Optimal reconfiguration and capacitor placement are used to reduce power losses and keep the voltage within its allowable interval in power distribution systems considering voltage, current, and radial condition constraints. Effective utilization of power distribution networks requires extensive studies in such areas as using capacitors, voltage regulators, network reconfiguration, and so on. Indeed, achieving accurate answers, and managing appropriate solutions for network problems requires detailed modeling of the network in the process of the above studies. Among the elements that are important for modeling in-network, research is network loads. Loads are generally being modeled such as constant power. While load nature is often widespread and different. Failure to have detailed modeling can lead to non-optimal and even wrong answers and will result in the waste of costs and investments. TLBO Algorithm is used to simultaneously reconfigure and
allocate optimal DG units in a distribution network. The radial nature
of the network is secured by generating the proper parent node-child
node path of the network during power flow. Since the load flow is the
basis of any research in distribution networks, in this design, an
effective method is presented for estimating the optimal amount of load
to be shed in a distribution system based on the TLBO algorithm. The
effectiveness of the proposed TLBO algorithm has been tested on two
different distribution network systems i.e 16 and 33-bus IEEE test
systems using the Newton Raphson and Forward_Backward method, to find the optimum
configuration of the network with regard to power losses. Five different
cases are considered as mentioned below, and the effectiveness of the
proposed technique is demonstrated with Normal load, Constant Impedance
load, Constant Current load, and ZIP load models, through MATLAB
software simulation as shown in the video demo.
Reference Paper-1: An Optimal Load Shedding Methodology for Radial Power Distribution Systems to Improve Static Voltage Stability Margin using Gravity Search Algorithm SIMULATION VIDEO DEMO-NEWTON RAPHSON SIMULATION VIDEO DEMO-FORWARD BACKWARD PREVIOUS PAGE|NEXT PAGE |