Power-Management Strategies for a Grid-Connected PV-FC Hybrid System

Khanh, Loc Nguyen; Seo, Jae-Jin; Kim, Yun-Seong; Won, Dong-Jun

doi:10.1109/tpwrd.2010.2047735

Cited by 137 publications

(32 citation statements)

References 13 publications

(20 reference statements)

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“…The rotor-side converter control objectives are MPPT in WTG and stator side reactive power management. Different control schemes such as direct torque control(DTC)and direct power control(DPC)for a DFIG in [18] and [19] have been proposed. In this paper, the proposed DTC scheme [17], shown in Fig.6, has been chosen as a control scheme for the rotor-side converter.…”

Section: The Dfig Converters Controller a Rotor-side Converter Contrmentioning

confidence: 99%

Optimal Voltage And Frequency Control Of A Microgrid System Using A Teaching-Learning Based Optimization (TLBO) Algorithm

Hedayati

Abbasi²

2015

International Journal of Electrical Electronics and Data Communication

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Abstract-The stability is an important topic to plan and manage the energy in the microgrids as the same as the conventional power systems. The voltage and frequency stability is one of the most important issues recently studied in microgrids. The objectives of this paper are the modelling and designing of the components and optimal controllers for the voltage and frequency control of the AC/DC hybrid microgrid under the different disturbances. Since the PI controllers have the advantages of simple structure and easy implementation, so they were designed and modeled in this paper. The teachinglearning based optimization (TLBO) algorithm is used to optimize the controllers' parameters. According to the achieved results, the optimal PI controllers have a good performance in voltage and frequency control of the microgrid.

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Section: The Dfig Converters Controller a Rotor-side Converter Contrmentioning

confidence: 99%

Optimal Voltage And Frequency Control Of A Microgrid System Using A Teaching-Learning Based Optimization (TLBO) Algorithm

Hedayati

Abbasi²

2015

International Journal of Electrical Electronics and Data Communication

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“…The hybrid system was operating in islanded mode. In [5], a power management strategy for a grid-connected PV-FC hybrid source was presented where the hybrid sources were operating in unit power control and feeder flow control modes. The strategy is to operate PV at MPPT and the fuel cell within its power range and reduce the number of switches between the two control modes.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

et al. 2017

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Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller K p (proportional constant) and T i (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation.

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“…Nevertheless, given the maximum fluctuation limitation, there is a range of control strategies to reduce the fluctuations to under this limit. At present, the two most often proposed strategies in the literature are ramp-rate control [16][17][18][19][20][21] and the moving-average (MA) [22][23][24][25]. The main advantage of MA is that, if the system is equipped with an ideal converter and battery, by definition of the mean value, the value of the energy in the ESS at the beginning and end of any given day should be the same.…”

Section: Introductionmentioning

confidence: 99%

Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems

et al. 2014

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Abstract:The variations in irradiance produced by changes in cloud cover can cause rapid fluctuations in the power generated by large photovoltaic (PV) plants. As the PV power share in the grid increases, such fluctuations may adversely affect power quality and reliability. Thus, energy storage systems (ESS) are necessary in order to smooth power fluctuations below the maximum allowable. This article first proposes a new control strategy (step-control), to improve the results in relation to two state-of-the-art strategies, ramp-rate control and moving average. It also presents a method to quantify the storage capacity requirements according to the three different smoothing strategies and for different PV plant sizes. Finally, simulations shows that, although the moving-average (MA) strategy requires the smallest capacity, it presents more losses (2-3 times more) and produces a much higher number of cycles over the ESS (around 10 times more), making it unsuitable with storage technologies as lithium-ion. The step-control shown as a better option in scenery with exigent ramp restrictions (around 2%/min) and distributed generation against the ramp-rate control in all ESS key aspects: 20% less of capacity, up to 30% less of losses and a 40% less of ageing. All the simulations were based on real PV production data, taken every 5 s in the course of one year (2012) from a number of systems with power outputs ranging from 550 kW to 40 MW. OPEN ACCESSEnergies 2014, 7 6594

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Power-Management Strategies for a Grid-Connected PV-FC Hybrid System

Cited by 137 publications

References 13 publications

Optimal Voltage And Frequency Control Of A Microgrid System Using A Teaching-Learning Based Optimization (TLBO) Algorithm

Optimal Voltage And Frequency Control Of A Microgrid System Using A Teaching-Learning Based Optimization (TLBO) Algorithm

A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems

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