HAMDAN DANIYAL
@umpsa.edu.my
FAKULTI TEKNOLOGI KEJURUTERAAN ELEKTRIK DAN ELEKTRONIK
UNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ibrahim Haruna Shanono, Nor Rul Hasma Abdullah, Hamdan Daniyal, and Aisha Muhammad
Springer Science and Business Media LLC
Ria Kunwar, Bhupender Pal, Izan Izwan Misnon, Hamdan Daniyal, Fatemeh Zabihi, Shengyuan Yang, Zděnek Sofer, Chun-Chen Yang, and Rajan Jose
Elsevier BV
Aisyah Ibrahim, Tuty Asmawaty Abdul Kadir, Roderick H. MacDonald, and Hamdan Daniyal
IEEE
This paper presents the manual calibration effort for the System Dynamics (SD) COVID-19 model for Malaysia. This study aims to develop a COVID-19 SD model based on the COVID-19 scenario in Malaysia. The SD model consisted of nine compartments and was adapted based on a standard disease SEIR model using Vensim software. While the development of the model is still ongoing, an initial validation was carried out between ‘Actively Infected’ and the case data gathered from the Malaysia Ministry of Health's official COVID-19 websites. During this period, the parameters were manually adjusted by hand to align the model's output with the actual data. The expected outcome was not easy to achieve, but the result was acceptable. It is important to note that the lack of such strategies may compromise the model's validity due to uncertainty. This paper also discusses the challenges posed by hand calibration, the lessons learned during this work, and the potential future implications of this work.
Suliana Ab-Ghani, Hamdan Daniyal, Abu Zaharin Ahmad, Norazila Jaalam, Norhafidzah Mohd Saad, Nur Huda Ramlan, and Norhazilina Bahari
American Institute of Mathematical Sciences (AIMS)
<abstract> <p>Electric vehicles (EVs) are an emerging technology that contribute to reducing air pollution. This paper presents the development of a 200 kW DC charger for the vehicle-to-grid (V2G) application. The bidirectional dual active bridge (DAB) converter was the preferred fit for a high-power DC-DC conversion due its attractive features such as high power density and bidirectional power flow. A particle swarm optimization (PSO) algorithm was used to online auto-tune the optimal proportional gain (<italic>K<sub>P</sub></italic>) and integral gain (<italic>K<sub>I</sub></italic>) value with minimized error voltage. Then, knowing that the controller with fixed gains have limitation in its response during dynamic change, the PSO was improved to allow re-tuning and update the new <italic>K<sub>P</sub></italic> and <italic>K<sub>I</sub></italic> upon step changes or disturbances through a time-variant approach. The proposed controller, online auto-tuned PI using PSO with re-tuning (OPSO-PI-RT) and one-time (OPSO-PI-OT) execution were compared under desired output voltage step changes and load step changes in terms of steady-state error and dynamic performance. The OPSO-PI-RT method was a superior controller with 98.16% accuracy and faster controller with 85.28 s<sup>-1</sup> average speed compared to OPSO-PI-OT using controller hardware-in-the-loop (CHIL) approach.</p> </abstract>
Mohd Herwan Sulaiman, Zuriani Mustaffa, Mohd Mawardi Saari, Hamdan Daniyal, and Seyedali Mirjalili
Springer Science and Business Media LLC
Rashidah Funke Olanrewaju, Burhan Ul Islam Khan, Khang Wen Goh, Aisha Hassan Abdalla Hashim, Khairul Azami Bin Sidek, Zuhani Ismail Khan, and Hamdan Daniyal
MDPI AG
Sales enablement sensing-as-a-service (SESaaS) is an organisation’s future process management for any sales management operation. With an expanding base of dynamic customer demands and the adoption of multiple technological advancements, there is a high possibility that human-centric sales management will be transformed into a fully automated form aimed at increasing productivity and being able to cater to effectively a broader customer base. A review of the relevant literature demonstrates that machine learning is one of the most prevalent techniques in analytics for predicting sales behaviour. However, SESaaS includes many features beyond the sales component. Internet-of-Things (IoT) can additionally be used for networking and data analytics to enrich sales data. Therefore, the proposed scheme introduces a novel SESaaS model capable of balancing the sales team’s needs with those of the customers to maximise profits. The proposed model also presents a novel learning scheme in the IoT environment that aids in projecting the service quality score to the final customer, thereby positively influencing the customer to pay a service fee for a superior and desired quality of experience. Unlike any existing sales management scheme, the proposed scheme offers a novel research methodology for improving sales enablement practices, emphasising service scalability, and forecasting company profit. In contrast to any existing system for sales management, the proposed scheme provides greater accuracy, higher service quality, and faster response time in its predictive strategy for projecting the cost of the adoption of SESaaS, which is not reported in any existing studies. In an extensive testing environment, it is determined that the proposed scheme achieves accuracy and service quality of approximately 98.75% and 92.91%, respectively. In addition, the proposed SESaaS model has a significantly faster response time of 1.256 s. These quantifiable outcomes were validated after being compared with commonly adopted learning programs.
