article · IEEE Access
Distribution utilities invest heavily in distribution system automation, deploying smart secondary substations and automatic sectionalising switches to modernise grid infrastructure. This research examines the optimal control and dynamic operation of automated distribution networks to cut energy losses and enhance power delivery for consumers. The approach coordinates the simultaneous allocation of distributed generators and capacitor banks during peak demand periods. Following this, automated systems adjust network reconfiguration, distributed generator commitment, and capacitor bank switching in response to practical daily load variations. To resolve these operational challenges, the Manta Ray Foraging Optimization Algorithm is implemented, simulating the foraging behaviours of manta rays. Tested on the IEEE 33-bus, 69-bus, and a real 84-bus network from the Taiwan Power Company, the algorithm demonstrated robust performance and reduced wasted energy when compared against other modern optimization methods.
Modern electrical grids suffer from energy losses as consumer demand changes throughout the day. By using nature-inspired computational algorithms to automate grid switching and power generation adjustments, utilities can cut wasted electricity, lower operating costs, and provide more dependable power services to consumers.
This work is relevant to electricity distribution utilities seeking software solutions to manage smart substations and automated network switches. The method was evaluated using simulations of standard test buses and an operational 84-bus utility grid, indicating an applied and tested stage of development that requires integration into commercial energy management platforms before real-world deployment.
AI-generated from the published abstract. Always read the original work before citing.
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.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1109/access.2021.3053479
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
