Open AccessOptimum generation dispatching of distributed resources in smart grids
Author(s) -
Ansarian Meghdad,
Sadeghzadeh Seyed Mohammad,
FotuhiFiruzabad Mahmud
Publication year - 2015
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.1906
Subject(s) - renewable energy , particle swarm optimization , smart grid , distributed generation , computer science , electricity generation , reliability engineering , simulated annealing , reliability (semiconductor) , grid , wind power , heuristic , mathematical optimization , engineering , power (physics) , electrical engineering , physics , geometry , mathematics , algorithm , quantum mechanics , machine learning , artificial intelligence
Summary Increasing interest in smart grids exhibits its potential benefits for providing reliable, secure, efficient, environmental friendly and sustainable electricity from renewable energy resources. Here, reliability models of four types of renewable and hybrid distributed generation were developed. A fuzzy multi‐objective function was suggested for simultaneous optimization of reliability, electricity generation cost, grid loss and voltage profile. This not only considers uncertainty of renewable energy resources but also provides smart generation dispatching. An efficient reliability index consisting of energy and interruption frequency terms was also defined. A novel hybrid heuristic optimization method based on simulated annealing and particle swarm optimization methods was proposed. These approaches were applied to the generation dispatching of a smart grid, and the results were discussed in details. Scenarios including the changes of wind speed, sun light, fuel price and weight coefficients of the objective function were analyzed. This work succeeds to model uncertainty of renewable energy resources and performs technical and economical optimization in the power generation planning. Copyright © 2014 John Wiley & Sons, Ltd.