Evaluating the impact of BESSs in the Jeju island power system

Jin, Kyung-Min; Kim, Eel-Hwan

doi:10.1109/icrera.2012.6477349

Cited by 6 publications

(1 citation statement)

References 3 publications

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“…Another technology presented in [17, 18] is lithium‐ion battery which is an energy saving technology with a high‐energy density and acceptable energy efficiency. This technology has a very notable potential for the WFPFS.…”

Section: Introductionmentioning

confidence: 99%

Mitigation of windfarm power fluctuation by adaptive linear neuron‐based power tracking method with flexible learning rate

Jannati¹,

Hosseinian²,

Vahidi³

et al. 2014

IET Renewable Power Generation

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Most wind turbine generators installed in large windfarms are of variable speed types operating at the maximum power point tracking mode to generate the maximum amount of power. Owing to this fact and regarding the random nature of the windspeed, the output power of the windfarm fluctuates. Fluctuating power is a serious problem for high capacity power plants and should be smoothed. As an effective factor on the required battery energy storage system (BESS) capacity value, tracking is the most important part performed by a coordinated control system in the power smoothing process. An ADAptive LInear NEuron (ADALINE)-based power tracking method with a flexible learning rate is proposed in this study. Furthermore, a particle swarm optimisation-based calculation of the learning rate is presented for optimising the proposed tracking method which reduces the required BESS capacity and the investment cost. Moreover, a charging/discharging algorithm for the BESS units is proposed which decreases the number of required BESS units and increases their useful life by reducing the switching activity as well. To evaluate the performance of the proposed coordinated control approach, the real output data of a 99 MW windfarm are tested. The simulation results verify the effectiveness of the proposed approach.

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Section: Introductionmentioning

confidence: 99%