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Showing 3 results for Ghanbari
Morteza Ebrahimi, Younes Noorollahi, Hosein Hoseini, Sasan Ghanbari,
Volume 18, Issue 1 (4-2015)
Abstract
The growing demand for energy as well as the environmental concerns about the fossil fuels has contributed to the recent uprising of utilization of renewable energy sources. Among these sources wind energy is the fastest to grow. Estimations indicate that there will be 536 GW installed capacity of wind power by the end of 2017 worldwide. According to the preliminary assessments there is a considerable potential for wind energy in Iran but the task to harness this energy would greatly depend on selection of the most suitable locations to set up wind farms. Considering the challenges posed by wind power, an attractive way of utilizing wind energy is combing it with other energy sources. In this research a methodology based on Multi Criteria Decision Making (MCDM) and Geographical Information System (GIS) has been proposed to rank the attributes and pick out the best location for a hybrid wind powered pumped storage power plant. It has been concluded that Gilan-e-gharb is the most suitable location in the study area.
Ehsan Moshksar, Teymoor Ghanbari, Farshid Naseri,
Volume 20, Issue 2 (9-2017)
Abstract
This paper presents a novel identification technique for estimation of unknown parameters
in photovoltaic (PV) systems. A single diode model is considered for the PV system, which
consists of five unknown parameters. Using information of standard test condition (STC), three
unknown parameters are written as functions of the other two parameters in a reduced model. An
objective function and a set of inequality constraints are defined for the reduced model considering
limitations of the physical system. It is shown that the non-convex optimization problem of
PV systems is converted to a convex constrained optimization one. The constraints are enforced
using a modified barrier function that generates an augmented objective function. An adaptive
identification technique is utilized to find the optimal values of the augmented cost. Unlike most
identification techniques, the proposed algorithm has a precise and unique solution, which is easy
to implement. The effectiveness of the proposed approach is confirmed using some simulation and
experiments.
Saman Ghanbari, Dr Mohsen Kalantar,
Volume 22, Issue 3 (12-2019)
Abstract
Introduction of new technologies such as energy storage systems, electric vehicles, and distributed generation improved the characteristics of networks. On other hand, using these components in distribution systems improves system performances such as power losses. One of effective methods for improving system characteristics is distribution network reconfiguration. In this study, in addition to these effects, the role of reconfiguration in improving system resilience is investigated. Accordingly, a comprehensive model for network reconfiguration in the precense of energy storage systems, electric vehicles, wind turbines, and photovoltaic generation is proposed. Regarding this, the optimal location and capacity for optimal operation of system is obtained for all mentioned components. The effectiveness of model is proved in four case studies, The results of the four modes are compared. The results show the effect of network reconfiguration and storage components on the outputs of the model. The model is implemented on the 33 IEEE network in the GAMS environment with Sbb solver.
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