu (author), Wu, Yanhong (author), Jiang, Yuzhe (author), Zeng, Wei (author), Lau, Alexis K.H. (author), Vilanova Bartroli, A. (author), Qu, Huamin (author)Recent attempts at utilizing visual analytics to interpret Recurrent Neural Networks (RNNs) mainly focus on natural language processing (NLP) tasks that take symbolic sequences as input. However, many real-world problems like environment pollution forecasting apply RNNs on sequences of multi-dimensional data where each dimension represents an...conference paper 2020
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Natali, A. (author), Isufi, E. (author), Leus, G.J.T. (author)The forecasting of multi-variate time processes through graph-based techniques has recently been addressed under the graph signal processing framework. However, problems in the representation and the processing arise when each time series carries a vector of quantities rather than a scalar one. To tackle this issue, we devise a new framework and...conference paper 2020
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Basu, S. (author), Watson, S.J. (author), Lacoa Arends, Eric (author), Cheneka, B.R. (author)A hybrid neural network model, comprising of a convolutional neural network and a multilayer perceptron network, has been developed for day-ahead forecasting of regional scale wind power production. This model requires operational weather forecasts as input and also has the capability to ingest data from ensemble forecasts. Even though the...conference paper 2020
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Reyes, O. Soto (author), Taneja, P. (author), Pielage, B. A. (author), Van Schuylenburg, M. (author)This paper presents a study carried out to first assess the impact of the Panama Canal expansion (PCE) on selected Caribbean ports, and thereafter, to examine how the ports can adapt in order to seize new opportunities created by the expansion. An applied case of long-term dynamic planning and flexibility in engineering design is presented for a...conference paper 2019
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Methenitis, G. (author), Kaisers, Michael (author), la Poutré, J.A. (author)We study mechanisms to incentivize demand response in smart energy systems. We assume agents that can respond (reduce their demand) with some probability if they prepare prior to the real-ization of the demand. Both preparation and response incur costs to agents. Previous work studies truthful mechanisms that select a minimal set of agents to...conference paper 2019
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Bauer, André (author), Lesch, Veronika (author), Versluis, L.F.D. (author), Ilyushkin, A.S. (author), Herbst, Nikolas (author), Kounev, Samuel (author)Nowadays, in order to keep track of the fast-changing requirements of Internet applications, auto-scaling is used as an essential mechanism for adapting the number of provisioned resources to the resource demand. The straightforward approach is to deploy a set of common and opensource single-service auto-scalers for each service independently....conference paper 2019
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Doole, M.M. (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)The concept of autonomous drone delivery in urban areas has gained a favorable amount of media attention over the past few years. Companies such as Amazon, Uber and Matternet are investigating the use of drones to transport parcels in order to solve the disaggregate delivery (last-mile) problem. This solution could potentially reduce vehicular...conference paper 2018
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Lago, Jesus (author), De Brabandere, Karel (author), De Ridder, Fjo (author), De Schutter, B.H.K. (author)In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without...conference paper 2018
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Sewdien, V. N. (author), Preece, R. (author), Rueda, José L. (author), van der Meijden, M.A.M.M. (author)The participation of volatile wind energy resources in the generation mix of power systems is increasing. It is therefore becoming more and more crucial for system operators to accurately predict the wind power generation across different short term horizons (5 to 60 minutes ahead) in order to adequately balance the system and maintain system...conference paper 2018
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Nespeca, V. (author), Comes, M. (author), Alfonso, Leonardo (author)The introduction of new information and communication technologies enables communities to share information and self-organize in the response to disasters. Crowd-sourcing approaches enable professional authorities to capture information from the ground in real-time. However, there is a gap between the professional and community-driven response:...conference paper 2018
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