Novel market decision approach using data management technique with short supply. (May 2022)

• Record Type: Journal Article
• Authors: Huang, Yan; Zhang, Yunhua
• Is Part Of: Computers & electrical engineering. Volume 100(2022)
• Publication Date: 2022-05
• Subjects: Market decision approach -- Uncertainty -- Battery energy storage system -- Data energy management -- Photovoltaic -- Microgrid; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107881
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Uncertainty quantization using a scenario based stochastic method in the renewable based microgrids Developing a new energy management framework based on the WOA Assessing the effect of the proposed model on different seasons and weather conditions Abstract: A novel decision approach is proposed in the present study for a microgrid (MG) with different renewable energy sources such as wind turbines (WT), fuel cells, battery energy storage systems, photovoltaics (PV), and microturbines in the electricity market. This paper suggested a model that evaluates the effect of various irradiances data on the day-ahead scheduling of the MG during various seasons and days. An approach on the basis of scenario is used for data management with uncertainties associated with the power output of the WT and PV, load demand forecasting error, and grid bid variations for the optimum management in an MG. With the suggested algorithm, the optimal position can be computed faster, and the results are more precise compare with traditional optimization algorithms. Based on outcomes of simulations, using an actual PV layout in practice improves the energy management system's precision and reduces the overall operating costs. Graphical Abstract: : Graphical Abstract Image, graphical abstract