Date of Award

1-1-2015

Document Type

Thesis

Degree Name

M.S.

Department

Electrical Engineering

First Advisor

Amin Khodaei

Keywords

Microgrid, Mixed-Integer Programming, Security-Constrained Unit Commitment, Unit Commitment, Wind Energy, Wind Power Forecasting

Abstract

The objective of this thesis is to study the impact of high penetration wind energy in economic and reliable operation of microgrids. Wind power is variable, i.e., constantly changing, and nondispatchable, i.e., cannot be controlled by the microgrid controller. Thus an accurate forecasting of wind power is an essential task in order to study its impacts in microgrid operation. Two commonly used forecasting methods including Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) have been used in this thesis to improve the wind power forecasting. The forecasting error is calculated using a Mean Absolute Percentage Error (MAPE) and is improved using the ANN. The wind forecast is further used in the microgrid optimal scheduling problem. The microgrid optimal scheduling is performed by developing a viable model for security-constrained unit commitment (SCUC) based on mixed-integer linear programing (MILP) method. The proposed SCUC is solved for various wind penetration levels and the relationship between the total cost and the wind power penetration is found. In order to reduce microgrid power transfer fluctuations, an additional constraint is proposed and added to the SCUC formulation. The new constraint would control the time-based fluctuations. The impact of the constraint on microgrid SCUC results is tested and validated with numerical analysis. Finally, the applicability of proposed models is demonstrated through numerical simulations.

Provenance

Recieved from ProQuest

Rights holder

Abdulaziz Furreh Alanazi

File size

92 p.

File format

application/pdf

Language

en

Discipline

Electrical engineering

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