A real-time evaluation of energy management systems for smart hybrid home microgrids

Marzband, M; Ghazimirsaeid, SS; Uppal, H; Fernando, TP

Abstract

Real-time energy management within the concepts of home Microgrids (H-MG) systems is crucial for H-MG operational reliability and safe functionality, regardless of simultaneously emanated variations in generation and load demand transients. In this paper, an experimental design and validation of a real-time mutli-period artificial bee colony (MABC) topology type central energy management system (CEMS) for H-MGs in islanding mode is proposed to maximize operational efficiency and minimize operational cost of the H-MG with full degree of freedom in automatically adapt the management problem under variations in the generation and storage resources in real-time as well, suitable for different size and types of generation resources and storage devices with plug-and-play structure, is presented. A self-adapting CEMS offers a control box capability of adapting and optimally operating with any H-MGs structure and integrated types of generation and storage technologies,using a two-way communication between each asset, being a unique inherent feature. This CEMS framework utilizes feature like day-ahead scheduling (DAS) integrated with real-time scheduling (RTS) units, and local energy market (LEM) structure based on Single Side Auction (SSA) to regulate the price of energy in real-time. The proposed system operates based on the data parameterization such as: the available power from renewable energy resources, the amount of non-responsive load demand, and the wholesale offers from generation units and time-wise scheduling for a range of integrated generation and
demand units. Experimental validation shows the effectiveness of our proposed EMS with minimum cost margins and plugand-play capabilitities for a H-MG in real-time islanding mode that can be envisioned for hybrid multi-functional smart grid supply chain energy systems with a revolutionary architectures. The better performance of the proposed algorithm is shown in comparison with the mixed integer non-linear programming (MINLP) algorithm, and its effectiveness is experimentally validated over a microgrid test bed. The obtained results show convergence speed increase and the remarkable improvement of efficiency and accuracy under different conditions.

Citation

Marzband, M., Ghazimirsaeid, S., Uppal, H., & Fernando, T. (2017). A real-time evaluation of energy management systems for smart hybrid home microgrids. Electric Power Systems Research, 143, 624-633. https://doi.org/10.1016/j.epsr.2016.10.054

• Journal Article Type: Article
• Acceptance Date: Oct 22, 2016
• Online Publication Date: Nov 2, 2016
• Publication Date: Feb 1, 2017
• Deposit Date: Dec 7, 2016
• Publicly Available Date: Nov 2, 2017
• Journal: Electric Power Systems Research
• Print ISSN: 0378-7796
• Publisher: Elsevier
• Volume: 143
• Pages: 624-633
• DOI: https://doi.org/10.1016/j.epsr.2016.10.054
• Publisher URL: http://dx.doi.org/10.1016/j.epsr.2016.10.054
• Related Public URLs: http://www.journals.elsevier.com/electric-power-systems-research/
• Additional Information: Funders : European Commission; Projects : Design4Energy Project; Grant Number: Grant Agreement No: 609380