An Integer Programming Approach and Implementation for an Electric Utility Capacity Planning Problem with Renewable Energy Sources
提出一个整数规划模型和分支定界算法，帮助电力公司在规划新增发电容量时考虑可再生能源选项，并通过墨西哥某子系统的实例验证了方法能节省约80%计算量，建议投资太阳能冷却和推广家庭节能措施。
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.