Probabilistic Load Flow methods with high integration of Renewable Energy Sources and Electric Vehicles - case study of Greece (original) (raw)

2011

Abstract

ABSTRACT This paper exams the large distribution power system of Greece with high integration of Renewable Energy Resources (RES) and Electrical Vehicles (EV) using Probabilistic Load Flow (PLF) techniques. These techniques provide Cumulative Density Functions (CDF) of branch power flows, node voltages and active power line losses with large variations of RES and EV integration. When different charging strategies of EV (dump charging, dual tariff policy and mixed charging) take place then lead to significant uncertainty in node injections. In order to tackle this issue, it is adopted and enhanced PLF methods to cope with EV nodal loads. Two methods are investigated for the calculation of Probabilistic Density Function (PDF) of RES' production, Gram - Charlier (G-C) and Cornish Fisher (C-F). All the PLF results are compared with Monte Carlo (MC) method.

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