Applying Virtual Inertia Control Topology to SMES System for Frequency Stability Improvement of Low-Inertia Microgrids Driven by High Renewables

Kerdphol, Thongchart; Watanabe, Masayuki; Mitani, Yasunori; Phunpeng, Veena

doi:10.3390/en12203902

Cited by 51 publications

(30 citation statements)

References 27 publications

(98 reference statements)

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“…Similarly, the share of the UK's electricity generation from renewable sources reached 35.5% in 2019 [2]. Energy security and system balance issues are likely to arise due to the intermittent nature of many clean energy sources such as wind and solar as they begin to make up a significant part of the energy generation mix [3,4]. Several methods have been used to ensure power system resiliency while allowing high share of renewable energy resources such as demand side management [5], smart grid [6], energy storage [7] and capacity markets (CM) [8].…”

Section: Introductionmentioning

confidence: 99%

Degradation Cost Analysis of Li-Ion Batteries in the Capacity Market with Different Degradation Models

et al. 2020

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Increased deployment of intermittent renewable energy plants raises concerns about energy security and energy affordability. Capacity markets (CMs) have been implemented to provide investment stability to generators and secure energy generation by reducing the number of shortage hours. The research presented in this paper contributes to answering the question of whether batteries can provide cost effective back up services for one year in this market. The analysis uses an equivalent circuit lithium ion battery model coupled with two degradation models (empirical and semi-empirical) to account for capacity fade during battery lifetime. Depending on the battery’s output power, four de-rating factors of 0.5 h, 1 h, 2 h and 4 h are considered to study which de-rating strategy can result in best economic profit. Two scenarios for the number of shortage hours per year in the CM are predicted based on the energy demand data of Great Britain and recent research. Results show that the estimated battery profit is maximum with 2 h and 1 h de-rating factors and minimum with 4 h and 0.5 h. Depending on the battery degradation model used, battery degradation cost can considerably impact the potential profit if the battery’s temperature is not controlled with adequate thermal management system. The empirical and semi-empirical models predict that the degradation cost is minimum at 5 °C and 25 °C respectively. Moreover, both models predict degradation is minimum at lower battery charge levels. While the battery’s capacity fade can be minimized to make some profits from the CM service, the increased shortage hours can make providing this service not economically viable.

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Section: Introductionmentioning

confidence: 99%

Degradation Cost Analysis of Li-Ion Batteries in the Capacity Market with Different Degradation Models

et al. 2020

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“…All the parameters of the studied system are provided in Table 1 according to the provided system data in [38]. The transfer function of the thermal power plant governor G g (s) and the turbine G t (s) for area a are modelled as follows in [39]:…”

Section: Mathematical Modelling Of the Studied Multi-area Power Smentioning

confidence: 99%

“…where, x denotes to the studied area (where x ∈ {a, b} FIGURE 2: The overall structure and system modelling of the studied two-area interconnected power system. and the PV generation G P V (s) for area b are modelled as follows in [39] :…”

Section: Mathematical Modelling Of the Studied Multi-area Power Smentioning

confidence: 99%

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An Optimized Hybrid Fractional Order Controller for Frequency Regulation in Multi-Area Power Systems

et al. 2020

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Multi-area power systems inhere complicated nonlinear response, which results in degraded performance due to the insufficient damping. The main causes of the damping problems are the stochastic behavior of the renewable energy sources, loading conditions, and the variations of system parameters. The load frequency control (LFC) represents an essential element for controlling multi-area power systems. Therefore, the proper design of the controllers is mandatory for preserving reliable, stable and high-quality electrical power. The controller has to suppress the deviations of the area frequency in addition to the tie-line power. Therefore, this paper proposes a new frequency regulation method based on employing the hybrid fractional order controller for the LFC side in coordination with the fractional order proportional integral derivative (FOPID) controller for the superconducting energy storage system (SMES) side. The hybrid controller is designed based on combining the FOPID and the tilt integral derivative (TID) controllers. In addition, the controller parameters are optimized through a new application of the manta ray foraging optimization algorithm (MRFO) for determining the optimum parameters of the LFC system and the SMES controllers. The optimally-designed controllers have operated cooperatively and hence the deviations of the area frequency and tie-line power are efficiently suppressed. The robustness of the proposed controllers is investigated against the variation of the power system parameters in addition to the location and/or magnitude of random/step load disturbances.

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“…The improvement of frequency regulation by using kinetic energy of variable speed wind turbine and DC capacitor of VSC-HVDC has been carried in Guo et al (2020). In Kerdphol et al (2019), frequency improvement using SMES based virtual inertia control over traditional ESS-based virtual inertia control in a microgrid has been shown. The concept of VSG has been applied in microgrids to control distributed generation sources (Alipoor et al, 2015; Wang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Distributed Virtual Synchronous Generator approach versus Singular Virtual Synchronous Generator approach: A dynamic stability evaluation

2020

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This paper reports the modeling and dynamic performance of a wind penetrated multi-area power system incorporating a Singular Virtual Synchronous Generator (SVSG)/Distributed Virtual Synchronous Generator (DVSG). The active and reactive power controls are achieved by using Superconducting Magnetic Energy Storage (SMES) as Virtual Synchronous Generator (VSG). SMES based VSG control parameters are tuned offline using genetic algorithm (GA). Two topologies of VSGs are considered in this paper: SVSG at lowest inertia generator bus (SVSGGENBUS), SVSG at load bus (SVSGLOADBUS) and DVSG of comparatively smaller rating at three lowest inertia generator buses. A modified 18 machine, 70-bus power system is simulated in MATLAB/Simulink environment. System performance is assessed for two different types of disturbances: step wind disturbance and three-phase fault. The simulation results show that rate of change of frequency (ROCOF), deviations in frequency and voltage are minimized with DVSG. Transient stability measured in terms of critical clearing time (CCT) verifies that CCT is increased by DVSG topology.

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Applying Virtual Inertia Control Topology to SMES System for Frequency Stability Improvement of Low-Inertia Microgrids Driven by High Renewables

Cited by 51 publications

References 27 publications

Degradation Cost Analysis of Li-Ion Batteries in the Capacity Market with Different Degradation Models

Degradation Cost Analysis of Li-Ion Batteries in the Capacity Market with Different Degradation Models

An Optimized Hybrid Fractional Order Controller for Frequency Regulation in Multi-Area Power Systems

Distributed Virtual Synchronous Generator approach versus Singular Virtual Synchronous Generator approach: A dynamic stability evaluation

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