Open AccessA combined probabilistic modeling of renewable generation and system load types to determine allowable DG penetration level in distribution networks
Author(s) -
Naghdi Marzieh,
Shafiyi MohammadAgha,
Haghifam MahmoudReza
Publication year - 2019
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2696
Subject(s) - renewable energy , distributed generation , probabilistic logic , transformer , electric power system , computer science , voltage , ac power , control theory (sociology) , engineering , mathematical optimization , reliability engineering , power (physics) , electrical engineering , mathematics , artificial intelligence , physics , control (management) , quantum mechanics
Summary Determining the penetration level of the distributed generation (DG) is an effective tool to site and size DGs in distribution networks. A multiobjective function of optimizing the DG penetration level, subject to constraints including short circuit capacity, voltage limits, transformer capacity, reverse power flow, and congestion of lines, is introduced to minimize the real and reactive losses and to ensure the voltage stability considering the variations of loads, different locations and power factors of DGs, and statistical nature of DG powers especially renewable energy resources. This optimization is performed based on a combined probabilistic modeling of the chronological behavior of wind speed, solar irradiance, and load with different types. The dynamical behavior of the compensators and on‐load tap changers is modeled by optimization subfunctions. An improved bee algorithm is used through conducting searches in the neighboring areas based on a new nonlinear function for a higher fitness and coherency speed.