Open AccessProbabilistic method for the operation of three‐phase unbalanced active distribution networks
Author(s) -
Mokryani Geev,
Majumdar Ankur,
Pal Bikash C.
Publication year - 2016
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2015.0334
Subject(s) - probabilistic logic , mathematical optimization , monte carlo method , computer science , probability density function , pareto principle , photovoltaic system , fuzzy logic , probability distribution , engineering , mathematics , artificial intelligence , electrical engineering , statistics
This study proposes a probabilistic multi‐objective optimisation method for the operation of three‐phase distribution networks incorporating active network management (ANM) schemes including coordinated voltage control and adaptive power factor control. The proposed probabilistic method incorporates detailed modelling of three‐phase distribution network components and considers different operational objectives. The method simultaneously minimises the total energy losses of the lines from the point of view of distribution network operators and maximises the energy generated by photovoltaic (PV) cells considering ANM schemes and network constraints. Uncertainties related to intermittent generation of PVs and load demands are modelled by probability density functions (PDFs). Monte Carlo simulation method is employed to use the generated PDFs. The problem is solved using ɛ ‐constraint approach and fuzzy satisfying method is used to select the best solution from the Pareto optimal set. The effectiveness of the proposed probabilistic method is demonstrated with IEEE 13‐ and 34‐bus test feeders.