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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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12.5%25.0%37.5%50.0% · Jan 199519922001200920172026
48 results for electricity production

In this note, we present an existence result of a Nash equilibrium between electricity producers selling their production on an electricity market and buying CO2 emission allowances on an auction carbon market. The producers' strategies integrate the coupling of the two markets via the cost functions of the electricity…

2013-11-06abs ↗pdf ↗

A new method forecasts hourly electricity prices considering product dynamics and limit order book signals.

problem High volatility and imbalance in power systems due to renewable energy and flexible demand.
method Incorporates short-term features from hourly and quarter-hourly products, including limit order book and neighboring product signals.
result Features from the limit order book are most influential, and neighboring product signals improve forecast accuracy.

The study improves load forecasting for electricity consumers using advanced machine learning models.

problem Improving short-term load forecasting for effective scheduling and decision-making.
method Proposes and evaluates statistical nonlinear models, including LSTM and GRU, for 15-min frequency electricity load forecasting.
result Advanced models outperform other models in out-of-sample forecasting accuracy, as shown by the Diebold-Mariano test.

THieF improves day-ahead electricity price prediction accuracy by reconciling hourly and block forecasts.

problem Improving accuracy in predicting day-ahead electricity prices.
method Temporal hierarchy forecasting (THieF) reconciling hourly and block forecasts.
result THieF significantly improves accuracy (up to 13%) at all levels of prediction.

The study finds that low frequency macroeconomic variables are more important for short-term electricity price forecasting.

problem Improving short-term forecasting of daily electricity prices using macroeconomic variables.
method Developed a Bayesian reverse unrestricted MIDAS model to account for frequency mismatch.
result Inclusion of macroeconomic low frequency variables improves short-term forecasts more than using only surveys or industrial production data.

Copulas model cross-product effects in intraday power markets.

problem Intraday power markets' cross-product effects are not adequately addressed by existing univariate approaches.
method Copulas and latent beta regression for modeling high-dimensional intraday price return vector, with time-varying dependence parameter.
result Modeling cross-product effects improves forecasting performance.

The paper explores features from orderbooks to improve intraday electricity price forecasting.

problem Improving probabilistic forecasting of intraday electricity prices.
method Extracted 384 features from orderbooks, selected powerful features, and benchmarked models across two countries and product types.
result Revealed an asymmetric generalization phenomenon in electricity price forecasting models.

Electricity accounts for 25% of global greenhouse gas emissions. Reducing emissions related to electricity consumption requires accurate measurements readily available to consumers, regulators and investors. In this case study, we propose a new real-time consumption-based accounting approach based on flow tracing. This…

2018-12-17abs ↗pdf ↗

The recent research report of U.S. Department of Energy prompts us to re-examine the pricing theories applied in electricity market design. The theory of spot pricing is the basis of electricity market design in many countries, but it has two major drawbacks: one is that it is still based on the traditional hourly sche…

2017-10-22abs ↗pdf ↗

Deep learning improves weather modeling for electricity load forecasting.

problem Accurate load and renewable energy forecasting requires complex spatio-temporal weather modeling.
method Automated spatio-temporal feature extraction using deep neural networks.
result Deep learning outperforms traditional methods in French national load forecasting.

We consider the problem of optimal trading for a power producer in the context of intraday electricity markets. The aim is to minimize the imbalance cost induced by the random residual demand in electricity, i.e. the consumption from the clients minus the production from renewable energy. For a simple linear price impa…

2015-01-19abs ↗pdf ↗

Model equilibrium price in intraday electricity markets with uncertainty.

problem Formulate equilibrium model for intraday electricity trading with balancing constraints and uncertainty.
method Develop equilibrium model with agents' balancing constraints, forecasted consumption, production uncertainties, and Markov chain outages.
result Existence and uniqueness of equilibrium price as a martingale, with insights into price formation and impact of uncertainty.

We propose a new structural model that can compute the electricity spot and forward prices in two coupled markets with limited interconnection and multiple fuels. We choose a structural approach in order to represent some key characteristics of electricity spot prices such as their link to fuel prices, consumption leve…

2017-04-20abs ↗pdf ↗

In the following paper, we analyse the ID3_3-Price in the German Intraday Continuous electricity market using an econometric time series model. A multivariate approach is conducted for hourly and quarter-hourly products separately. We estimate the model using lasso and elastic net techniques and perform an out-of-samp…

2018-12-21abs ↗pdf ↗

Adaptive models improve electricity demand forecasting during lockdown.

problem Poor load forecasting due to sudden consumption changes during lockdown.
method Adaptive generalized additive models with Kalman filters and expert aggregation.
result Significant reduction in prediction errors compared to traditional models.

