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Tie-line scheduling in multi-area power systems in the United States largely proceeds through a market-based mechanism called Coordinated Transaction Scheduling (CTS). We analyze this market mechanism through a game-theoretic lens. Our analysis characterizes the effect of market liquidity, market participants&#x2019; forecasts about inter-area price spreads, transactions fees and coupling of CTS markets with up-to-congestion virtual transactions. Using real data, we empirically verify that the market outcomes with CTS bidders, employing simple learning algorithms, support the conclusions from our equilibrium analysis of the games.

Coordinated Transaction Scheduling in Multi-Area Electricity Markets: Equilibrium and Learning