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All Journal International Journal of Electrical and Computer Engineering International Journal of Advances in Applied Sciences Indonesian Journal of Electrical Engineering and Computer Science
Mashitah Mohd Hussain
Universiti Teknologi MARA
Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Short term forecasting of electrical consumption using a neural network: joint approximate diagonal eigenvalue Mashitah Mohd Hussain; Zuhaina Zakaria; Nofri Yenita Dahlan; Nur Iqtiyani Ilham; Zhafran Hussin; Noor Hasliza Abdul Rahman; Md Azwan Md Yasin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp56-66

Abstract

This article aims to estimate the load profiling of electricity that provides information on the electrical load demand. In achieving this research implemented the neural network algorithm of joint approximate diagonalisation of eigen-matrices (JADE) to describe the load profile pattern for each point. Nowadays, utility providers claim that natural sources are used to generate power by rising consumer demands for energy. However, occasionally utility workers need to know the demand at certain location, corresponding to maintenance issues or for any shutdown area involved. A distribution pattern based on the data can be predicted based on the incoming data profile without having detailed information of certain load bus, the concept of derivatives was relevant to forecast the types of distribution data. The model was constructed with load profile information based on three different locations, and the concept of derivative was recognized, including the type of incoming data. Historical data were captured from a selected location in Malaysia that was proposed to train the JADE algorithm from three different empirical distributions of consumers, recording every 15 minutes per day. The results were analyzed based on the error measurement and compared with the real specific load distribution feeder information of needed profiles.
Stability model integration for large scale solar photovoltaic system using Western electricity coordinating council model Mohammad Nayeim Fazumy Mohd Tajudin; Mohd Najib Mohd Hussain; Mashitah Mohd Hussain; Intan Rahayu Ibrahim
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.pp3641-3650

Abstract

Due to the increased demand for renewable energy, the interest in the large-scale solar photovoltaic (LSSPV) power plant has recently grown dramatically. However, when a large amount of electricity is produced from the LSSPV power plant to the grid interconnection, the system commonly experiences instability and thus disrupt the grid system in disturbance issues such as bus fault, line-to-line fault, three-phase fault, and tripping. This sudden disturbance occurrence is tended to interrupt the stability of the system from providing balanced electrical production within the electrical grid. A dynamics response from the simulation is used to study the stability and the behavior of the photovoltaic (PV) plant into the grid interconnection by developing 118 bus system. The observation of critical clearing time (CCT) duration shows that the result from the simulation where the duration takes less than t=15 s for the system to get back to its pre-fault condition in three-phase fault and tripping in a dynamic simulation to shows that the system reaches its stability been observed through the simulation result by using from user-specific models to generic models like those advocated by the Western electricity coordinating council (WECC) in power system simulator for engineering (PSSE) software.
An innovative fast iterative process algorithm computerization for intermittency LSSPV generation reconfiguration Mashitah Mohd Hussain; Zuhaina Zakaria; Nofri Yenita Dahlan; Ihsan Mohd Yassin; Mohd Najib Mohd Hussain
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp628-638

Abstract

The recent implementation of solar photovoltaic (SPV) power generation in low-voltage distribution networks has increased due to its environmentally friendly technology, low cost, and high efficiency. However, SPV generation carried both the availability of uncertainty and intermittency on power energy exceeding voltage range, increased losses during reverse power flow action, and energy transmission problems. This paper presents a new capabilities methodology with accurate analysis to simulate the intermittent nature of SPV energy including normal generators associated with uncertain customer demand of high resolution with 1-minute temporal resolution using a fast iterative process algorithm (FIPA) simulated by Python programming. The primary goal is to address the unpredictable nature of SPV using computer operation technology connected to a real network with a fast iteration process. The result shows that in 0-10% of standard generators, grid energy (GE) is still required in daily supply, and the intermittent nature influences voltage violations and losses. Besides, the prediction typical SPV method (zero fluctuation) can serve as guidelines for engineers to design the photovoltaic (PV) module reducing its fluctuating nature and battery installation area. The research provides utilities with accurate information to plan for various difficulties at different levels of PV penetration while reducing time, effort, and resource utilization.
Co-Authors Ihsan Mohd Yassin Intan Rahayu Ibrahim Md Azwan Md Yasin Mohammad Nayeim Fazumy Mohd Tajudin Mohd Najib Mohd Hussain Nofri Yenita Dahlan Noor Hasliza Abdul Rahman Nur Iqtiyani Ilham Zhafran Hussin Zuhaina Zakaria