Fuzzy scheduling of a non-isolated micro-grid with renewable resources. (August 2018)

• Record Type: Journal Article
• Authors: Banaei, Mohsen; Rezaee, Babak
• Is Part Of: Renewable energy. Volume 123(2018)
• Page Start: 67
• Page End: 78
• Publication Date: 2018-08
• Subjects: Distributed energy resources -- Renewable resources -- Fuzzy sets -- Day-ahead scheduling -- Fuzzy linear programming; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2018.01.088
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: This paper proposes a new energy management scheduling model for optimizing operation costs of a non-isolated micro-grid. It's assumed that the micro-grid includes some renewable energy resources like wind turbines and photovoltaic panels, fuel cell, and energy storage systems, and is connected to the macro-grid through a distributed transmission line with limited capacity. Different possible uncertainties associated with different elements of the micro-grid like forecasted outputs of renewable resources, a maximum capacity of the fuel cell and batteries, a maximum capacity of distributed line and hourly demands are considered in the proposed model. Fuzzy sets concept is used to model these uncertainties in the micro-grid and a three stage optimization method is applied to find the optimal scheduling of the micro-grid under the uncertainties. The proposed method is implemented to a real case study. Impacts of variations in each element of the micro-grid and its associated uncertainty on the results are investigated through a sensitivity analysis. Highlights: Modeling the uncertainty of the wind and solar power generation and load consumption using fuzzy sets concepts. Taking into account the renewable energy subsidies and balancing penalties. Considering the uncertainty of maximum charging and discharging capacity of the batteries and output power of the fuel cells. Presenting Fuzzy mixed-integer linear programming for day-ahead scheduling a nonisolated micro-grid with renewable resources. Performing sensitivity analysis of variations of the different parameters on the optimal scheduling of the micro-grid.