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Ahmad H. Milyani
Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia

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Short Biography

Ahmad H. Milyani received B.Sc (with distinction) and M.Sc degrees in Electrical and Computer Engineering from Purdue University in 2011 and 2013, respectively, and a PhD degree in Electrical Engineering from the University of Washington in 2019. He is currently an Assistant Professor with the Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia. His research interests include power systems operation and optimization, renewable and sustainable energy, power electronics, electric vehicles, and machine learning.

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Journal article
Published: 27 May 2021 in Sustainability
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Price based demand response is an important strategy to facilitate energy retailers and end-users to maintain a balance between demand and supply while providing the opportunity to end users to get monetary incentives. In this work, we consider real-time electricity pricing policy to further calculate the incentives in terms of reduced electricity price and cost. Initially, a mathematical model based on the backtracking technique is developed to calculate the load shifted and consumed in any time slot. Then, based on this, the electricity price is calculated for all types of users to estimate the incentives through load shifting profiles. To keep the load under the upper limit, the load is shifted in other time slots in such a way to facilitate end-users regarding social welfare. The user who is not interested in participating load shifting program will not get any benefit. Then the well behaved functional form optimization problem is solved by using a heuristic-based genetic algorithm (GA), wwhich converged within an insignificant amount of time with the best optimal results. Simulation results reflect that the users can obtain some real incentives by participating in the load scheduling process.

ACS Style

Thamer Alquthami; Ahmad Milyani; Muhammad Awais; Muhammad Rasheed. An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective. Sustainability 2021, 13, 6066 .

AMA Style

Thamer Alquthami, Ahmad Milyani, Muhammad Awais, Muhammad Rasheed. An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective. Sustainability. 2021; 13 (11):6066.

Chicago/Turabian Style

Thamer Alquthami; Ahmad Milyani; Muhammad Awais; Muhammad Rasheed. 2021. "An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective." Sustainability 13, no. 11: 6066.

Journal article
Published: 19 May 2021 in IEEE Access
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In this paper, a two-stage approach is proposed on a joint dispatch of thermal power generation and variable resources including a storage system. Although, the dispatch of alternate energy along with conventional resources has become increasingly important in the new utility environment. However, recent studies based on the uncertainty and worst-case scenario-oriented robust optimization methodology reveal the perplexities associated with renewable energy sources (RES). First, the load demand is predicted through a convolutional neural network (CNN) by taking the ISO-NECA hourly real-time data. Then, the joint dispatch of energy and spinning reserve capacity is performed with the integration of RES and battery storage system (BSS) to satisfy the predicted load demand. In addition, the generation system is penalized with a cost factor against load not served for the amount of energy demand which is not fulfilled due to generation constraints. Meanwhile, due to ramping of thermal units, the available surplus power will be stored in the backup energy storage system considering the state of charge of the storage system. The proposed method is applied on the IEEE-standard 6-Bus system and particle swarm optimization (PSO) algorithm is used to solve the cost minimization objective function. Finally, the proposed system performance has been verified along with the reliability during two worst-case scenarios, i.e., sudden drop in power demand and a short-fall at the generation end.

ACS Style

M. Wajahat Hassan; Thamer Alquthami; Ahmad H. Milyani; Ashfaq Ahmad; Muhammad Babar Rasheed. A Joint Optimization Model for Energy and Reserve Capacity Scheduling With the Integration of Variable Energy Resources. IEEE Access 2021, 9, 75252 -75264.

AMA Style

M. Wajahat Hassan, Thamer Alquthami, Ahmad H. Milyani, Ashfaq Ahmad, Muhammad Babar Rasheed. A Joint Optimization Model for Energy and Reserve Capacity Scheduling With the Integration of Variable Energy Resources. IEEE Access. 2021; 9 ():75252-75264.

