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Dynamic control of intergrated wind farm battery energy storage systems for grid connection
Author(s)
Gwabavu, Mandisi
Date Issued
2020
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
The intermittent nature of wind power is a major challenge for wind as an energy
source. Wind power generation is therefore difficult to plan, manage, sustain, and track
during the year due to different weather conditions. The uncertainty of energy loads
and power generation from wind energy sources heavily affects the system stability.
The battery energy storage system (BESS) plays a fundamental role in controlling and
improving the efficiency of renewable energy sources. Stochasticity of wind speed and
reliability of the main system components are considered.
This paper presents a dynamical control system based on model predictive control
(MPC) in real time, to make full use of the flexibility and controllability of energy storage
to mitigate problems of wind farm variability and intermittency. The control scheme first
plans the expected output, then stochastic optimization is used to optimize grid
integrated wind farm BESS output power, develop an optimal operation strategy for
BESS, and prevent some unpredictable conditions that may have impacts on the
stability of the system. The results show that the proposed method can reduce gridconnected
wind power fluctuations, limit system faults, control command for the BESS
in the dispatching period, and ensure system stability for grid connection..
source. Wind power generation is therefore difficult to plan, manage, sustain, and track
during the year due to different weather conditions. The uncertainty of energy loads
and power generation from wind energy sources heavily affects the system stability.
The battery energy storage system (BESS) plays a fundamental role in controlling and
improving the efficiency of renewable energy sources. Stochasticity of wind speed and
reliability of the main system components are considered.
This paper presents a dynamical control system based on model predictive control
(MPC) in real time, to make full use of the flexibility and controllability of energy storage
to mitigate problems of wind farm variability and intermittency. The control scheme first
plans the expected output, then stochastic optimization is used to optimize grid
integrated wind farm BESS output power, develop an optimal operation strategy for
BESS, and prevent some unpredictable conditions that may have impacts on the
stability of the system. The results show that the proposed method can reduce gridconnected
wind power fluctuations, limit system faults, control command for the BESS
in the dispatching period, and ensure system stability for grid connection..
Additional information
Thesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2020
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