This paper addresses a multi-stage generation investment problem for a strategic (price-maker) power producer in electricity markets. This problem is exposed to different sources of uncertainty, including short-term operational (e.g., rivals’ offering strategies) and long-term macro (e.g., demand growth) uncertainties. This problem is formulated as a stochastic bilevel optimization problem, which eventually recasts as a large-scale stochastic mixed-integer linear programming (MILP) problem with limited computational tractability. To cope with computational issues, we propose a consensus version of alternating direction method of multipliers (ADMM), which decomposes the original problem by both short- and long-term scenarios. Although the convergence of ADMM to the global solution cannot be generally guaranteed for MILP problems, we introduce two bounds on the optimal solution, allowing for the evaluation of the solution quality over iterations. Our numerical findings show that there is a trade-off between computational time and solution quality.
|Title of host publication||Proceedings of 57th IEEE Conference on Decision and Control|
|Publication status||Published - 2018|
|Event||57th IEEE Conference on Decision and Control - Fontainebleau , Miami, United States|
Duration: 17 Dec 2018 → 19 Dec 2018
|Conference||57th IEEE Conference on Decision and Control|
|Period||17/12/2018 → 19/12/2018|