Extracting physical power plant parameters from historical behaviour

TL;DR

This paper introduces a novel method to estimate key physical parameters of thermal power plants using only publicly available market data by solving a bilevel optimization problem that aligns model outputs with historical production.

Contribution

The paper presents a new approach to extract power plant parameters solely from publicly available data, improving fundamental power market modeling accuracy.

Findings

Successfully estimates plant efficiency, costs, and start-up parameters

Matches historical production data closely with optimized parameters

Applicable to the British electricity market

Abstract

The information needed for fundamental modelling of the power markets -- the efficiency, start-up, fixed, and variable operating costs of each power plant -- is not publicly available. These parameters are usually estimated by considering the type of technology and the age of a power plant. We present a method to extract these parameters for thermal power plants on the British electricity market using only the publicly available data. For each power plant, we solve a bilevel optimisation problem, where the inner level solves the Unit Commitment (UC) problem and outputs the optimal schedule given the prices of fuel, emissions, electricity, and the unknown plant parameters. The outer level then optimises over the plant parameters matching the historical production of each plant as closely as possible.