Investment appraisal of cost-optimal and near-optimal pathways for the UK electricity sector transition to 2050

Abstract

Deep decarbonisation of the electricity sector is central to achieving the United Kingdom's (UK) climate policy targets for 2050 and meeting its international commitments under the Paris Agreement. While the overall strategy for decarbonising the energy system has been well established in previous studies, there remain deep uncertainties around the total investment cost requirements for the power system. The future of the power system is of critical importance because low carbon electricity may create significant opportunities for emissions reduction in buildings and transport. A key policy application of quantitative analysis using models is to explore how much investment needs to be mobilised for the energy transition. However, past estimates of energy transition costs for the UK power sector have focused only on 2030 rather than 2050 and consider a relatively narrow range of uncertainties. This paper addresses this important research gap. The UK government's main whole system energy economy model is linked to a power system model that employs an advanced approach to uncertainty analysis, combining Monte Carlo simulation with Modelling-to-Generate Alternatives (MGA), producing 800 different scenario pathways. These pathways simultaneously consider uncertainties in policy, technology and costs. The results show that with No Climate Policy, installed generation capacities in 2050 are found in the range 60-75GW, while under an 80% Reduction in GHG Emissions, between 100GW and 130GW of plant are required. Meeting climate targets for 2050 is also found to increase the investment requirements for new electricity generation. The interquartile range for cumulative investments in new generation under the No Climate Policy scenario ranges from £60bn to £75bn, while under an 80% Reduction in GHG Emissions, investment requirements approximately double to £110bn -£140bn. The exercise demonstrates the importance of uncertainty analysis to policy evaluation, yielding insights for future research practice both in the UK and internationally.

The significance of measuring embodied carbon dioxide equivalent in water sector infrastructure

“…This will in turn considerably alter the aggregate CF values calculated for operational CO2e. The carbon intensity of the electricity grid is generally on a downward trajectory, but it can be volatile (Li and Trutnevyte, 2017;Staffell, 2017;Green and Staffell, 2016); in this case, as far as the operational CO2e calculations for OFWRP are concerned, possible future energy mix scenarios were not considered, and the potential future decarbonisation of the UK national electricity grid was not accounted for. The ECC published in government guidelines for company reporting (BEIS et al, 2017) was used instead to account for the assumed 25-year operation period of the plant in the TWU LCI analysis.…”

Formalizing best practice for energy system optimization modelling

“…Price [134] has developed a formulation of the MGA objective function that maximizes the difference associated with the consumption of each primary energy commodity between successive MGA iterations. Most recently, Li and Trutnevyte [135] combined Monte Carlo simulation with MGA to produce 800 different scenario pathways in order to explore UK electric sector transition pathways to 2050.…”

Uncertainty, politics, and technology: Expert perceptions on energy transitions in the United Kingdom

“…These place a cost-driven paradigm (A1) at the heart of the analytical approach, which condenses the diverse behaviours and motivations of different actors into a notional "utility maximising consumer" from neoclassical economic theory. Several interview participants expressed the view that directly incurred costs were not necessarily the only valid metric upon which to base decision-making, and a well-known limitation of ESOM models is that small variations in costs can sometimes lead to a diverse range of solutions ( [63] and [64]).…”