Kerry D McBee
Distribution Automation, Optimization , Reliability, Renewable Energy
Smart grid activities are increasing the implementation of distribution automated devices on electric power systems. Most methods for identifying the optimal distribution automation allocation (DAA) rely upon evaluating monetized reliability indices, while ignoring lifetime costs. The approach described in this manuscript applies accepted distribution planning methodologies to net present value analysis to develop a novel optimal DAA algorithm. The approach relies upon mixed integer nonlinear programming optimization methods to identify the number of automated devices that should be installed on a circuit to minimize lifetime costs (installation, operation, and reliability) when accounting for failure rates, the monetary impact of Customer Minutes Out (CMO’s), and demand side management and distributed energy resource expenditures that support restoration activities. With the addition of each automated switching device on a circuit, the incremental reliability improvements decrease while the installation costs linearly increase. The algorithm identifies the intersection of reliability and installation costs through the application of a multi-dimensional objective cost function developed utilized traditional system planning methodologies and present day costs. Solving the cost function identifies the specific number of automated switching devices on the circuit that produce the minimum lifetime costs. Unlike heuristic approaches, the method is easily applied and solved with computational software.
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