6533b85dfe1ef96bd12be032

RESEARCH PRODUCT

Measurement uncertainty impact on simplified load flow analysis in MV smart grids

CataliottiA.CosentinoV.GuaianaS.NuccioS.Di CaraD.PanzavecchiaN.TinèG.

subject

MonitoringBusbar020209 energyMonte Carlo methodElectric load flowAdvanced metering infrastructure (AMI)02 engineering and technologySmart gridUncertainty evaluationElectric power system measurementPower quality analyzerSlack buspower system monitoringElectric power transmission networksControl theory0202 electrical engineering electronic engineering information engineeringpower quality analyzers (PQA)MedicinePower-flow studyload flow analysiSafety Risk Reliability and QualityInstrumentationbusiness.industryElectric power distributionPower (physics)Smart gridPower system measurementMeasurement uncertaintybusinessSettore ING-INF/07 - Misure Elettriche E ElettronicheVoltage

description

This work is focused on the measurement uncertainty impact on load flow analysis in medium voltage (MV) distribution networks. In more detail, the paper presents the uncertainty evaluation of a simplified load flow algorithm, which is based on the load power measurements at each secondary substation and one voltage measurement at the slack bus (i.e. the voltage at the MV bus bars of the primary substation). To reduce the costs of the monitoring system, the load flow algorithm makes use of LV load power measurements for all the substations except those of MV users, where MV transducers are usually already installed. The uncertainties on the algorithm input quantities (load powers and slack bus voltage) are calculated, considering the actual values of the loads power factors and currents and the accuracy specifications of the measurement instruments installed in the distribution network. Starting from the input quantities uncertainties, the power flows uncertainties are obtained applying the Monte Carlo analysis. The analysis is carried out on a real test system, i.e. the distribution network of Favignana Island. The compatibility is also shown between the algorithm power flow estimations and the power measurements.

10.1109/i2mtc.2018.8409826http://www.cnr.it/prodotto/i/398406