Abstract
A transmission topology control (TC) framework for production cost reduction based on a shift factor (SF) representation of line flows is proposed. The framework can model topology changes endogenously while maintaining linearity in the overall Mixed Integer Linear Programming (MILP) formulation of the problem. In large power systems it is standard practice to optimize operations considering few but representative contingency constraints. Under these conditions and when tractably small switchable sets are analyzed, the SF framework has significant computational advantages compared to the standard B $\theta$ alternative used so far in TC research. These claims are supported and elaborated by numerical results on full models of PJM with over 13,000 buses. We finally present analytical investigations on locational marginal price (LMP) computation in our SF TC framework and their relation to LMPs computed for problems without TC. Also, we discuss practical implementation choices such as sufficient conditions on lower bounds that allow selection of large numbers employed in the MILP formulation.
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