Saving utility costs optimization in generator operation planning based on scalable alternatives of probabilistic demand-side management
Journal Article

The electric power system network has become more self-sufficient and less dependent on fossil fuel-based units due to the increasing integration of renewable energy resources. It is crucial to have an efficient method or technology for managing the system’s economics, security, reliability,  environmental damage, and the un- certainties that come with fluctuating loads. In this context, this paper utilizes a framework based on probabi- listic simulation of a demand-side management approach and computational intelligence to calculate the optimal value of saving utility cost (SUC). Unlike traditional methods that dispatch peak-clipped resource blocks sequentially, a modified artificial bee colony (MABC) algorithm is employed. The SUC is then reported through a sequential valley-filling procedure. Consequently, the SUC is derived from the overall profitability of the gen- eration system and includes savings in energy costs, capacity costs, and expected cycle costs. Further investi- gation to obtain the optimal value of SUC was conducted by comparing the SUC determined directly and indirectly, explicitly referring to the peak clipping energy of thermal units (PCETU). The comparisons utilized the MABC algorithm and a standard artificial bee colony, and the results were verified using the modified IEEE RTS- 79 with varying peak load demands. The findings illustrate that the proposed method demonstrated robustness in determining the global optimal values of SUC increments, achieving increases of 7.26 % for 2850 MW and 5 % for 3000 MW, compared to indirect estimation based on PCETU. Moreover, SUC increments of 18.13 % and 25.47 % were also achieved over the conventional method.


Daw Saleh Sasi Mohammed, Muhammad Murtadha Othman, Olatunji Obalowu Mohammed, Masoud Ahmadipour, Mohammad Lutfi Othman, (03-2025), Sustainable Energy Technologies and Assessments: Elsevier, 75 (32767), 1-11

Systematic Approach for Fault Analysis and Power System Protection based on Wavelet Applications
Journal Article

Abstract—In the current landscape of power system utilities, ensuring stability and reliability is more crucial than ever, highlighting the  importance of your expertise and contributions. Protecting transmission lines is essential for  maintaining these key attributes in power delivery. This study introduces an innovative approach  using wavelet transform (WT) to an effective wavelet transform (WT) approach. Detect and classify  transmission line faults. The unique capabilities of wavelets make them ideal for addressing  transient disturbances in power systems. Our algorithm utilizes the discrete wavelet transform  (DWT) to extract the three-phase current signal in the case of a single line-to-ground fault.  Carefully selecting the Daubechies4 mother wavelet significantly enhances our ability to gather  helpful information about fault conditions. The classification process is based on careful  calculation. The absolute sum of the signal details at level 2 over a single cycle window provides  precise insights. We employed Power System Computer-Aided Design / Electromagnetic Transients with  DC (PSCAD/EMTDC) to generate the three-phase current signal in a tested 230 kv transmission system.  The simulation results robustly demonstrate that our proposed algorithm excels in detecting and  classifying both faulted and healthy phases, ensuring a future of heightened reliability in power  systems.


Abdulhamid A. Abohagar, Daw Saleh Sasi Mohammed, (12-2024), Libyan Journal of Engineering Science and Technology: جامعة النجم الساطع, 4 (3), 1-5

Design of Intelligent Chatbot for Stress Management
Conference paper

ABSTRACT: This paper focuses on using natural language processing (NLP) in chatbots to manage stress in war-affected countries. A Java-based chatbot was designed to alleviate stress using two algorithms: TextRank and Stanford_CoreNLP. The problem was solved by integrating different languages using a plugin. The chatbot was tested with fifteen people and received positive feedback. Modifications were made based on user feedback, with journaling being a winner. However, the chatbot faced limitations like a lack of Arabic language support and voice chat features.

Adel Ali Faraj Eluheshi, Amira Shlebik, (12-2024), Libya: The International Journal of Engineering & Information Technology (IJEIT), 17-27

Compliance of Libyan Government Websites with Web Content Accessibility Guidelines Standards
Journal Article

This study provides a comprehensive evaluation of the compliance of key Libyan government websites with the Web Content Accessibility Guidelines (WCAG) 2.2, the latest international standard for digital accessibility published in October 2023. The assessment focuses on the nine new success criteria introduced in WCAG 2.2, which aim to improve accessibility for users with low vision, cognitive, and motor disabilities. By conducting thorough automated and manual testing, this research identifies the specific strengths and weaknesses of the evaluated websites in meeting WCAG 2.2 requirements at the A, AA, and AAA levels. The findings reveal significant areas for improvement across the government's online presence and provide actionable recommendations for Libyan institutions to enhance their digital accessibility efforts and create a more inclusive online environment for all citizens. KEYWORDS: digital accessibility, web accessibility, compliance, Libyan government websites

Musa Kh A Faneer, (10-2024), المجلة الأكاديمية للعلوم و التقنية الاكاديمية الليبية للدراسات العليا: Libyan Academy, 4 (1), 189-192

Medical Expert Systems in Ambulance Care
Journal Article

Daily incidents significantly impact the workflow of ambulance and healthcare personnel, whose critical role involves providing immediate medical treatment and facilitating transportation to hospitals. This study presents the design of a medical expert system aimed at enhancing first-aid response in ambulances and educating users on fundamental first-aid principles. The proposed system integrates a comprehensive knowledge base that catalogs disease symptoms and corresponding treatments, functioning similarly to a medical professional's guidance. While the system relies on pre-programmed symptoms, it allows for the continuous addition of new symptoms and diseases, ensuring adaptability in emergencies. This expert system is particularly beneficial for novice healthcare providers, equipping them with reliable diagnostic support and improving patient outcomes during medical emergencies.

