Paper: arXiv 2302.00411

Authors: Bartosz Uniejewski

Abstract

Accurate short-term price forecasting is essential for daily operations in electricity markets. This article introduces a new method, called Smoothing Quantile Regression (SQR) Averaging, that improves upon well-performing probabilistic forecasting schemes. To demonstrate its utility, a comprehensive study is conducted on two electricity markets, including recent data covering the COVID-19 pandemic and the Russian invasion of Ukraine. The performance of SQR Averaging is evaluated both in terms of reliability and sharpness measures, and economic benefits from a trading strategy. The latter utilizes battery storage and sets limit orders using selected quantiles of the predictive distribution. SQR Averaging leads to profit increases of up to 3.5% on average compared to the benchmark strategy based solely on point forecasts. This is strong evidence for the practical value of using probabilistic forecasts in day-ahead power trading, even in the face of the COVID-19 pandemic and geopolitical disruptions.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 6.0/10 (capped from 8.5: transaction costs not modelled; see penalty flags)
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper introduces a novel Smoothing Quantile Regression Averaging technique backed by sound mathematical formulation and extensive empirical testing across multiple electricity markets. The inclusion of a practical battery storage trading strategy during major macro disruptions (COVID-19 and geopolitical conflicts) provides strong validation of its real-world economic value.

Research Flowchart

  flowchart TD
    A[Research Goal: Improve Short-Term Probabilistic Electricity Price Forecasting & Trading Profits] --> B[Data Inputs: Electricity Market Prices including COVID-19 & Ukraine War Periods]
    B --> C[Methodology: Develop Smoothing Quantile Regression Averaging Method]
    C --> D[Model Evaluation: Assess Forecast Reliability, Sharpness, & Battery Storage Trading Strategy]
    D --> E[Key Findings: SQR Averaging Increases Day-Ahead Trading Profits by up to 3.5%]