Rashidah Funke Olanrewaju, Burhan Ul Islam Khan, Aisha Hassan Abdalla Hashim, Khairul Azami Sidek, Zuhani Ismail Khan, and Hamdan Daniyal
Akademia Baru Publishing
With the improvements in machine-to-machine (M2M) communication, ubiquitous computing, and wireless sensor networks, the Internet of Things (IoT) has become a notion that is constantly rising in importance. Using uniquely addressable IDs, the Internet of Things links diverse physical items and allows them to communicate with one another through the Internet. A general overview of the IoT in the context of the architecture and associated technologies is provided in this article. On the other hand, the Internet of Things does not follow a standardised architecture model. This is accomplished by describing widely recognised architectural concepts that are subsequently refined with the associated technology in various tiers. Also included are some solutions that have been developed and future directions for addressing the obstacles faced by the IoT paradigm. Finally, the article discusses several Internet of Things applications to demonstrate the viability of the IoT idea in real-world settings.
S. Ab-Ghani, H. Daniyal, N. Jaalam, N. M. Saad, and N. H. Ramlan
Institution of Engineering and Technology
Ibrahim Haruna Shanono, Nor Rul Hasma Abdullah, Hamdan Daniyal, and Aisha Muhammad
IEEE
This research article proposed a new modified single-phase multi-level inverter topology with an optimal switching control strategy to reduce the inverter output harmonic distortion. The topology is configured to operate in asymmetric mode to generate eleven levels of output voltage steps. Additionally, a selective harmonic elimination technique has been deployed to minimize the switching loss and EMI. The Moth Flame Optimization (MFO) algorithm is deployed to compute the optimal switching angles. The proposed MLI topology is simulated in PSIM software using the optimized switching angles. The inverter performance parameters such as the total harmonic distortion (THD), harmonic amplitudes, switching, and conduction losses, were also analyzed and reported. The topology total harmonic distortion is 2.4%, hence satisfying the IEEE 519 standard.
Suliana Ab-Ghani, Hamdan Daniyal, Norazila Jaalam, Nur Huda Ramlan, and Norhafidzah Mohd Saad
IEEE
The proliferation of clean energy and environmentally friendly transportation has contributed to the development of electric vehicles (EVs) including the EV DC charger system. A dual active bridge (DAB) is a DC-DC converter that has the required features for an EV DC charger. A proportional-integral (PI) controller is a common method in power electronics applications, including DAB. However, the manual tuning of PI parameters using Ziegler-Nichols (ZN) needs a lengthy time and the tuning values are practical and well-functioning at the tuning point only. Moreover, the fixed gains in offline tuning cannot fully control the system output as needed and do not guarantee the robustness of the system. This paper proposes a time-variant online auto-tuned PI controller using a particle swarm optimization (PSO) algorithm for the 200 kW DAB system. The DAB performance with the proposed controller is evaluated in terms of steady-state error, eSS and dynamic performance under various reference voltages at different loads and load step changes. Comparative analysis between the proposed method and manual tuning performance are presented. A hardware-in-the-loop (HIL) experimental circuit is built to validate the simulation results. The DAB with the proposed method produces 64% higher accuracy and 40% faster response compared to manual tuning. tuning.
Meng Chung Tiong, Hamdan Daniyal, Mohd Herwan Sulaiman, and Mohd Shafie Bakar
Springer Singapore
Suliana Ab-Ghani, Hamdan Daniyal, Nur Huda Ramlan, Norhafidzah Mohd Saad, and Meng Chung Tiong
Springer Singapore
Aisyah Ibrahim, Tuty Asmawaty Abdul Kadir, Hamdan Daniyal, and Adzhar Kamaludin
Springer International Publishing
Aisyah Ibrahim, Tuty Asmawaty Abdul Kadir, Hamdan Daniyal, and Adzhar Kamaludin
IEEE
The world is facing a massive challenge as the COVID-19 outbreak strikes across the globe. Many efforts have been made to detect, control and contain the coronavirus proactively and aggressively before a further catastrophe occurs. Indeed, ending the global COVID-19 pandemic is not a simple task. It requires adequate planning and implementation of sustainable strategies and interventions to control COVID-19 from keep spreading globally. One way to address this issue is using System Dynamics (SD). With this aim in mind, this paper presents an initial COVID-19 modelling work in the formulation stage of SD methodology. A literature review was carried out on published and unpublished papers to understand the essential outbreak model design structure. Within this process, a total of 15 COVID-19 models in SD were gathered and analysed. As the outcome, this paper highlights the components of the conceptual representation model for the COVID-19 outbreak, which later can serve as the core basis for modelling complex COVID19 outbreak dynamics and interventions for future development. As an implication, a comprehensive model can be developed to support decision making.