Musa Kh A Faneer, Omer Saleh Mahmod Jomah, (10-2024), African Journal of Advanced Pure and Applied Sciences: African Journal of Advanced Pure and Applied Sciences (AJAPAS), 4 (3), 210-217

Implementing Digital Medical Prescriptions in Libya: A Strategy to Minimize Medical Errors in Hospitals and Pharmacies
Journal Article

The Libyan healthcare system faces significant challenges in medication management, with high rates of medication errors posing serious risks to patient safety. Digital transformation, particularly through the adoption of electronic medical prescriptions, offers a promising solution to enhance prescription accuracy, improve patient outcomes, and streamline healthcare processes. This technical paper examines the implementation of digital medical prescriptions in Libya, focusing on the role of health informatics, the validation of prescriptions, and the potential barriers to success. The paper also highlights efforts in Arab and African countries similar to Libya, showcasing best practices and lessons learned.


Keywords: Digital prescriptions, Libya healthcare system, Medication errors, Patient safety, Digital transformation, Prescription practices, Prescription accuracy, Handwritten prescriptions, Prescription software, electronic health record systems (EHRS).


Musa Kh A Faneer, (08-2024), مجلة الأكاديمية للعلوم الأساسية والتطبيقية الاكاديمية الليبية للدراسات العليا: Libyan Academy, 2 (6), 122-132

Identifying interaction boundary of inverter-based generation in assessing system strength of power grids using relative electrical distance concept
Journal Article

The increasing use of inverter-based generation (IBG) in power grids raises concern about system  strength. This is partly due to the inherent interactions among multiple IBGs in close proximity to  one another. This paper proposes an approach to identifying the existential boundary of interaction  in a network using the relative electrical distance (RED) concept. The mathematical formulation of  the RED concept to address the interaction problem among the IBGs involved utilising the power  system network’s admittance matrix to capture its structural characteristics. An interaction matrix  derived from the RED values of all IBG pairs was then developed to identify the interacting IBG  groups. The proposed approach was demonstrated using the IEEE 39-bus system and a practical 72-bus  Nigerian power grid. Results showed that RED values effectively group interacting IBGs, with values  closer to 0 signifying higher interaction levels, values closer to 1 indicating lower interaction,  and a value of 1 denoting no interaction. Time-domain simulations confirmed the accuracy of the  approach, demon- strating that the effect of control interaction propagates proportionally to  neighbouring IBGs based on RED values. However, fault currents can influence the impact of control  interactions. This approach, which requires less computational effort, provides a quick  identification tool for potential areas of concern based on the degree of interaction, enhancing  the reliability of power grids with high IBG penetration.


Shereefdeen Oladapo Sanni, Olatunji Obalowu Mohammed, Ayodele Isqeel Abdullateef, Daw Saleh Sasi Mohammed, Joseph Yakubu Oricha, (08-2024), Renewable Energy Focus: Elsevier, 51 (32767), 1-12

Simulating Photovoltaic Emulator Systems for Renewable Energy Analysis
Conference paper

The article discusses exploring the Photovoltaic (PV) emulator for simulating photovoltaic systems for Renewable Energy Analysis (REA) focuses on creating and applying a PV emulator to simulate photovoltaic systems and concludes by emphasizing the value of precise simulation tools in comprehending and enhancing photovoltaic system performance. The first portion of the article emphasizes how renewable energy sources especially solar energy are becoming more and more important in tackling the world's energy problems. As a result, the pv output along with the voltage and current have been presented

Omer.S. M. Jomah, (07-2024), 2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA): IEEE, 4-14

Assessing Random Power Flow for Vehicle-to-Grid Operation Based on Monte Carlo Simulation
Conference paper

This paper employs Monte Carlo Simulation (MCS) to assess how randomly power flow is distributed in Vehicle-to-Grid (V2G) operations. V2G technology facilitates a bidirectional flow of electricity by allowing Electric Vehicles (EVs) to feed excess power back into the grid in addition to drawing power from it. The researchers used Monte Carlo simulation as a computational technique that involves generating random samples to analyze the behaviour of a system, to assess the impact of random variations in power flow on V2G operations. They considered various factors such as EV charging and discharging patterns, grid conditions, and user behaviour to create a realistic simulation environment. The main objective function in this study wants to achieve is to reduce the dependency on the grid and develop a stochastic framework for the efficient management of microgrids with the presence of EVs. reduce cost. As a result, the analysis of the MCS shows the performance of the bidirectional operation, and the output power of the integrated sources is obtained.

Omer.S. M. Jomah, (07-2024), 2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA): IEEE, 11-24

Alzheimer’s Disease Based on Machine Learning Algorithms and Mind Maps: Review
Journal Article

Alzheimer's disease (AD) is a complex neurological illness that has several deep reasons. According to recent research, the use of machine learning techniques (ML) on MRI images can assist in identify the brain regions and the connections between them that are implicated in dementia. The study aims to review literature from 2017 to 2023 on the use of machine learning algorithms to identifying and categorize AD. The precision of each machine learning model is assessed, and mind map models are employed to illustrate the study and compare the outcomes.

Adel Ali Faraj Eluheshi, Howayda Abedallah Elmarzaki, (06-2024), Libya: مجلة ليبيا للعلوم التطبيقية والتقنية, 12 (1), 1-11