Optimal Operation of Automated Distribution Networks Based-MRFO Algorithm

Ehab E Elattar,Ahmed R Ginidi,Ragab A El-Sehiemy,Abdullah M El-Sayed,Abdullah M Shaheen

doi:10.1109/access.2021.3053479

Abstract

Nowadays, distribution utilities expend large investments on Distributed System Automation (DSA) based on smart secondary substations at load, capacitor, and distributed generator points with installed automatic sectionalizing switches on their branches. This article addresses the optimal control and operation of distribution systems that minimize the wasted energy and introducing quantitative and qualitative power services to meet consumers’ satisfaction. Simultaneous allocations of Distributed Generators (DGs) and Capacitor Banks (CBs) are handled at peak loading condition. Then, the DSA is optimally activated for optimal Distribution Network Reconfiguration (DNR), optimal DGs commitment, and optimal CBs switching for losses minimization in coordination with different loading conditions. Practical daily load variation is applied to simulate the dynamic operation of automated distribution systems. For achieving these targets, the Manta Ray Foraging Optimization Algorithm (MRFOA) is adopted. MRFOA is an effective and simple structure optimizer that emulates three various individual manta rays foraging organizations. The capability of the MRFOA is applied to the IEEE 33-bus, 69-bus and practical distribution network of 84-bus due to the Taiwan Power Company (TPC). A comparison with recent techniques has been conducted to prove the effectiveness of MRFOA. The accomplished results demonstrate that the proposed MRFOA has great effectiveness and robustness among other optimization techniques.

Highlights

The rapid power demand increase with limited generation and transmission expansion is a big challenge for numerous electrical grids
Optimal allocation and control of the three elements distributed generators (DGs), capacitor banks (CBs), and distribution network reconfiguration (DNR) are executed with different operational cases
In this article, a recently developed Manta Ray Foraging Optimization Algorithm has been employed for control and optimal allocation of Distributed Generators, Capacitor Banks, and Distribution Network Reconfiguration simultaneously

Summary

Ibn Ibmnax

Elattar et al.: Optimal Operation of Automated Distribution Networks Based-MRFO Algorithm. Active load demand Reactive load demand Penetration level which is acceptable from the DGs and CBs Buses number of the system Substation reactive power Substation active power Number of designated load conditions Number of populations of the manta rays Maximum number of iterations Individual of each manta ray (m) New position of the manta ray position Best position in the population Adaptive weight coefficients Somersault coefficient Random uniformly distributed number in range [0, 1]

INTRODUCTION

PROBLEM FORMULATION

CONCLUSION