Cost-optimal power system extension under flow-based market coupling

Electricity market models, implemented as dynamic programming problems, have been applied widely to identify possible pathways towards a cost-optimal and low carbon electricity system. However, the joint optimization of generation and transmission remains challenging, mainly due to the fact that commercial trades do not directly translate into power flows on a specific line in meshed networks. Instead, loop flows occur and potentially impact the entire transmission system. This paper presents a methodology that allows optimizing transmission investments under flow-based market coupling and complements established electricity market models implemented in a linear programming environment that are suitable for solving large-scale problems. The algorithm developed is based on a linear ‘DC’ representation of the physical load flow equations, expressed as power transfer distribution factors (PTDFs). It iteratively updates the PTDFs when grid infrastructures are modified due to cost-optimal extension and thus yields an optimal solution with a consistent representation of physical load flows. The method is first demonstrated on a simplified three-node model where it is found to be robust and convergent. It is then applied to the European power system in order to find its cost-optimal development under the prescription of strongly decreasing CO2 emissions until 2050. •We develop a methodology to jointly optimize power generation and transmission.•The algorithm iterates PTDF matrices to find a consistent solution.•It is convergent and applicable to large-scale problems.•Cost-optimal European power system development under CO2 targets is investigated.•A 2nd scenario analyzes the results when grid extensions are strictly avoided.