Fast Frequency Regulation in Islanded Microgrid Using Model-Based Load Estimation

Hussain, Amir; Hasan, Shamim; Patil, Sumit; Shireen, Wajiha

doi:10.1109/tec.2021.3076784

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…Also, frequency security constraints as a crucial part of secure operation in IMGs are neglected in papers earlier examined. The frequency control mechanism is an essential need for IMGs ignoring this issue can severely decrease the operation reliability [17]. In [17], [2], and [1], some methods for frequency control in IMGs are offered, but only a few works in this literature have included the frequency issues of IMGs in EMS models.…”

Section: B Background and Literature Reviewsmentioning

confidence: 99%

“…The frequency control mechanism is an essential need for IMGs ignoring this issue can severely decrease the operation reliability [17]. In [17], [2], and [1], some methods for frequency control in IMGs are offered, but only a few works in this literature have included the frequency issues of IMGs in EMS models. In [3], a nonlinear EMS model considers short-term fluctuations and their effects on frequency and operation.…”

Section: B Background and Literature Reviewsmentioning

confidence: 99%

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Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Abedi

Yousefi

Shafie‐khah

2024

IEEE Trans. Smart Grid

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With the developments of isolated microgrids (IMGs) and prosumers in remote areas, energy trading has become more significant in IMGs. On the other hand, the lack of an upstream network and the system's low inertia could endanger the secure operation of these networks. This paper presents a Micro-Market (µM) model for IMGs with the precise modeling of hierarchical control structure. To deal with the IMG's low inertia and high intermittency of renewable energy sources (RES), the proposed µM manages the active-reactive power and schedules sufficiently primary and secondary active reserves to preserve frequency in a predefined range. In addition, a bidirectional linearized AC power flow is established to schedule the reactive reserve and the proposed model is formulated as a two-stage stochastic mixed-integer linear problem (MILP) to maximize social welfare (SW) during the next 24 hours. To verify the ability of the proposed model, the µM is tested in an IMG based on a CIGRE medium-voltage benchmark system and different operational cases are simulated. The results showed that considering hierarchical control levels and technical issues of the IMG in the proposed model is a cost-effective manner to maximize the social welfare while the secure operation of the IMG is ensured.

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Section: B Background and Literature Reviewsmentioning

confidence: 99%

Section: B Background and Literature Reviewsmentioning

confidence: 99%

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Abedi

Yousefi

Shafie‐khah

2024

IEEE Trans. Smart Grid

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“…Table 6 shows the functions of different layers and their response time. Two main challenges in the control of microgrids are frequency [37,38] and voltage regulation. For frequency and voltage regulation, model-based controllers have been proposed.…”

Section: Microgridsmentioning

confidence: 99%

Model-Free Predictive Control and Its Applications

2022

Self Cite

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Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper.

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Multiobjective Laguerre Functions−Based Discrete−Time Model Predictive Control: A Fast Inner−Loop Controller for Grid−
Saeedian
¹
,
Gomis‐Bellmunt
²
,
Pouresmaeil
³

2022
Electric Power Systems Research
2
0
0
0
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Fast Frequency Regulation in Islanded Microgrid Using Model-Based Load Estimation

Cited by 6 publications

References 25 publications

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Model-Free Predictive Control and Its Applications

Multiobjective Laguerre Functions−Based Discrete−Time Model Predictive Control: A Fast Inner−Loop Controller for Grid−
Saeedian
¹
,
Gomis‐Bellmunt
²
,
Pouresmaeil
³

2022
Electric Power Systems Research
2
0
0
0
View full text Add to dashboard Cite

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Fast Frequency Regulation in Islanded Microgrid Using Model-Based Load Estimation

Cited by 6 publications

References 25 publications

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

Model-Free Predictive Control and Its Applications

Multiobjective Laguerre Functions−Based Discrete−Time Model Predictive Control: A Fast Inner−Loop Controller for Grid−Saeedian1, Gomis‐Bellmunt2, Pouresmaeil3 2022Electric Power Systems Research2000View full textAdd to dashboardCite

Contact Info

Product

Resources

About

Multiobjective Laguerre Functions−Based Discrete−Time Model Predictive Control: A Fast Inner−Loop Controller for Grid−
Saeedian
¹
,
Gomis‐Bellmunt
²
,
Pouresmaeil
³

2022
Electric Power Systems Research
2
0
0
0
View full text Add to dashboard Cite