Chicago/Turabian Style

M. Wajahat Hassan; Thamer Alquthami; Ahmad H. Milyani; Ashfaq Ahmad; Muhammad Babar Rasheed. 2021. "A Joint Optimization Model for Energy and Reserve Capacity Scheduling With the Integration of Variable Energy Resources." IEEE Access 9, no. : 75252-75264.

Review
Published: 27 April 2021 in Energy Reports
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Renewable energy sources are commonly available on earth; thus, both research and practical applications have drawn significant interest. In the large-scale renewable energy system, power quality in the grid, particularly harmonics and flickers, has a massive influence on the grid system. Recent years have seen enormous use of magnetically controllable reactors (MCRs) to solve these power quality problems. MCR can provide reactive power and voltage regulation in ultra and high voltage power grid, suppress power frequency and overvoltage operation, eradicate generator self-excitation, dynamically adjust power charging in a transmission line, suppress secondary arc current, damping system resonance, and so on, which can meet the different needs of the modern system. Considering MCR’s development status, this paper provides a detailed theoretical analysis of MCR and its configurations. Moreover, voltage and reactive power control mechanisms and other associated economic and technical factors and relevant application selection are explained in detail. It aims to give the researchers and application engineers dealing with power quality issues a broad perspective on MCR technology’s status. Finally, the MCR issues and future directions for research are discussed. A list of more than 280 research publications on the subject is also linked for a quick reference.

ACS Style

Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Adeel Saleem; Ahmad H. Milyani. A comprehensive review on magnetically controllable reactor: Modelling, applications and future prospects. Energy Reports 2021, 7, 2354 -2378.

AMA Style

Kashif Mehmood, Khalid Mehmood Cheema, Muhammad Faizan Tahir, Adeel Saleem, Ahmad H. Milyani. A comprehensive review on magnetically controllable reactor: Modelling, applications and future prospects. Energy Reports. 2021; 7 ():2354-2378.

Chicago/Turabian Style

Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Adeel Saleem; Ahmad H. Milyani. 2021. "A comprehensive review on magnetically controllable reactor: Modelling, applications and future prospects." Energy Reports 7, no. : 2354-2378.

Journal article
Published: 17 April 2021 in Sensors
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Despite eminent progress in recent years, various challenges associated with object tracking algorithms such as scale variations, partial or full occlusions, background clutters, illumination variations are still required to be resolved with improved estimation for real-time applications. This paper proposes a robust and fast algorithm for object tracking based on spatio-temporal context (STC). A pyramid representation-based scale correlation filter is incorporated to overcome the STC’s inability on the rapid change of scale of target. It learns appearance induced by variations in the target scale sampled at a different set of scales. During occlusion, most correlation filter trackers start drifting due to the wrong update of samples. To prevent the target model from drift, an occlusion detection and handling mechanism are incorporated. Occlusion is detected from the peak correlation score of the response map. It continuously predicts target location during occlusion and passes it to the STC tracking model. After the successful detection of occlusion, an extended Kalman filter is used for occlusion handling. This decreases the chance of tracking failure as the Kalman filter continuously updates itself and the tracking model. Further improvement to the model is provided by fusion with average peak to correlation energy (APCE) criteria, which automatically update the target model to deal with environmental changes. Extensive calculations on the benchmark datasets indicate the efficacy of the proposed tracking method with state of the art in terms of performance analysis.

ACS Style

Khizer Mehmood; Abdul Jalil; Ahmad Ali; Baber Khan; Maria Murad; Khalid Cheema; Ahmad Milyani. Spatio-Temporal Context, Correlation Filter and Measurement Estimation Collaboration Based Visual Object Tracking. Sensors 2021, 21, 2841 .

AMA Style

Khizer Mehmood, Abdul Jalil, Ahmad Ali, Baber Khan, Maria Murad, Khalid Cheema, Ahmad Milyani. Spatio-Temporal Context, Correlation Filter and Measurement Estimation Collaboration Based Visual Object Tracking. Sensors. 2021; 21 (8):2841.

