Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty

Abstract

We develop a stochastic two-stage optimisation model that captures the multistage nature of electricity transmission planning under uncertainty and apply it to a stylised representation of the Great Britain (GB) network. In our model, a proactive transmission planner makes investment decisions in two time periods, each time followed by a market response. This model allows us to identify robust first-stage investments and estimate the value of information in transmission planning, the costs of ignoring uncertainty, and the value of flexibility. Our results show that ignoring risk has quantifiable economic consequences, and that considering uncertainty explicitly can yield decisions that have lower expected costs than traditional deterministic planning methods. Furthermore, the best plan under a risk-neutral criterion can differ from the best under risk-aversion.