Dr. Hasan Abdel Rahim A. Zidan holds a Ph.D. in Control Engineering from Japan (2001). He began his academic career at AAU in Jordan, where he served as the Head of the Computer Engineering Department until 2005. Since joining Ajman University, Dr. Zidan has been an integral faculty member, contributing to various committees at the department, college, and university levels. His roles have included Student Advisory Coordinator, Curriculum Committee Member, Chair of the Curriculum and Study Plan Sub-Committees, and active participation in strategic initiatives such as the College Effectiveness Committee and the AU Interactive Online Study Plans Committee. Dr. Zidan has also served as a jury member and assessor for student research and scientific competitions both locally and internationally, helping to elevate Ajman University's presence on the global stage. His leadership extends to key roles such as Chair of the Procurement Committee, Investigation Committee, and Energy Optimization Subcommittee, underscoring his commitment to academic excellence and institutional development.
In recent years, modular multilevel converters (MMC) have become one of the most popular multilevel converter topologies. Despite its growing popularity, MMC is still less widespread in variable speed drives (VSDs) applications. The reason for this is that the voltage ripple of the MMC submodules (SM) increases during the low-speed constant torque operation. In this paper, carrier phase shift-pulse width modulation (CPS-PWM) is modified to reduce the average voltage of SM and thus accommodate more ripples without exceeding the maximum SM voltage. The proposed method does not involve the injection of circulating current components, thereby resulting in less power loss. In addition to that, the necessity for increasing the SM capacitor rating during low-speed operation is not required. Extensive simulation has been conducted under various speed commands to validate the effectiveness of this method.
Water canal networks that are widely used for irrigation are an equally good source of micropower generation to be fed to the nearby areas. A practical example of such a system is the micro-hydro generation at Renala Khurd Pakistan integrated with the national grid known as hydro–grid configuration. Apart from the rare Renala Khurd hydro generation example, solar photovoltaic generation integrated with a mainstream network, i.e., solar PV-Grid configuration, is widely used. The integrated operation of combinations of primary distributed generation sources has different operational attributes in terms of economics and reliability that are needed to be quantified before installation. So far, various combinations of primary distributed generation sources have been simulated and their accumulative impact on project economics and reliability have been reported. A detailed economic and reliability assessment of various configurations is needed for sustainable and cost-effective configuration selection. This study proposes a trigeneration combination of solar–hydro–grid with an optimal sizing scheme to reduce the solar system sizing and grid operational cost. A genetic algorithm based optimal sizing formulation is developed using fixed hydro and variable solar and grid systems with a number of pre-defined constraints. The hydro–grid, solar–grid, and grid–hydro–solar configurations are simulated in HOMER Pro software to analyze the economic impact, and to undertake reliability assessments under various configurations of the project. Finally, optimal values of the genetic algorithm are provided to the HOMER Pro software search space for simulating the grid–hydro–solar configuration. It was revealed that the net present cost (NPC) of hydro-to-grid configuration was 23% lower than the grid–hydro–solar configuration, whereas the NPC of grid–hydro–solar without optimal sizing was 40% lower than the solar–grid configuration, and the NPC of grid–solar–hydro with the genetic algorithm was 36% lower than the hydro–grid configuration, 50.90% lower than solar–grid–hydro without the genetic algorithm, and 17.1% lower than the grid–solar configuration, thus proving utilization of trigeneration sources integration to be a feasible solution for areas where canal hydropower is available.
Due to global environmental impacts, the electric vehicle (EV) adoption rate is increasing. However, unlike conventional petrol vehicles, EVs take a considerable time to charge. EVs on the road with different battery charging statuses and driving demographics may cause uncertain peak time arrivals at charging stations. Battery-swappable charging stations are a quick and easier way to replace uncharged batteries with charged ones. However, charging due to uncertain EV arrival causes higher charging profiles posing load to the grid, management of charged and discharged batteries, and peak time charging tariffs. These challenges hinder the wide operation of battery-swappable charging stations. Nevertheless, a pre-assessment of peak hours using EV demographics can reduce congestion. In recent literature surveys for battery-swappable charging stations, spot congestion has not been given much attention, which has a direct influence on the sizing and operation of battery-swappable charging stations. This research study is focused on estimating peak time events using a novel integrated techno-economic assessment framework. A fuzzy-based parametric assessment tool is developed that identifies the factors that influence higher congestion events. Based on the peak event assessment, grid, and solar PV-based generation is optimized using mixed integer linear programming. In the final step, an environment analysis of a swappable charging station is performed. Furthermore, the results achieved using the proposed framework for battery-swappable charging stations (BSCSs) were compared with fast-charging (FC) stations. FC can economically perform well if integrated with solar PV systems; however, the capital cost is 80% greater than the BSCSs designed under the proposed framework. The operational cost of BSCSs is 39% higher than FC stations as they use 29% higher grid units than FC stations due to night operations under congestion.
The twin rotor aerodynamic system (TRAS) reflects the dynamics of vertical take-off rotor systems. TRAS considers the coupling effect and gyroscopic disturbance torque as unwanted signals. For safe and reliable TRAS operation, proper control input is vital, along with fast fault indication. This paper addresses the output sensor fault detection problem in the linear model of TRAS subjected to -norm bounded disturbance. A robust design of an observer is formulated as H-/ optimization problem to maximize the sensitivity/robustness criterion. The approach minimizes the disturbance effect on the residual signal, which leads to successful fault detection. Furthermore, a linear quadratic regulator-based state feedback controller is proposed to meet the system's desired transient response requirement. The incorporation of an observer-based residual generator for fault detection along with the state-feedback controller differs the current work from the existing work. Successful fault detection in the output sensor of TRAS depicts the good performance of the proposed observer.
DC bus voltage control in DC islanded microgrids is essential for the power quality and reliability. There are various algorithms being used in the literature review to control the bus voltages of DC microgrids. However, most of the research works controlled the generation side that requires high performance devices such as super capacitors etc., On the other hand, battery storage systems are also being used to regulate the bus voltage. In this research work, a separate strategy was developed in which battery storage was implemented at the load side to maintain stability of DC bus voltage. The load management scheme is introduced in which during the voltage instability, the loads are cutoff from the main supply and local installed storage system feed the loads. A particle swarm optimization (PSO) technique was used to optimally decide for the load in watts to be operated. A DC microgrid hardware was designed to test the control algorithm. The loads are not connected to the main system until the power supply is stable again. The load management scheme not only reduces the cost of the system but also stabilizes the overall system with 60% charge available in the batteries using the proposed load management scheme. The results were achieved while performing experiments on developed DC Microgrid hardware.