Chicago/Turabian Style

Khizer Mehmood; Abdul Jalil; Ahmad Ali; Baber Khan; Maria Murad; Khalid Cheema; Ahmad Milyani. 2021. "Spatio-Temporal Context, Correlation Filter and Measurement Estimation Collaboration Based Visual Object Tracking." Sensors 21, no. 8: 2841.

Journal article
Published: 12 January 2021 in Energy Reports
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A hybrid resonant three-level converter comprised of dual transformers is proposed in this paper, which is suitable for the application of distributed photovoltaic power accessing the medium voltage dc distribution network. The proposed converter can be obtained by adding a control circuit into the traditional neutral point clamped (NPC) three-level (TL) circuit, achieving the basic TL circuit operating with a fixed duty cycle. Pulse width modulation (PWM) is adopted for the control circuit to realize zero current switchings for the basic TL circuit, which delivers most of the power, under full load range. As a result, the switching loss of the converter can be significantly reduced. The influences of the turn ratio of the second transformer and resonant capacitance on the switch current, the peak value of resonant voltage, and the value of the resonant inductance value are discussed in detail, and the parameters design principles are put forward. Finally, a prototype is built to verify the performance of the proposed converter.

ACS Style

Syed Waqar Azeem; Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Ahmed M. El-Sherbeeny. Dual-transformer-based hybrid resonant three-level ZCS converter. Energy Reports 2021, 7, 421 -429.

AMA Style

Syed Waqar Azeem, Kashif Mehmood, Khalid Mehmood Cheema, Muhammad Faizan Tahir, Ahmed M. El-Sherbeeny. Dual-transformer-based hybrid resonant three-level ZCS converter. Energy Reports. 2021; 7 ():421-429.

Chicago/Turabian Style

Syed Waqar Azeem; Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Ahmed M. El-Sherbeeny. 2021. "Dual-transformer-based hybrid resonant three-level ZCS converter." Energy Reports 7, no. : 421-429.

Journal article
Published: 19 December 2020 in Energy Reports
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This research utilizes a hybrid technology through resonant line-level control phase-shifted full-bridge (HR-LLC-PSFB) dc–dc converter. In this research, a line level control (LLC) auxiliary circuit is used to achieve zero-current soft-switching turned-off operation of a controlled switch. The zero-voltage soft-switching turned-on operation is achieved by using the transformers’ magnetic branch energy and the energy reflected by the output filter inductor. The effective turn’s ratio of the isolating transformers is used to reduce the inverter circuit’s voltage stresses. The effect of voltage overshoots and freewheeling circulating current in rectifying branches is improved by implementing an energy recovery circuit with an output filter. A closed loop coordination proportional integral derivative (PID) controller is proposed to generate the pulse width modulation (PWM) control signal to transmit smooth power by controlling output voltage and current values. The droop constant current charging (CCC) and reduced constant current charging (RCCC) technique is proposed for the charging process. Simulations performed in MATLAB and results substantiate the proposed work superiority in comparison to other topologies.

ACS Style

Tehzeeb-Ul Hassan; Khalid Mehmood Cheema; Kashif Mehmood; Muhammad Faizan Tahir; Ahmad H. Milyani; Muhammad Akhtar. Optimal control of high-power density hybrid electric vehicle charger. Energy Reports 2020, 7, 194 -207.

AMA Style

Tehzeeb-Ul Hassan, Khalid Mehmood Cheema, Kashif Mehmood, Muhammad Faizan Tahir, Ahmad H. Milyani, Muhammad Akhtar. Optimal control of high-power density hybrid electric vehicle charger. Energy Reports. 2020; 7 ():194-207.

Chicago/Turabian Style

Tehzeeb-Ul Hassan; Khalid Mehmood Cheema; Kashif Mehmood; Muhammad Faizan Tahir; Ahmad H. Milyani; Muhammad Akhtar. 2020. "Optimal control of high-power density hybrid electric vehicle charger." Energy Reports 7, no. : 194-207.

