Optimal sizing of the wind farm and wind farm transformer using MILP and dynamic transformer rating

• Published in: International journal of electrical power & energy systems 2022-03, Vol.136, p.107645, Article 107645
• Main Authors: Molina Gómez, Andrea, Morozovska, Kateryna, Laneryd, Tor, Hilber, Patrik
• Format: Article
• Language: English
• Subjects: Dynamic transformer rating; Electrical and Electronic Engineering; Electrical Engineering; Elektro- och systemteknik; Energy Engineering and Power Technology; Planning of power systems; Renewable generation; Wind energy integration
• ISSN: 0142-0615; 1879-3517; 1879-3517
• DOI: 10.1016/j.ijepes.2021.107645

•Expansion of the wind parks using existing power grid infrastructure.•Effective sizing of the transformers and wind farms.•Using dynamic rating for efficient and economical sizing of wind sites.•Dynamic rating allows to fit up to 30% extra wind power generation using exiting substation transformer. An increase in electricity demand and renewable penetration requires electrical utilities to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively based on static rated power. However, load and weather change continuously and hence, transformers are not used most efficiently. For this reason, new technology has been developed: Dynamic transformer rating (DTR). Applying DTR makes it possible to load transformers above the nameplate rating without affecting their lifetime expectancy. This study uses DTR for short-term and long-term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer and using it as an input to a Mixed-Integer Linear Programming (MILP) model. Regarding the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As a result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are critical parameters for the wind farm’s feasibility.