An agile optimization algorithm for vitality management along with fusion of sustainable renewable resources in microgrid. Issue 13 (2nd July 2020)

• Record Type: Journal Article
• Authors: Gajula, Viswanath; Rajathy, R.
• Is Part Of: Energy sources. Volume 42:Issue 13(2020)
• Page Start: 1580
• Page End: 1598
• Publication Date: 2020-07-02
• Subjects: smart grid -- hybridgalactic–swarm optimization with point estimation method -- ant–lion optimization -- energy management -- microgrid; Natural resources -- Periodicals; Energy consumption -- Periodicals; Energy consumption -- Climatic factors -- Periodicals; Energy conversion -- Periodicals; Energy conversion -- Environment aspects -- Periodicals; Power (Mechanics) -- Periodicals; 333.7905
• DOI: 10.1080/15567036.2019.1604869
• Languages: English
• ISSNs: 1556-7036

Abstract

ABSTRACT: 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.