The formulation of a Poolco model suitable for power system planning is presented. The model involves only slight enhancement to existing conventional power system software and directly enables the calculation of spot prices and a bidbased dispatch. Included is a method for decomposing spot prices to reveal components caused by system congestion. An example illustrates how financial hedges that are traded in the Poolco scenario will affect system planning decisions.
Traditionally, state estimation algorithms have treated each transformer tap setting (voltage transformer turns ratio or phase-shift transformer angle) as a fixed parameter of the network, even though the real-time measurement may be in error or non-existent.Such a strategy can lead to misdirecting residuals in adjacent valid measurements when the modeled transformer setting is incorrect. Ultimately, a network solution is derived which does not match actual real-time conditions.A new transformer tap estimation technique is presented which incorporates the function directly into the state estimation algorithm.The procedure provides for turns ratio and phase angle measurements and treats each transformer tap setting as an independent state variable.Test results for an actual 300-bus network demonstrate the tap estimation capability.
This paper summarizes several recent presentations and discussions made before the IEEE Control Center Database Task Force These presentations have garnered a high level of interest among task force membersThe intent of the paper is to disseminate these findings to a wider audience, thereby focusing industry attention on critical issues affecting control center databasesThe short note paper addresses new and evolving requirements placed on control center databases Among the issues addressed are data access, portability of applications, the need to safeguard and protect mission-critical information, and the role data objects may play in future data bases 0885-8950/96/$05.00 0 1995 IEEE
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.