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Coordination of distributed energy resources is critical for electricity grid management. Although nodal pricing schemes can mitigate congestion and voltage deviations, the resulting prices are not necessarily equitable. In this work, we…

Optimization and Control · Mathematics 2023-12-15 Emmanuel Balogun , Sonia Martin , Anthony Degleris , Ram Rajagopal

Electricity price forecasting is a critical tool for the efficient operation of power systems and for supporting informed decision-making by market participants. This paper explores a novel methodology aimed at improving the accuracy of…

Applications · Statistics 2025-01-13 Bartosz Uniejewski , Florian Ziel

Since the 1990s, widespread introduction of central (wholesale) electricity markets has been seen across multiple continents, driven by the search for efficient operation of the power grid through competition. The increase of renewables has…

Systems and Control · Electrical Eng. & Systems 2025-10-15 Pål Forr Austnes , Matthieu Jacobs , Lu Wang , Mario Paolone

Renewable electricity generation has grown significantly across many European power systems, leading to a greener energy mix, but also additional complexity in balancing electricity supply and demand. Unexpected differences between…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Arnaud Verstraeten , Maria Margarida Mascarenhas , Hussain Kazmi

The availability of historical data related to electricity day-ahead prices and to the underlying price formation process is limited. In addition, the electricity market in Europe is facing a rapid transformation, which limits the…

Applications · Statistics 2023-06-27 Raffaele Sgarlato

The problem of probabilistic forecasting and online simulation of real-time electricity market with stochastic generation and demand is considered. By exploiting the parametric structure of the direct current optimal power flow, a new…

Applications · Statistics 2016-06-28 Weisi Deng , Yuting Ji , Lang Tong

This paper studies the use of conformal prediction (CP), an emerging probabilistic forecasting method, for day-ahead photovoltaic power predictions to enhance participation in electricity markets. First, machine learning models are used to…

Machine Learning · Computer Science 2024-04-01 Yvet Renkema , Nico Brinkel , Tarek Alskaif

Market information events are generated intermittently and disseminated at high speeds in real-time. Market participants consume this high-frequency data to build limit order books, representing the current bids and offers for a given…

Trading and Market Microstructure · Quantitative Finance 2024-08-08 Aditya Nittur Anantha , Shashi Jain

In this paper we investigate a dynamic pricing model for constant demand elasticity where customers have a probability distribution on the number of items they order. This is a generalization from standard models which restrict customers to…

Optimization and Control · Mathematics 2018-03-01 Nyles Breecher , Richard Stockbridge

A limit order book provides information on available limit order prices and their volumes. Based on these quantities, we give an empirical result on the relationship between the bid-ask liquidity balance and trade sign and we show that…

Trading and Market Microstructure · Quantitative Finance 2012-04-09 Ban Zheng , Eric Moulines , Frédéric Abergel

This paper deals with the market-bidding problem of a cluster of price-responsive consumers of electricity. We develop an inverse optimization scheme that, recast as a bilevel programming problem, uses price-consumption data to estimate the…

Optimization and Control · Mathematics 2015-11-04 Javier Saez-Gallego , Juan M. Morales , Marco Zugno , Henrik Madsen

We study the problem of the intraday short-term volume forecasting in cryptocurrency exchange markets. The predictions are built by using transaction and order book data from different markets where the exchange takes place.…

Trading and Market Microstructure · Quantitative Finance 2020-12-03 Nino Antulov-Fantulin , Tian Guo , Fabrizio Lillo

We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a…

Trading and Market Microstructure · Quantitative Finance 2010-08-03 Guo-Hua Mu , Wei-Xing Zhou , Wei Chen , Janos Kertesz

This paper studies the fill probabilities of limit orders placed at different price levels in a limit order book. These probabilities play a central role in execution optimization, as limit orders are not guaranteed to be executed and…

Trading and Market Microstructure · Quantitative Finance 2026-02-09 Felix Lokin , Fenghui Yu

We examine the novel problem of the estimation of transaction arrival processes in the intraday electricity markets. We model the inter-arrivals using multiple time-varying parametric densities based on the generalized F distribution…

General Economics · Economics 2019-12-03 Michał Narajewski , Florian Ziel

I present an overview of some recent advancements on the empirical analysis and theoretical modeling of the process of price formation in financial markets as the result of the arrival of orders in a limit order book exchange. After…

Trading and Market Microstructure · Quantitative Finance 2021-05-04 Fabrizio Lillo

Purpose: Trading on electricity markets occurs such that the price settlement takes place before delivery, often day-ahead. In practice, these prices are highly volatile as they largely depend upon a range of variables such as electricity…

Applications · Statistics 2020-05-19 Christof Naumzik , Stefan Feuerriegel

Virtual bidding plays an important role in two-settlement electric power markets, as it can reduce discrepancies between day-ahead and real-time markets. Renewable energy penetration increases volatility in electricity prices, making…

Machine Learning · Computer Science 2024-12-03 Xuesong Wang , Sharaf K. Magableh , Oraib Dawaghreh , Caisheng Wang , Jiaxuan Gong , Zhongyang Zhao , Michael H. Liao

Accurate short-term electricity price forecasting is crucial for strategically scheduling demand and generation bids in day-ahead markets. While data-driven techniques have shown considerable prowess in achieving high forecast accuracy in…

Machine Learning · Computer Science 2025-12-05 Maria Margarida Mascarenhas , Jilles De Blauwe , Mikael Amelin , Hussain Kazmi

Build-to-order (BTO) supply chains have become common-place in industries such as electronics, automotive and fashion. They enable building products based on individual requirements with a short lead time and minimum inventory and…

Machine Learning · Computer Science 2019-05-21 Rodrigo Rivera-Castro , Ivan Nazarov , Yuke Xiang , Alexander Pletneev , Ivan Maksimov , Evgeny Burnaev