学位论文详细信息
Generation Scheduling in Microgrids under Uncertainties in Power Generation
power;generation;renewable;energy;optimization;scheduling;unit commitment;microgrid;Electrical and Computer Engineering
Zein Alabedin, Ayman
University of Waterloo
关键词: power;    generation;    renewable;    energy;    optimization;    scheduling;    unit commitment;    microgrid;    Electrical and Computer Engineering;   
Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/6912/1/Zein_Alabedin_Ayman.pdf
瑞士|英语
来源: UWSPACE Waterloo Institutional Repository
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【 摘 要 】

Recently, the concept of Microgrids (MG) has been introduced in the distribution network. Microgrids are defined as small power systems that consist of various distributed micro generators that are capable of supplying a significant portion of the local demand. Microgrids can operate in grid-connected mode, in which they are connected to the upstream grid, or in isolated mode, where they are disconnected from the upstream grid and the local generators are the only source of power supply. In order to maximize the benefits of the resources available in a microgrid, an optimal scheduling of the power generation is required. Renewable resources have an intermittent nature that causes uncertainties in the system. These added uncertainties must be taken into consideration when solving the generation scheduling problem in order to obtain reliable solutions.This research studies the scheduling of power generation in a microgrid that has a group of dispatchable and non-dispatchable generators. The operation of a microgrid during grid-connected mode and isolated mode is analyzed under variable demand profiles. Two mixed integer linear programming (MILP) models for the day-ahead unit commitment problem in a microgrid are proposed. Each model corresponds to one mode of operation. Uncertainty handling techniques are integrated in both models. The models are solved using the General Algebraic Modeling System (GAMS). A number of study cases are examined to study the operation of the microgrid and to evaluate the effects of uncertainties and spinning reserve requirement on the microgrid’s expenses.

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