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Sumamry form only given. The conjectured supply function (CSF) model calculates an oligopolistic equilibrium among competing generating companies (GenCos), presuming that GenCos anticipate that rival firms react to price increases by expanding their sales at an assumed rate. The CSF model is generalized here to include each generator's conjectures concerning how the price of transmission services (point-to-point service and constrained interfaces) is affected by the amount of those services that the generator demands. The model simulates oligopolistic competition among generators while simultaneously representing a mixed transmission pricing system. This mixed system includes fixed transmission tariffs, congestion-based pricing of physical transmission constraints (represented as a linearized DC load flow), and auctions of interface capacity in a path-based pricing system. Pricing inefficiencies, such as export fees and no credit for counterflows, can be simulated. The model is formulated as a linear mixed complementarity problem (MCP), which enables very large market models to be solved. A mixed transmission pricing system is simulated, including export fees, a path-based auction system for between-country interfaces, and implicit congestion-based pricing of internal country constraints. The path-based system does not give credit for counterflows when calculating export capability. The application shows that this no-netting policy can exacerbate the economic inefficiencies caused by oligopolistic pricing by generators. The application also illustrates the effects of different generator conjectures regarding rival supply responses and transmission prices. If generators anticipate that their increased demand for transmission services increase transmission prices, then competitive intensity diminishes and energy prices rise. In the example here, the effect of this anticipation is to double the price increase that results from oligopolistic (Cournot) competition among- - generators.
Power Engineering Society General Meeting, 2004. IEEE
Date of Conference: 10-10 June 2004