Distributed energy resources (DERs) can serve as non-wire alternatives (NWAs) to capacity expansion by managing peak load to avoid or delay traditional expansion projects. However, the value stream derived from using DERs as NWAs is usually not explicitly included in DER planning problems. In this paper, we study a planning problem that co-optimizes investment and operation of DERs and the timing of capacity expansion. By including the timing of capacity expansion as a decision variable, we naturally incorporate NWA value stream of DERs into the planning problem. Furthermore, we show that even though the resulting optimization problem could have millions of variables and is non-convex, an optimal solution can be found by solving a series of smaller linear problems. Finally, we present a NWAs planning problem using real data from the Seattle Campus of the University of Washington.

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 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.

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