A mixed integer nonlinear programming (MINLP) supply chain optimisation framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK

The co-firing of biomass and fossil fuels in conjunction with CO2 capture and storage (CCS) has the potential to lead to the generation of relatively inexpensive carbon negative electricity. In this work, we use a mixed integer nonlinear programming (MINLP) model of carbon negative energy generation in the UK to examine the potential for existing power generation assets to act as a carbon sink as opposed to a carbon source. Via a Pareto front analysis, we examine the technical and economic compromises implicit in transitioning from a dedicated fossil fuel only to a carbon negative electricity generation network. A price of approximately £30-50/t CO2 appears sufficient to incentivise a reduction of carbon intensity of electricity from a base case of 800 kg/MWh to less than 100 kg/MWh. However, the price required to incentivise the generation of carbon negative electricity is in the region of £120-175/t of CO2. In order for biomass to energy with CCS (BECCS) to be commercially attractive, the power plants in question must operate at a high load factor and high rates of CO2 capture. The relative fuel cost is a key determinant of required carbon price. Increasing biomass availability also reduces the cost of generating carbon negative electricity; however one must be cognisant of land use change implications.