Journal article
Published: 15 December 2020 in Journal of Energy Storage
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This work reports the application of ensemble artificial neural networks, a machine learning technique, in the solution of short term optimal power generation on the IEEE 30-bus test system. The study, carried out using MATLAB, is being reported. The motive for using ensemble artificial neural networks has been to take advantage of multiple parallel processors computing rather than the traditional serial computation. The Bootstraps are obtained through small bags in the Bagging algorithm and are combined by averaging. Employing ensemble neural networks reduces bias and variance in machine learning so that the overall error is reduced, and hence better prediction can be achieved. The results obtained from the proposed algorithm are compared with those from the other heuristic and conventional techniques to validate the effectiveness of the proposed methodology.

ACS Style

Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Abdul Rehman Tariq; Ahmad H. Milyani; Rajvikram Madurai Elavarasan; Shaheer Shaheen; Kannadasan Raju. Short term power dispatch using neural network based ensemble classifier. Journal of Energy Storage 2020, 33, 102101 .

AMA Style

Kashif Mehmood, Khalid Mehmood Cheema, Muhammad Faizan Tahir, Abdul Rehman Tariq, Ahmad H. Milyani, Rajvikram Madurai Elavarasan, Shaheer Shaheen, Kannadasan Raju. Short term power dispatch using neural network based ensemble classifier. Journal of Energy Storage. 2020; 33 ():102101.

Chicago/Turabian Style

Kashif Mehmood; Khalid Mehmood Cheema; Muhammad Faizan Tahir; Abdul Rehman Tariq; Ahmad H. Milyani; Rajvikram Madurai Elavarasan; Shaheer Shaheen; Kannadasan Raju. 2020. "Short term power dispatch using neural network based ensemble classifier." Journal of Energy Storage 33, no. : 102101.

Journal article
Published: 25 August 2020 in Energy Reports
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This paper presents the solution of optimal power flow using the Hamiltonian optimization technique. The proposed Hamiltonian technique is employed for power loss optimization which is very critical issue in optimal power flow. Power loss across transmission lines is a major concern in the recent electrical power crisis. Therefore, the scope of this work is to minimize the power loss effectively and to evaluate the performance and analyze the effectiveness of the Hamiltonian optimization technique. The control variables chosen for this work are voltage magnitude of generator buses, the reactive power generation from the buses and static VAR compensators, voltage angle of the slack bus, and active, reactive power of load buses. The minimum power loss value by using HOP for IEEE 30-bus and 57-bus systems are 3.38 MW and 10.354 MW, respectively. The basic reason for such improved result is the use of Set to Middle Approach (SMA) instead of Set to Limit Approach (SLA) for tackling inequality constraints on control variables. MATLAB is used to simulated the IEEE 30-bus and IEEE 57-bus system to test and analyze the effectiveness of the proposed technique.

ACS Style

Hafiz Tehzeeb-Ul-Hassan; Muhammad Faizan Tahir; Kashif Mehmood; Khalid Mehmood Cheema; Ahmad H. Milyani; Qasim Rasool. Optimization of power flow by using Hamiltonian technique. Energy Reports 2020, 6, 2267 -2275.

AMA Style

Hafiz Tehzeeb-Ul-Hassan, Muhammad Faizan Tahir, Kashif Mehmood, Khalid Mehmood Cheema, Ahmad H. Milyani, Qasim Rasool. Optimization of power flow by using Hamiltonian technique. Energy Reports. 2020; 6 ():2267-2275.

Chicago/Turabian Style

Hafiz Tehzeeb-Ul-Hassan; Muhammad Faizan Tahir; Kashif Mehmood; Khalid Mehmood Cheema; Ahmad H. Milyani; Qasim Rasool. 2020. "Optimization of power flow by using Hamiltonian technique." Energy Reports 6, no. : 2267-2275.