Aisyah Ibrahim, Hamdan Daniyal, Tuty Asmawaty, and Adzhar Kamaludin
The Science and Information Organization
System Dynamics (SD) modelling is a highly complex process. Although the SD methodology has been discussed extensively in most breakthroughs and present literature, discussions on data collection methods for SD modelling are not explained in details in most studies. To date, comprehensive descriptions of knowledge extraction for SD modelling is still scarce in the literature either. In an attempt to fill in the gap, three primary groups of data sources proposed by Forrester: (1) mental database, (2) written database and (3) numerical database, were reviewed, including the potential data collections methods for each database by taking into account the advancement of current computer and information technology. The contributions of this paper come in threefolds. First, this paper highlights the potential data sources that deserved to be acknowledged and reflected in the SD domain. Second, this paper provides insights into the appropriate mix and match of data collection methods for SD development. Third, this paper provides a practical synthesis of potential data sources and their suitability according to the SD modelling stage, which can serve as modelling practice guidelines.
Ibrahim Haruna Shanono, Nor Rul Hasma Abdullah, Hamdan Daniyal, and Aisha Muhammad
Springer Science and Business Media LLC
Suliana Ab-Ghani, Hamdan Daniyal, Nur Huda Ramlan, and Meng Chung Tiong
Springer Science and Business Media LLC
Muhammad Ikram Mohd Rashid, Ahmad Amir Solihin Mohd Apandi, Hamdan Daniyal, and Mohd Ashraf Ahmad
Springer Singapore
Mohd Herwan Sulaiman, Zuriani Mustaffa, Mohd Mawardi Saari, and Hamdan Daniyal
Elsevier BV
Abstract This paper presents a novel bio-inspired optimization algorithm namely the Barnacles Mating Optimizer (BMO) algorithm to solve optimization problems. The proposed algorithm mimics the mating behaviour of barnacles in nature for solving optimization problems. The BMO is first benchmarked on a set of 23 mathematical functions to test the characteristics of BMO in finding the optimal solutions. It is then applied to optimal reactive power dispatch (ORPD) problem to verify the reliability and efficiency of BMO. Extensive comparative studies with other algorithms are conducted and from the simulation results, it is observed that BMO generally provides better results and exhibits huge potential of BMO in solving real optimization problems.
Ibrahim Haruna Shanono, Nor Rul Hasma Abdullah, Hamdan Daniyal, and Aisha Muhammad
Springer Science and Business Media LLC
Christopher Ngadi Anak Julius and
The World Academy of Research in Science and Engineering
The use of renewable energy sources is highly demand in electricity market nowadays. The incorporation of renewable energy sources with the utility grid has becoming a challenging task in power system as it arises several control issues such as grid stability, power quality control, loads sharing and others. This paper presents current control methods namely Hysteresis controller and Proportional-Integral controller used to interface of single-phase grid connected inverter with nonlinear load. The impact of nonlinear load on grid current is analysed by measuring the performance of total current harmonics distortion (THDi) level in MATLAB Simulink software environment.
Mohd Herwan Sulaiman, Zuriani Mustaffa, Mohd Mawardi Saari, Hamdan Daniyal, Ismail Musirin, and Mohd Razali Daud
IEEE
A new evolutionary algorithm called Barnacles Mating Optimizer (BMO) to solve optimization problems is presented in this paper. BMO is inspired from the behavior of barnacle’ mating in nature. They are known as micro-organisms that existed since Jurassic times and classified as hermaphroditic micro-organisms. They have a unique feature which is they own long penises that can be said as the longest among microorganisms, relatively to size of their body. To show the effectiveness of proposed BMO in solving optimization problems, a set of 23 mathematical functions are used to test the characteristic of BMO in finding the optimal solutions especially in unimodal, multimodal and composite test functions. Comparisons with other evolutionary and swarm algorithms also will be presented.
Muhammad Ikram bin Mohd Rashid, Hamdan Daniyal, and Mohd Ashraf Ahmad
Springer International Publishing