An agile optimization algorithm for vitality management along with fusion of sustainable renewable resources in microgrid

This article presents a residential microgrid consisting of hybrid wind-solar energy to meet residential local demand. Due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids such as loss of power, decrease in performance,...

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Bibliographic Details
Published in:Energy sources. Part A, Recovery, utilization, and environmental effects Vol. 42; no. 13; pp. 1580 - 1598
Main Authors: Gajula, Viswanath, Rajathy, R.
Format: Journal Article
Language:English
Published: Taylor & Francis 02.07.2020
Subjects:
ant-lion optimization
energy management
hybridgalactic-swarm optimization with point estimation method
microgrid
smart grid
ISSN:1556-7036, 1556-7230
Online Access:Get full text
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Summary:This article presents a residential microgrid consisting of hybrid wind-solar energy to meet residential local demand. Due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids such as loss of power, decrease in performance, reduction in quality of power, etc. Hence, a novel hybrid galactic-swarm optimization (GSO with point estimation method that utilizes renewable energy resources such as wind and solar energy for energy management is proposed in this article. The point estimation method models the uncertainties of energy resources and also provides optimal power flow from wind and solar. Then, GSO algorithm concludes the optimal amount of output power to avoid supplementary generation with proper scheduling and also the amount of exchanging energy with load and main grid during the operating period. Based on the power supply form the hybrid energy resources to load, the load shifting is done during peak hours using ant-lion Optimization Algorithm. The proposed method manages the processes in power distribution system for controlling power stability and power loss. The proposed work is implemented in the working platform of MATLAB and the effectiveness of the proposed is demonstrated.
ISSN:1556-7036
1556-7230
DOI:10.1080/15567036.2019.1604869