Randomized discrepancy bounded local search for transmission expansion planning

Conference · Tue Nov 23 04:00:00 EST 2010

DOI:https://doi.org/10.1109/PES.2011.6039443· OSTI ID:1041204

Bent, Russell W ^[1]; Daniel, William B ^[1]

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1. Los Alamos National Laboratory

In recent years the transmission network expansion planning problem (TNEP) has become increasingly complex. As the TNEP is a non-linear and non-convex optimization problem, researchers have traditionally focused on approximate models of power flows to solve the TNEP. Existing approaches are often tightly coupled to the approximation choice. Until recently these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (e.g. large amounts of limited control, renewable generation) and necessitates new approaches. Recent work on deterministic Discrepancy Bounded Local Search (DBLS) has shown it to be quite effective in addressing this question. DBLS encapsulates the complexity of power flow modeling in a black box that may be queried for information about the quality of proposed expansions. In this paper, we propose a randomization strategy that builds on DBLS and dramatically increases the computational efficiency of the algorithm.

• Research Organization: Los Alamos National Laboratory (LANL)
• Sponsoring Organization: DOE
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 1041204
• Report Number(s): LA-UR-10-07890; LA-UR-10-7890
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
29 ENERGY PLANNING, POLICY, AND ECONOMY
97 MATHEMATICS AND COMPUTING
APPROXIMATIONS
EFFICIENCY
NONLINEAR PROBLEMS
OPTIMIZATION
PLANNING
POWER SYSTEMS
SIMULATION