An efficient technique‐based distributed energy management for hybrid MG system: A hybrid QOCSOS‐RF technique. Issue 3 (24th November 2019)

• Record Type: Journal Article
• Authors: Chen, Jialin; Zhou, Zheng; Karunakaran, Venkatesan; Zhao, Shiwen
• Is Part Of: Wind energy. Volume 23:Issue 3(2020)
• Page Start: 575
• Page End: 592
• Publication Date: 2019-11-24
• Subjects: energy management strategy -- grid‐connected MG -- power flow constraints -- random forest -- quasi‐oppositional‐chaotic symbiotic organisms search algorithm; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2443
• Languages: English
• ISSNs: 1095-4244

Abstract

Abstract: This paper proposes an efficient hybrid approach–based energy management strategy (EMS) for grid‐connected microgrid (MG) system. The primary objective of the proposed technique is to reduce the operational electricity cost and enhanced power flow between the source side and load side subject to power flow constraints. The proposed control scheme is a consolidated execution of both the random forest (RF) and quasi‐oppositional‐chaotic symbiotic organisms search algorithm (QOCSOS), and it is named as QOCSOS‐RF. Here, the QOCSOS can have the capacity to enhance the underlying irregular arrangements and joining to a superior point in the pursuit space. Likewise, the QOCSOS has prevalence in nonlinear frameworks due over the way that can insert and extrapolate the arbitrary information with high exactness. Here, the required load demand of the grid‐connected MG system is continuously tracked by the RF technique. The QOCSOS optimized the perfect combination of the MG with the consideration of the predicted load demand. Furthermore, in order to reduce the influence of renewable energy forecasting errors, a two‐strategy for energy management of the MG is employed. At that point, proposed model is executed in MATLAB/Simulink working platform, and the execution is assessed with the existing techniques.