A Multi-Objective Optimization Model Based on Genetic Algorithm for Voltage Management of Radial Distribution Networks in Tropical Areas of South of Iran Using a Combination of Fixed Capacitors and Voltage Regulators

Subject Areas : Generation, transmission and distribution

Ali Askarizadeh ¹ (Department of Faculty of Engineering- Shahid Chamran University of Ahvaz, Ahvaz, Iran)
Elaheh Mashhour ² (Department of Faculty of Engineering- Shahid Chamran University of Ahvaz, Ahvaz, Iran)
Mohsen Saniei ³ (Department of Faculty of Engineering- Shahid Chamran University of Ahvaz, Ahvaz, Iran)

Received: 2022-12-15 Accepted : 2023-04-09 Published : 2025-02-19

Keywords: Distribution networks, Automatic voltage regulator, voltage deviation index, Energy Loss Cost, Investment Cost, non-automatic voltage regulator,

Abstract :

This paper presents a multi-objective optimization model for optimal placement of fixed capacitors and voltage regulators to manage the voltage profile of radial distribution networks, in which the realities of the distribution network of Ahvaz city (as representing the tropical regions of southern Iran) are considered. The objective functions include minimizing the investment cost, minimizing the sum of absolute value of the node’s voltage deviations from 1 p.u., and minimizing the cost of energy losses on the planning horizon. The optimization model is formulated by considering two different load patterns according to the warm and temperate periods of the year in Ahvaz city. The loads are modeled as a combination of constant power and constant impedance components and the share of each component in the warm and temperate periods of the year is considered in accordance with the actual conditions of the Ahwaz power distribution network. The cost of energy losses as well as the final profit of the project is calculated based on the current rules of Iranian power market for active and reactive powers. The optimization problem is solved using multi-objective non-dominated-sorting genetic algorithm-II (NSGA_II), and in order to choose the best answer among none-dominated Pareto front, a selection index is introduced. The proposed model is implemented on two 33 kV test feeders (i.e., a 33-bus test feeder and a real 123-bus feeder from Ahvaz distribution company) and the results are analyzed. 

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