Strategic planning for power system restorations
- Los Alamos National Laboratory
- BROWN UNIV.
This paper considers the power system restoration planning problem (PSRPP) for disaster recovery, a fundamental problem faced by all populated areas. PSRPPs are complex stochastic optimization problems that combine resource allocation, warehouse location, and vehicle routing considerations. Furthermore, electrical power systems are complex systems whose behavior can only be determined by physics simulations. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This work is three fold: (1) it formalizes the specification of PSRPPs; (2) introduces a simple optimization-simulation hybridization necessary for solving PSRPPs; and (3) presents a complete restoration algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. This paper studied a novel problem in the field of humanitarian logistics, the Power System Restoration Problem (PSRPP). The PSRPP models the strategic planning process for post disaster power system recovery. The paper proposed a multi-stage stochastic hybrid optimization algorithm that yields high quality solutions to real-world benchmarks provided by Los Alamos National Laboratory (LANL). The algorithm uses a variety of technologies, including MIP, constraint programming, and large neighborhood search, to exploit the structure of each individual optimization subproblem. The experimental results on hurricane disaster benchmarks indicate that the algorithm is practical from a computational standpoint and produce significant improvements over existing relief delivery procedures.
- Research Organization:
- Los Alamos National Laboratory (LANL)
- Sponsoring Organization:
- DOE
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1036728
- Report Number(s):
- LA-UR-10-06901; LA-UR-10-6901
- Country of Publication:
- United States
- Language:
- English
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