Post-market computation engine toward CAISO market settlements

The electricity market redesign and technology upgrade (MRTU) program executed by the California independent system operator (CAISO) represents a major overhaul of the original legacy market design, which attempts to address the critical issues leading to the well-known California energy crisis discovered with the original design and builds on the fundamental principles of efficient use of electric grids and the locational marginal prices (LMP). With the new market design, CAISO will be able to administer and oversee the commodity markets for buying and selling electricity within its administered territory. As a result of the new design, the two-settlement system is used to determine the awards or charges, as the results of the clearing of the day-ahead integrated forward market (IFM) and real-time market (RTM), to be paid to or by a market participant to satisfy its financial obligations. The CAISO market quality system (MQS) serves as the historical market data repository for the settlement purpose and more importantly the core after-the-fact computation engine and conducts time- consuming, algorithmic calculations for providing the essential settlement needed granular results. The post- market data required by MQS flows from the Scheduling Infrastructure business rules system (SIBR), IFM and RTM at different periodicities. The high volume of data coupled with the complexity of the wholesale energy settlement business rules and demanding post-market computation requirements, presents unique engineering and computational challenges to the CAISO MQS. This paper identifies the core technical issues, presents an innovative, practical engineering solution framework, and provides additional details on some creative algorithmic treatments for optimal execution time and result accuracy performances of post-market calculations to meet the CAISO commercial operation timelines and performance requirements.