A Reserve Forecast-based Approach to Determining Credit Collateral Requirements in Electricity Markets
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2015 IEEE. In electricity markets, credit collateral requirements for participants have traditionally been set based on historical price data that may not properly reflect future risks. A new predictive approach to determining credit risk is proposed in this paper. For any market that prices reserves in the real-time market, correlation exists between available reserve levels and real-time energy prices. This paper shows that it is possible to forecast hourly system-wide available reserves in a realistic system such as the Electric Reliability Council of Texas (ERCOT) market for up to a week ahead with high confidence. A credit collateral call can then be issued based on predicted system conditions due to the strong correlation between system-wide reserves and real-time energy prices. This in turn, would lower the risk of default for participants as it better reflects their actual risk. Case studies based on a representative ERCOT simulation show that potential scarcity conditions can be successfully identified as far as four days out.