Ali Alizadeh Ph.D. Candidate

Ali Alizadeh

Ph.D. Candidate

About me

Please accept my warmest welcome to my personal website.

My first and last names are Ali and Alizadeh. I was born in 1995 in Tabriz, a city in the northwest of Iran. I was admitted to bachelor degree when I was 18 at Shahid Madani University. Then, I was accepted to continue my education in the power system field at the University of Tehran, the most prestigious university in Iran, as a master student. In this period, I was working on reliability in distribution systems under natural monopoly. You can find more information about my master thesis by clicking on .

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Currently, I am a Ph.D. candidate at Laval University under Prof. Kamwa's direct supervision. In my Ph.D., I am working on reliability in smart grids by the Transactive Energy Control paradigm, which is based on marketing control in a decentralized fashion. Click on to know more.

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Now, I am 27 years old.

Education

Jan 2021-Present

Sep 2017- Sep 2020

Sep 2013- Aug 2017

2020- Present

Doctoral of Philosophy_ Thesis Title: Exploitation of Flexibilities Using A Fully-Distributed Hierarchical Transactive Control To Schedule Resources under A high Penetration of Renewables.

Supervisors: Innocent Kamwa

and

Ali Moeini

GPA: A+

Mater of Science_ Thesis Title: Performance-Based Regulation in Distribution Systems.

Supervisors:

Hamid Lesani

and

Alireza Fereidunian

GPA: 3.89/4 (17.99/20)

Bachelor of Science_ Project Title: Speed Control of Two-Mode Motors Using Rectified-Based Full Bridge Inverters with A Constant Ratio of Voltage and Frequency.

Supervisor:

MohammadReza Banaei

GPA: 3.86/4 (18.16/20)

IEEE Member from 2020 until Present. Reviewer in IEEE Transactions on Smart Grid, IEEE Transactions on Power System, and IET Generation, Transmission, and Distribution Journals.

Research

Smart Grid Lab

Supervisor: Innocent Kamwa

Jan 2021 - Present

Research Assistant

Transactive Energy Control (TEC) paradigm enables involving Microgrids (MGs) in the energy management procedure to realize the transition of energy systems using market-based mechanisms. This Thesis, in this regard, proposes a review including state-of-the-art energy management using the TEC concept in MGs, highlighting the types of interactions among prosumers and MG operators, uncertainty models, and Energy Management System (EMS) designs. The proposed review illustrates that the distributed style of interactions with prosumer-centric uncertainty management has scarcely been investigated, while it is more beneficial in terms of financial, computational, and communication aspects. Hence, to pave the path for future research, a distributed TEC is proposed based on the consensus Alternative Direction Method of Multipliers (ADMM), wherein prosumers can solve their prosumption problem using a novel EMS and the MG operator acts as a coordinator to oversee system constraints. The EMS relies on a two-stage stochastic model, whereby prosumers can personally manage the associated risk using conditional value-at-risk (CVaR). The implementation results indicate that the accuracy, runtime, and communication burden are improved using the proposed distributed TEC by 32.76%, 15.68%, and 1,094.6% compared to the decentralized TEC. Moreover, prosumers can save a further 5.75% on their bills using prosumer-centric uncertainty management. Consequently, the proposed review illuminates the research direction, while the proposed distributed TEC with the prosumer-centric uncertainty management elaborates on the identified gaps to accelerate the pace of improvement in this area.

System and Machine Lab

Supervisor: Hamid Lesani

Sep 2017 - Sep 2020

Research Assistant

After restructuring, improvement of services and reliability became one of the most important matters in the power system. The distribution system as the last chan of power supply plays an essential role in this issue. However, owing to natural monopoly, the quality of the services and the reliability decreases tangibly. To solve this problem, a regulation in distribution systems is proposed as an effective tool that is determined by the regulator. In this thesis, the reliability assessment problem is considered from the distribution companies’ point of view. In other words, in this study, a method is presented to contemplate a regulation scheme (reward-penalty scheme) in the reliability assessment problem. in this method which is named dynamic regulation, the improvement of reliability and financial performance are taken into account. Furthermore, the first step to reliability assessment is failure rate modeling, for which a comprehensive method is addressed. In this approach, the failure rate is modeled by Weibull Function and Neural Network Time Series. In the next step, a linear method is proposed to consider the maintenance problem and DG placement for better-managing investment in the reliability assessment problem at the same time. These models are applied to two-bus of Roy Billington Test System (RBTS2) and the results confim their efficiency.

Publication List

Energy Management in Microgrids Using Transactive Energy Control Concept Under High Penetration of Renewables; A Survey and Case Study, Renewable and Sustainable Energy Reviews, 2023.

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A Multi-Period Regulation Methodology for Reliability as Service Quality Considering Reward-Penalty Scheme, IEEE Transactions on Power Delivery, 2022.

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An Exact MILP Model for Joint Switch Placement and Preventive Maintenance Scheduling Considering Incentive Regulation, IET Generation, Transmission, and Distribution, 2022.

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An Efficient Distributed Transactive Energy Control Model Using Adaptive Consensus ADMM, 10th International Conference on Systems and Control (ICSC’2022), 2022.

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Reliability-Centered Maintenance Scheduling Considering Failure Rates Uncertainty: A Two-Stage Robust Model, IEEE Transactions om Power Delivery, 2021.

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A Recurrent Neural Network Approach to Model Failure Rate Considering Random and Deteriorating Failures, 26th International Computer Conference (CSICC), 2021.

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A Transactive Energy Market Mechanism with Loss Implication, IEEE Transactions on Smart Grid, 2020.

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Performance Based Regulation Framework for Demand Side Management, 24th Electrical Power Distribution Conference, 2019.

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