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 CO 2 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 CO 2 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 CO 2 . 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 CO 2 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.