Optimal renewable energy project sequencing with transmission expansion

Solving the Project Sequencing Problem (PSP) by Dynamic Programming (DP) has usually assumed a set of potential projects to be connected to a single bus and has therefore ignored any transmission constraints. This papers reformulates the PSP by expanding to simultaneously optimize generation and transmission by taking into account transmission limitations and costs. The problem is generally formulated, by assuming a set of projects, available at each bus, and a set of transmission expansion options for network branches. A solution with DP is proposed, where limited set sizes are assumed to avoid the well known 'curse of dimensionality'. This limitation may be acceptable, as the number of expansion options is often limited in practice. For each configuration a Nonlinear Programming (NLP) subproblem can be solved to calculate the appropriate timing for each state and stage of the DP process. Finally, the NLP/DP algorithm is used in a case study where a small generation and transmission expansion problem is solved.