Proposes a new model for simulating electricity prices and their correlation structure.

problem Simulating and understanding the complex dynamics of intraday electricity prices.
method Develops a multidimensional statistical model based on Poisson measures, estimating three key parameters.
result Demonstrates the model's effectiveness in battery valuation through dynamic programming.

The authors characterize flexibility in power and energy markets considering time, spatiality, resource, and risk.

problem Evaluating and maximizing flexibility in power systems and markets.
method Characterization of flexibility dimensions (time, spatiality, resource, risk) and their interrelations with flexibility assets, products, and services.
result Flexibility should be evaluated based on multiple dimensions for efficient power systems and markets.

The paper models quanto weather and energy derivatives using Ornstein-Uhlenbeck processes and develops methods to hedge them.

problem Valuation and hedging of quanto derivatives on temperature and electricity.
method Developed a coupled model using Ornstein-Uhlenbeck processes and Conditional Least Square method for parameter estimation.
result Explicit and semi-explicit formulas for quanto options and hedging strategies are derived.

Electricity production via solar energy is tackled via short-term forecasts and risk management. Our main tool is a new setting on time series. It allows the definition of "confidence bands" where the Gaussian assumption, which is not satisfied by our concrete data, may be abandoned. Those bands are quite convenient an…

2016-02-19abs ↗pdf ↗

A method for multidimensional probabilistic electricity market forecasting is proposed.

problem Uncertainty in simultaneous multivariate predictions of electricity markets.
method Repeated resampling to estimate uncertainty of simultaneous multivariate predictions.
result The method provides highly accurate predictions and gains are largest when considering functions of variables.

Develops a new model for day-ahead electricity prices using ambit fields.

problem The high-dimensional panel structure of electricity spot prices in European zones.
method Formulates a continuous time framework as an ambit field indexed by a cylinder surface, embedding intrinsic dependence structures.
result The model allows for pricing of derivatives on individual delivery periods, making products like spreads analytically tractable.

Electrostatic systems with specific tensors are locally conformally flat.

problem Understanding the geometry of electrostatic systems with special tensors.
method Proving local conformal flatness for electrostatic manifolds with divergence-free Bach tensor.
result Three-dimensional electrostatic manifolds with divergence-free Bach tensor are locally conformally flat.

Study on implied certainty equivalent rates in financial markets and electric vehicles.

problem Investment risk in financial markets.
method Mathematical derivation of implied certainty equivalent rate, empirical analysis of stock and option data.
result Positive implied certainty equivalent rates are more suitable for investment than negative ones, but higher values increase risk.

Research focuses on predicting electricity prices with complex models considering probabilistic forecasts.

problem Challenging task due to market dynamics and weather and business activity dependence.
method Shift from econometric to statistical/machine learning models, considering probabilistic forecasts.
result More accurate predictions with complex models and probabilistic measures.

We consider the reduction along two compact directions of a twisted N=4 gauge theory on a 4-dimensional orientable manifold which is not a global product of two surfaces but contains a non-orientable surface. The low energy theory is a sigma-model on a 2-dimensional worldsheet with a boundary which lives on branes cons…

2018-04-30abs ↗pdf ↗

Study identifies regions where scoring rules reliably detect forecast errors.

problem Insufficient reliability of scoring rules in evaluating multivariate probabilistic forecasts.
method Systematic finite-sample analysis of proper scoring rules on synthetic and real-world data.
result Identified regions of reliability for scoring rules in time-series forecasting.

The study finds obstructions for certain Weyl curvature tensors on manifolds.

problem Can manifolds admit metrics with purely electric or magnetic Weyl tensors?
method Analyzes algebraic curvature tensors and their Pontryagin classes on scalar product spaces.
result Obstructions to the existence of metrics with PE or PM Weyl tensors in top-degree cohomology.

The paper analyzes MENA region's energy consumption and policy needs for renewable energy.

problem High dependency on oil and low renewable energy penetration in MENA region.
method Analysis of World Bank datasets and policy portfolio in MENA countries.
result MENA region has high potential for solar energy but faces challenges in decoupling economic growth from energy consumption.

We study the situation of an agent who can trade on a financial market and can also transform some assets into others by means of a production system, in order to price and hedge derivatives on produced goods. This framework is motivated by the case of an electricity producer who wants to hedge a position on the electr…

2011-12-20abs ↗pdf ↗