An intelligent controller for optimal vector control of induction motor

Khalghani, Mohammad Reza; Shamsinejad, Mohammad Ali; Beyki, Karim

doi:10.1109/iccaie.2011.6162108

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…With the rising trend for manufacturing and using EVs all over the world, it is interesting to study their effects on power distribution systems. The registered sales of EVs in California were more than 200,000 units in March of 2016 [20] with higher sales in the Netherlands too, which was the forerunner of EVs in Europe in 2013 [21]. A single EV penetration does not affect the operation of a distribution system; however, an aggregator of EVs has a large impact.…”

Section: Introductionmentioning

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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Section: Introductionmentioning

confidence: 99%

Resilient Stochastic Control Strategies in Cyber-Physical Microgrids

Khalghani¹

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Bi-objective regulating of DVR compensator to modify power quality's indices of load

Nejad

Zamen²,

Dadgar³

et al. 2013

22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013)

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This paper aims to present a control scheme based upon Particle Swarm Optimization (PSO) algorithm in order to compensate the key power-quality disturbances, particularly voltage sags and harmonic voltages, using a Dynamic Voltage Restorer (DVR). According to the aforesaid method, DVR's PI controller structure is regulated via multi-objective PSO algorithm. We introduce the method for distribution systems to modify both SAG and THD as major power quality indices in sensitive loads at fault conditions. Therefore, we apply the multi-objective optimization algorithm in order to attain a better performance in solving the related problems.

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An intelligent controller for optimal vector control of induction motor

Cited by 2 publications

References 12 publications

Resilient Stochastic Control Strategies in Cyber-Physical Microgrids

Resilient Stochastic Control Strategies in Cyber-Physical Microgrids

Bi-objective regulating of DVR compensator to modify power quality's indices of load

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