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The development of the smart grid has many implications and goals. With the addition of smart devices throughout the distribution grid, improvements can be made in many aspects of power systems including energy savings, economics, reliability, power quality, and security. Furthermore, the smart grid is an environment friendly oriented directive as it allows for better control algorithms. With ongoing development in the smart grid, distribution systems become more important. The developments encourage utilities to install more control devices on the distribution systems. Growing penetration of advanced metering infrastructure (AMI), and installing more control equipment and devices such as voltage regulators, smart switches, and reclosers, provide a large volume of valuable real-time information, new control capabilities, and feedback for utilities and control centres. Volt-VAr optimization (VVO) is the tool which
improves the efficiency of the distribution system by coordinating the voltage and reactive power. Due to voltage-dependence of loads, both real and reactive power will be affected by variation in voltage. Consequently, rather than minimizing active energy of the system, the design is mainly focusing to reduce the daily apparent energy of the substation using VVO combined with Genetic Algorithm. The design tested on IEEE 69 bus system with 3 DG (2 PV, 1CB) using Matlab 2020a.
REFERENCES
Reference Paper-1: Integrated Volt-VAr Optimization with Distributed Energy Sources to Minimize Substation Energy in Distribution System
Author’s Name: Saran Satsangi & Ganesh Balu Kumbhar
Source: Electric Power Components and Systems, Taylor & Francis Group, LLC
Year: 2019
Reference Paper-2: Volt/VAr Optimization with Energy Savings for Distribution System Using Intelligent Control
Author’s Name: Griet Devriese, Farshid Shariatzadeh, and Anurag K. Srivastava
Source: IEEE
Year: 2013
Reference Paper-3: Multiple DG placements in radial distribution system for multi objectives using Whale Optimization Algorithm
Author’s Name: D.B. Prakash and, C. Lakshminarayana
Source: Elsevier
Year: 2017
DOWNLOAD the Matlab(P-code) encrypted code from the below URL,
https://drive.google.com/file/d/1hWC_rnq3dSOo0jotPdw0_xT9fK1fP6YS/view?usp=sharing
SIMULATION VIDEO DEMO
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