Volume 65

Data Driven Modelling for Informed Decision-making in the Coupled Energy Market and Emissions Trading Scheme Jingyuan Hong, Weiqi Hua

Abstract

The UK’s commitment to achieving net-zero emissions by 2050 necessitates navigating the impacts of rising carbon prices on its electricity market and the generation companies that operate within it. Maintaining electricity price stability and generator competitiveness under increasing carbon costs is a key challenge. This study examines the impact of the UK Emissions Trading Scheme (ETS) on the electricity market and the profitability of generators. We build a data-driven framework coupling an ETS allowance-wholesale market auction module with a merit-order dispatch model and a firm-level valuation module (cash flow, NPV). Using monthly fuel, carbon and plant data, we compute technology-specific marginal costs, simulate market clearing, and evaluate company cash flows. Our findings reveal that wholesale prices follow with marginal costs: in our simulations for gas-fired units, fuel explains 40–50% of the marginal cost and carbon 20–35%. When fuel or carbon costs rise, the traditional power plants will change accordingly, and the price of electricity will also increase. Furthermore, due to the energy-transition investment, which requires high upfront capital expenditures and a multiyear payback horizon, a negative cash flow, paralleling the declining NPV of traditional generation companies, is illustrated in our results.

Keywords Emission trading scheme, Net-zero, Wholesale market, Generation company, energy economics.