Modeling, Simulation and Decentralized Control of Islanded Microgrids

Mohammadi, Farideh Doost

doi:10.33915/etd.7113

Cited by 2 publications

(5 citation statements)

References 23 publications

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“…By using equation (18,19) and equations (22,23) with the assumption that %&' = %&' * , state space modeling of this part can be derived as in (31):…”

Section: A Power Controllermentioning

confidence: 99%

“…Equations of (15,16,20,24,31) can be used to find out the complete state space model for each inverter as in (32).…”

Section: A Power Controllermentioning

confidence: 99%

“…In [24], a comprehensive small signal model for inverter based MGs has been considered with considering the primary control loop only. In [31] secondary controller is proposed but only for the frequency control. In this paper, a secondary voltage controller has been proposed for a comprehensive small signal model of MGs (i.e.…”

Section: Introductionmentioning

confidence: 99%

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State space modeling of inverter based microgrids considering distributed secondary voltage control

Banadaki

Mohammadi

Feliachi

2017

2017 North American Power Symposium (NAPS)

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Abstract-Appropriate control of high penetration renewable energies in power systems requires a complete modeling of the system. In this paper, a comprehensive state space modeling of voltage source inverters, networks and loads are studied. We have modeled a secondary voltage control that utilizes the nominal set points of the output voltage as the input for the controller design. A distributed control algorithm only requiring a sparse communication between neighboring distributed generators (DGs) is used. The proposed secondary voltage model is applied on a microgrid with three DGs and two loads to verify the results.

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“…By using equation (18,19) and equations (22,23) with the assumption that %&' = %&' * , state space modeling of this part can be derived as in (31):…”

Section: A Power Controllermentioning

confidence: 99%

“…Equations of (15,16,20,24,31) can be used to find out the complete state space model for each inverter as in (32).…”

Section: A Power Controllermentioning

confidence: 99%

See 1 more Smart Citation

State space modeling of inverter based microgrids considering distributed secondary voltage control

Banadaki

Mohammadi

Feliachi

2017

2017 North American Power Symposium (NAPS)

Self Cite

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“…where ω ni is the nominal frequency set-point for each inverter [131,132]. As seen in (4.18), all inverter angle dynamics∆δ i are a function of the first inverter active power ∆P 1 .…”

Section: Vsi State-space Modelmentioning

confidence: 99%

“…where A M G , B M G are microgrid characteristic matrices and can be found in detail in [131]. Having this state-space representation of the microgrid, we can design an optimal secondary control for this system and compare the results of secondary and primary control of the microgrid.…”

Section: Complete Microgrid Modelmentioning

confidence: 99%

Resilient Stochastic Control Strategies in Cyber-Physical Microgrids

Khalghani¹

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Microgrids can locally fulfill the demand and operate isolated from the main grid to sustain critical services even in case of large-scale outages and cascading power failures. Microgrids are the integration of a large number of distributed energy resources in a decentralized way such that the energy supply reliability and resiliency are enhanced against natural disasters, physical and cyber disruptions. This dissertation focuses on three main challenges regarding technologies emerging in microgrids. 1) According to the fast growing number of Electric Vehicles (EV) deployment, their impacts on microgrids resulted from their uncertain behaviors are new concerns for the microgrid operators. These concerns can be EV charging and discharging schedule and locations of EV parking-lots in the system which are considered and solved using stochastic modeling and optimization algorithms based on Artificial Intelligence (AI) techniques. First, charging and discharging scheduling of EVs is minimized using Particle Swarm Optimization (PSO) Algorithm such that the daily load profile is flattened (peak and off-peak shaving) with considering constraints of State-Of-Charging (SoC). Due to the uncertain nature of daily travelling EVs between residential and administrative areas, chronological stochastic modeling is suggested. Furthermore, a multi-objective optimization based on PSO and fuzzification theory is proposed to find the best location of parking lots for these EV aggregators. Two indices, voltage unbalance and power loss, for locating the EV aggregators are considered. During peak hour, these indices can be more critical for a three-phase distribution system. 2) As the penetration of renewable energies, generally, uncertainties, increase in microgrids, a more dynamic and complex system is emerging that makes frequency control of the islanded microgrid more challenging due to stochastic dynamic encumbrances. These stochastic encumbrances can create oscillatory frequency response, which eventually leads to astray controls and instability even under primary and traditional secondary controllers. This dissertation develops AI-based and analytical based secondary control for the islanded microgrids to compensate for the frequency deviation in the presence of intermittent energy resources and uncertain load changes. Two types of artificial I wish to express my deep and sincere gratitude to my supervisor Prof. Jignesh Solanki for his guidance, support and encouragement in entire my Ph.D. program. Prof. Jignesh Solanki was always there to patiently listen and to give valuable advice. I will not forget his great feedback for enhancing my research presentation skills. Besides my supervisor, I cannot begin to express my thanks to Prof. Sarika Khushalani Solanki for participating in lengthy discussions to perfectly align my research and present my accomplishments. She has been very supportive and sympathetic in both my professional and daily lives. Working under these two great professors was a golden opportunity for me to leverage a...

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Modeling, Simulation and Decentralized Control of Islanded Microgrids

Cited by 2 publications

References 23 publications

State space modeling of inverter based microgrids considering distributed secondary voltage control

State space modeling of inverter based microgrids considering distributed secondary voltage control

Resilient Stochastic Control Strategies in Cyber-Physical Microgrids

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