Integration of distributed energy resource models in the VSC control for microgrid applications

García-Ceballos, C.; Pérez-Londoño, Sandra; Flórez, Juan José Mora

doi:10.1016/j.epsr.2021.107278

Cited by 17 publications

(6 citation statements)

References 31 publications

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“…Additionally, since the number of parameters increases with each CIDER in the microgrid, these are grouped, and each group uses the same control parameters. us, the parameters sought by the optimisation strategy are given by (13).…”

Section: Execution Of the Optimisation Processmentioning

confidence: 99%

“…Even though adjusting the PI control constants is considered in many proposals, a standard process is not available, which makes the microgrid adjustment from scratch difficult. Consequently, it is desirable to obtain a simple and effective method that allows researchers to design and adjust multi-CIDER microgrids straightforwardly, and then deeper and detailed studies can be developed [13].…”

Section: Introductionmentioning

confidence: 99%

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Iterative Approach for Tuning Multiple Converter-Integrated DER in Microgrids

García-Ceballos

Pérez-Londoño

Flórez

2022

International Transactions on Electrical Energy Systems

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This paper proposes an iterative approach to adjust the control parameters of multiple power converters within a microgrid, which operates in grid-connected and grid-islanded modes. The adequate control parameters are determined using an optimisation-based strategy, local measurements, and results obtained in previous algorithm iterations. The proposed objective function is based on the integral time-weighted absolute error (ITAE), modified to improve the microgrid control performance. The proposed approach addresses the control tuning complexity by considering an incremental strategy, starting from adjusting basic microgrids, continuing to the setting of intermediate microgrids, and finalising when the target microgrid control is fine adjusted. The results obtained at the CIGRE LV benchmark microgrid validate the proposal, obtaining during faults, the maximum deviations from rated frequency around 2.2% and 0.3% in grid-islanded or grid-connected cases, respectively. Also, voltage and power references are adequately followed during steady-state regardless of the microgrid operation mode, where the steady voltage profile is below 10% variation. The obtained results demonstrate the proposed approach advantages, which straightforwardly adjust multiple converters integrated into a microgrid. The main contributions are as follows: (a) the microgrid model is not required, and (b) only measurements at the point of common coupling of the distributed energy resource are used; consequently, the proposed tuning approach is especially applicable to complex microgrids. Finally, finely adjusted microgrids are required for further operation or protection studies where complex system configurations are commonly required.

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Section: Execution Of the Optimisation Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Iterative Approach for Tuning Multiple Converter-Integrated DER in Microgrids

García-Ceballos

Pérez-Londoño

Flórez

2022

International Transactions on Electrical Energy Systems

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“…Due to the inherent characteristics of new energy output, the impact of large-scale grid connection on the power grid has become greater, and the fluctuation of new energy output has brought enormous pressure to the safety of the power grid. In order to promote the high-quality development of new energy, help achieve the "dual carbon" goal, and ensure the safe and stable operation of the system, it is urgent to carry out a balanced impact analysis of the new energy grid [1][2]. In this context, taking into account the consumption situation of new energy, the carrying capacity of the main transformer, and other information, assist users in balancing risk mining and provide optimization assistance strategies to enhance the output, grid connection, and consumption capacity of new energy, ensure the utilization rate of distributed new energy, and achieve balanced, safe, and stable operation of the distributed new energy grid [3].…”

Section: Introductionmentioning

confidence: 99%

Risk analysis method for balancing positive and negative backup gaps in distributed new energy grids based on historical load peak and valley values and big data

Zhang,

Xia

2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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This study proposes a risk analysis method for balancing positive and negative reserve gaps in distributed new energy grids based on historical load peak valley values and big data. This method analyzes historical load data, explores potential laws and correlations in distributed new energy grid data, and combines ARIMA model and hidden Markov model to describe the operation of distributed new energy grids, obtaining the evaluation results of distributed new energy power supply capacity. Based on the evaluation results, calculate the positive and negative backup gaps and obtain the risk indicator values at each time point. Analyze and make decisions based on risk indicator values to achieve risk analysis. The experimental results indicate that this method can accurately evaluate the risk of positive and negative backup gaps in distributed new energy grids, and provide reasonable decision-making basis for grid managers. It is expected to play an important role in practical applications.

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“…Starting with the modeling, authors in [4] improve the balance between the dynamic model precision and the steady state of the DER's converter by modifying the control reference to simplify its integration into the control algorithm. After modelling the MG, authors in [5] rely on multi-loop control for the voltage optimal control strategy.…”

Section: Introductionmentioning

confidence: 99%

Active Disturbance Rejection Control for Distributed Energy Resources in Microgrids

Hezzi,

Elbouchikhi,

Bouzid

et al. 2024

Machines

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Motivated by the significant efforts developed by researchers and engineers to improve the economic and technical performance of microgrids (MGs), this paper proposes an Active Disturbance Rejection Control (ADRC) for Distributed Energy Resources (DER) in microgrids. This approach is a nonlinear control that is based on a real-time compensation of different estimated disturbances. The DER operates along with the electrical grid to provide the load requirements. This load has a nonlinear and uncertain character, which presents a source of unmodeled dynamics and harmonic perturbations of the MG. The main objective of this paper is to ensure the stability and the continuity of service of the distributed generation resources by controlling the DC-AC converter. The ADRC as a robust control technique is characterized by its ability to compensate for the estimated total disturbances caused by the load variation and the external unmodeled perturbations to guarantee the high tracking performance of sinusoidal reference signals in the DER system. The ADRC technique is characterized by its nonlinear function, which provides a high robustness to the controlled system. However, in order to simplify the control structure by keeping its high reliability, this paper proposes to replace the nonlinear function with a simple error (termed linear ADRC), compares the impact of this modification on the system performances, and evaluates its operation in the presence of linear and nonlinear load variations. Simulation results are presented to demonstrate the efficiency of the proposed control approach for a three-phase DER.

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Integration of distributed energy resource models in the VSC control for microgrid applications

Cited by 17 publications

References 31 publications

Iterative Approach for Tuning Multiple Converter-Integrated DER in Microgrids

Iterative Approach for Tuning Multiple Converter-Integrated DER in Microgrids

Risk analysis method for balancing positive and negative backup gaps in distributed new energy grids based on historical load peak and valley values and big data

Active Disturbance Rejection Control for Distributed Energy Resources in Microgrids

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