An Integer Programming Approach and Implementation for an Electric Utility Capacity Planning Problem with Renewable Energy Sources

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This paper presents an integer programming model and algorithm for an electric utility capacity expansion problem which considers the option of investing in nondispatchable or renewable energy sources. A branch-and-bound algorithm is proposed for this problem in which the continuous relaxation of the subproblem associated with each node in the enumeration tree is solved via an efficient two-phase procedure. This procedure solves a deterministic approximation of the problem in the first phase in order to determine a quick near-optimal solution. The resulting solution is subsequently refined in a second phase using more accurate techniques to represent the negative load due to the renewable sources, and to perform the probabilistic production costing. This technique conserves about 80% of the effort which would be required without the deterministic phase. An implementation of this approach is described for the Tijuana-Mexicali subsystem of the Mexican utility, which is not connected to the rest of the Mexican electric system, and which faces a very high summer peak load and a comparatively low winter load. The results suggest that along with a prescribed capacity expansion of conventional equipments, the utility should invest in some solar cooling systems, and, more pertinently, should involve itself intensely in conservation measures in homes of individual customers.