Power
systems encounter more and more uncertainties due to the probabilistic
nature of renewable generations, load fluctuations, and probable failure
of system parts. Power system uncertainties bring in various
operational challenges and lead to increase of risk in operational
decisions due to the unpredictable nature of the system state. Under
probabilistic situations, the predictability of power system is
associated with its certainty and/or uncertainty, directly. The more the
power system is certain, the more the power system is predictable.
Increasing power system predictability can result in better decision
making by the power system operator. This Matlab design proposes a
multi-objective framework for optimal placement and parameters setting
of a unified power flow controller (UPFC) considering system
predictability. The well-known multi-objective nondominated sorting
genetic algorithm is implemented to handle various objective functions
such as active power losses and predictability of system in the presence
of operational constraints and uncertainties. The point estimate method
is used for modeling probabilistic nature of the wind power. Using the
proposed method, statistical information of voltage magnitude and
apparent power of converters of UPFCs can be obtained, which are
especially useful in making decision on the sizing of UPFCs.
Comprehensive discussions are provided using the simulations on the IEEE
57-bus test system. Also, to validate the obtained results, a
multi-objective particle swarm optimization algorithm is implemented and
the results of two algorithms i.e NSGA-II and MOPSO are compared with
each other. Reference Paper: Multiobjective Predictability-Based Optimal Placement and Parameters Setting of UPFC in Wind Power Included Power Systems Author’s Name: Sadjad Galvani, Mehrdad Tarafdar Hagh , Mohammad Bagher Bannae Sharifian,and Behnam Mohammadi-Ivatloo Source: IEEE Year :2019 Request source code for academic purpose, fill REQUEST FORM or contact +91 7904568456 by WhatsApp or sales@verilogcourseteam.com, fee applicable. SIMULATION VIDEO DEMO

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