  Distributed energy resources (DERs) can serve as non-wire alternatives to
capacity expansion by managing peak load to avoid or defer traditional
expansion projects. In this paper, we study a planning problem that
co-optimizes DERs investment and operation (e.g., energy efficiency, energy
storage, demand response, solar photovoltaic) and the timing of capacity
expansion. We formulate the problem as a large scale (in the order of millions
of variables because we model the operation of DERs over a period of decades)
non-convex optimization problem. Despite its non-convexities, we find its
optimal solution by decomposing it using the Dantzig-Wolfe Decomposition
Algorithm and solving a series of small linear problems. Finally, we present a
real planning problem at the University of Washington Seattle Campus.
