Very short term load forecasting aided hybrid state estimator with optimally placed pseudo-measurements

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2018

Öğrenci: BURAK ÖZSOY

Danışman: MURAT GÖL

Özet:

The use of PMUs in power grids have been increased with the development of GPS and computer-based technology. Unlike conventional SCADA measurements, PMUs obtain synchronized measurements with respect to the GPS. Moreover, PMU measurements are more qualified than conventional measurements thanks to having better accuracy and being updated with higher refresh rates. Nevertheless, it is unlikely that power system state estimator can be conducted with only PMUs instead of existing SCADA systems in large power systems in the near future due to the high cost of installation. Therefore, it seems more feasible to use both PMUs and SCADA in power system state estimation, namely hybrid state estimation. In the practical applications, the different resolutions of these measurements cause several problems. One of the major problems is that the system observability cannot be provided at the time instants between SCADA updates due to little number of PMUs for the system observability. This thesis proposes a hybrid state estimation strategy, which uses pseudomeasurements to restore the system observability at time instants between adjacent SCADA updates. The pseudo-measurements are generated using statistical properties vi of the injection measurement data gathered in the most recent 60 days to include effects of climate and economy in power consumption. The derived statistical model of the injections is updated during the day via Kalman Filter based very short-term load forecasting. In order to minimize the bias because of the use of pseudo-measurements, minimum number of pseudo-measurements that restore system observability are selected among the candidate buses.