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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Jamal Fadhil Tawfeq
Al-Farahidi University
Computer Science & IT Electrical & Electronics Engineering

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Evaluation of wind-solar hybrid power generation system based on Monte Carlo method Yitong Niu; Ahmed Mohammed Merza; Suhad Ibraheem Kadhem; Jamal Fadhil Tawfeq; Poh Soon JosephNg; Hassan Muwafaq Gheni
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4401-4411

Abstract

The application of wind-photovoltaic complementary power generation systems is becoming more and more widespread, but its intermittent and fluctuating characteristics may have a certain impact on the system's reliability. To better evaluate the reliability of stand-alone power generation systems with wind and photovoltaic generators, a reliability assessment model for stand-alone power generation systems with wind and photovoltaic generators was developed based on the analysis of the impact of wind and photovoltaic generator outages and derating on reliability. A sequential Monte Carlo method was used to evaluate the impact of the wind turbine, photovoltaic (PV) turbine, wind/photovoltaic complementary system, the randomness of wind turbine/photovoltaic outage status and penetration rate on the reliability of Independent photovoltaic power generation system (IPPS) under the reliability test system (RBTS). The results show that this reliability assessment method can provide some reference for planning the actual IPP system with wind and complementary solar systems.
A powerful heuristic method for generating efficient database systems Haider Hadi Abbas; Poh Soon JosephNg; Ahmed Lateef Khalaf; Jamal Fadhil Tawfeq; Ahmed Dheyaa Radhi
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5070

Abstract

Heuristic functions are an integral part of MapReduce software, both in Apache Hadoop and Spark. If the heuristic function performs badly, the load in the reduce part will not be balanced and access times spike. To investigate this problem closer, we run an optimal database program with numerous different heuristic functions on database. We will leverage the Amazon elastic MapReduce framework. The paper investigates on general purpose, implementation, and evaluation of heuristic algorithm for generating optimal database system, checksum, and special heuristic functions. With the analysis, we present the corresponding runtime results. For the coding part, the records counting part is hasty and can only work for local Hadoop part, it can be debugged and optimized for general purpose implement on Hadoop and Spark and turn into an effective performance monitor tool. As mentioned before, there are strange issue, also the performance of BLAKE2s is unexpectedly slow in that it’s widely accepted the performance of BLAKE2s is much better than MD5 and SHA256, we would like to figure out why the common-sense performance of heuristics is deferent from what we got in distributed frameworks.
A novel data offloading scheme for QoS optimization in 5G based internet of medical things Saadya Fahad Jabbar; Nuha Sami Mohsin; Jamal Fadhil Tawfeq; Poh Soon JosephNg; Ahmed Lateef Khalaf
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5069

Abstract

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of data transmission at the original targeted location. Initially, healthcare data was collected. Preprocessing is achieved by the normalization method. An EEEF data offloading scheme is proposed. A fruit fly optimization (FFO) technique is utilized. The performance metrics such as energy consumption, delay, resource utilization, scalability, and packet loss are analyzed and compared with existing techniques. The future scope will make use of a revolutionary optimization approach for IoMT.
Co-Authors Ahmed Dheyaa Radhi Ahmed Lateef Khalaf Ahmed Mohammed Merza Haider Hadi Abbas Hassan Muwafaq Gheni Nuha Sami Mohsin Poh Soon JosephNg Saadya Fahad Jabbar Suhad Ibraheem Kadhem Yitong Niu