377 citations · 724 across the 41 of their papers we have counts for
11 papers · 1 filter
On the Efficiency of Energy Markets with Non-Merchant Storage
Linde Frölke, Eléa Prat, Pierre Pinson +2
Energy market designs with non-merchant storage have been proposed in recent years, with the aim of achieving optimal market integration of storage. In order to handle the time-lin…
Robust Generation Dispatch with Purchase of Renewable Power and Load Predictions
Rui Xie, Pierre Pinson, Yin Xu +1
The increasing use of renewable energy sources (RESs) and responsive loads has made power systems more uncertain. Meanwhile, thanks to the development of advanced metering and fore…
Privacy-Preserving Convex Optimization: When Differential Privacy Meets Stochastic Programming
Vladimir Dvorkin, Ferdinando Fioretto, Pascal Van Hentenryck +2
Convex optimization finds many real-life applications, where--optimized on real data--optimization results may expose private data attributes (e.g., individual health records, comm…
Distributionally robust trading strategies for renewable energy producers
Pierre Pinson
Renewable energy generation is offered through electricity markets, quite some time in advance. This then leads to a problem of decision-making under uncertainty, which may be seen…
Online Decision Making for Trading Wind Energy
Miguel Angel Muñoz, Pierre Pinson, Jalal Kazempour
We propose and develop a new algorithm for trading wind energy in electricity markets, within an online learning and optimization framework. In particular, we combine a component-w…
Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach
Honglin Wen, Pierre Pinson, Jinghuan Ma +2
We present a data-driven approach for probabilistic wind power forecasting based on conditional normalizing flow (CNF). In contrast with the existing, this approach is distribution…
Strategic Coalition for Data Pricing in IoT Data Markets
Shashi Raj Pandey, Pierre Pinson, Petar Popovski
This paper considers a market for trading Internet of Things (IoT) data that is used to train machine learning models. The data, either raw or processed, is supplied to the market…
An adversarially robust data-market for spatial, crowd-sourced data
Aida Manzano Kharman, Christian Jursitzky, Quan Zhou +4
We describe an architecture for a decentralised data market for applications in which agents are incentivised to collaborate to crowd-source their data. The architecture is designe…
A Market for Trading Forecasts: A Wagering Mechanism
Aitazaz Ali Raja, Pierre Pinson, Jalal Kazempour +1
In many areas of industry and society, e.g., energy, healthcare, logistics, agents collect vast amounts of data that they deem proprietary. These data owners extract predictive inf…
Wind energy forecasting with missing values within a fully conditional specification framework
Honglin Wen, Pierre Pinson, Jie Gu +1
Wind power forecasting is essential to power system operation and electricity markets. As abundant data became available thanks to the deployment of measurement infrastructures and…
Chance-Constrained Generic Energy Storage Operations under Decision-Dependent Uncertainty
Ning Qi, Pierre Pinson, Mads R. Almassalkhi +2
Compared with large-scale physical batteries, aggregated and coordinated generic energy storage (GES) resources provide low-cost, but uncertain, flexibility for power grid operatio…