LOAD SHEDDING AND CAPACITOR PLACEMENT-BACKWARD-FORWARD LOAD FLOW-DIFFERENT LOAD MODELS-IEEE 33 BUS

DESIGN DETAILS
Load Shedding is an important scheme to prevent the collapse of the power system. However, this method is not able to stabilize the system all by itself, as well as frequency. Voltage also affects the stability of the network. This Malab design is based on combination of load shedding and capacitor placement in distribution network. First identifying the weakest node using Equivalent Node Voltage Collapse Index (ENVCI) and then applying the Dolphin Optimization Algorithm to find the best solutions. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented, among them to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Teaching Learning Based Optimization (TLBO) Algorithm is applied for selecting the sizes and locations of capacitors. The design uses Backward-Forward load flow, node selection for load shedding and capacitor placement based on ENVCI/Optimization algorithm on the test networks.

OBJECTIVE FUNCTION
𝐼𝑖𝑗≤ 𝐼𝑖𝑗𝑚𝑎𝑥
Vimin ≤Vi ≤Vimax (0.95-1.05) p.u.
Minimum losses.
Enhancement voltage profile.

TESTING
IEEE 33-bus system is employed to evaluate the different load models considering the results for normal, load shedding only, capacitor placement only, load shedding then capacitor placement, capacitor placement then load shedding, load shedding and capacitor placement simultaneously. The Matlab version 2020a used for simulation and the video shows the performance of the design with its result graphs/values. We have shown the Matlab program implementation of each function i.e TLBO, Load Flow Analysis with the corresponding file in the simulation video to make you understand how it works.

REFERENCES
Reference Paper-1: Optimum reactive power compensation for distribution system using dolphin algorithm considering different load models.
Author’s Name: Waleed Khalid Shakir Al-Jubori1 and Ali Nasser Hussain
Source: IJECE)
Year:2020

Reference Paper:2-Optimal Allocation of DGs and Reconfiguration of Radial Distribution Systems Using an Intelligent Search-based TLBO.
Author’s Name: Neeraj Kanwar, Nikhil Gupta, Khaleequr R. Niazi & Anil Swarnkar
Source: Taylor & Francis- Electric Power Components and Systems
Year:2017

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