Control Methods for Energy Storage for Dispatching Intermittent Renewable Energy Sources
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2009-11-13
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Abstract
Solar, wind and other renewable energy sources are becoming an important part of energy supply to the power grid. Integrating a battery energy storage system (BESS) with a solar photovoltaic (PV) system or a wind farm can make these intermittent renewable energy sources more dispatchable. In this thesis, three different control methods for BESS are proposed for this purpose.
For dispatching, the set point for the controllers is determined first using the historical data. Then using this reference, the power and energy ratings required for the BESS is calculated, and the battery operation in terms of charge/discharge duration is characterized.
For optimal use of a BESS to minimize the deviations from dispatch set points, three control methods for BESS have been developed. The simulations have shown that the dispatch performance obtained with SOC feedback method is unsatisfactory compared to the other two methods namely optimal control and rule based control. The rule based control, and the optimal control performs very similar since the rule based control corresponds to the closed loop implementation of the optimal control. Moreover, the rule based method has several advantages over the optimal control such as less computation time, closed loop implementation, and no need for development of a mathematical model for BESS.
In terms of BESS operation, it is seen that the BESS charge/discharge frequency is relatively high in this application; and hence, new type of batteries with high charge/discharge cycling rates are needed. Moreover, the control methods considered make a compromise in that they didn’t utilize the BESS full capacity in order to extend the lifetime of the BESS, and hence, a large size BESS – about 15%-25% of the solar PV/wind farm capacity – is needed to have an effective hourly dispatch.
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Battery energy storage system (BESS), optimal control, dispatchability, photovoltaic system, rule based control, wind energy
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Degree
PhD
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Electrical Engineering
