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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Indonesian Journal of Electrical Engineering and Computer Science
Zuhaina Zakaria
Universiti Teknologi MARA
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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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.
Ant Lion Optimizer for Solving Unit Commitment Problem in Smart Grid System Izni Nadhirah Sam’on; Zuhaila Mat Yasin; Zuhaina Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp129-136

Abstract

This paper proposed the integration of solar energy resources into the conventional unit commitment. The growing concern about the depletion of fossil fuels increased the awareness on the importance of renewable energy resources, as an alternative energy resources in unit commitment operation. However, the present renewable energy resources is intermitted due to unpredicted photovoltaic output. Therefore, Ant Lion Optimizer (ALO) is proposed to solve unit commitment problem in smart grid system with consideration of uncertainties .ALO is inspired by the hunting appliance of ant lions in natural surroundings. A 10-unit system with the constraints, such as power balance, spinning reserve, generation limit, minimum up and down time constraints are considered to prove the effectiveness of the proposed method. The performance of proposed algorithm are compared with the performance of Dynamic Programming (DP). The results show that the integration of solar energy resources in unit commitment scheduling can improve the total operating cost significantly. 
Optimal reactive power pricing with transformer variable taps using genetic algorithm Ahmad Kor; Hossein Zeynal; Zuhaina Zakaria; Seyed Hamid Hosseini
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1272-1280

Abstract

Ancillary services in interconnected networks are crucial to secure real power transfers, maintaining network reliability, improving power quality as well as network stability. Reactive power has always been of special importance as one of the most substantial ancillary services required to control the voltage in power grid. This paper presents a fresh reactive power pricing approach by embedding variable transformer taps into voltage ampere reactive (var) pricing method. To carry out the resultant optimization problem with a set of complicating constraints, the genetic algorithm takes part and guarantees the global optimal solution. The simulation results show that when transformer tap works as a control variable, the total cost of reactive power can be decreased. However, the incorporation of transformer taps in the pricing model can slightly complicates voltage profiles as the sensitivity of bus voltages to the reactive power variations in the system is increased. Further, the findings reiterate that by optimal position of transformer taps, technically, the security index of the system can be enhanced while the var price for end-users (lowest purchase cost for independent system operator) being more reasonable. To simulate the proposed reactive pricing method, the standard IEEE 30-bus system is employed to analyze the proposed method.
An efficient MPPT based photovoltaic control model considering environmental parameters Hossein Zeynal; Zuhaina Zakaria; Bahareh Pourveis
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i4.pp2432-2439

Abstract

This paper presents an efficient way for maximum power point tracking (MPPT) in photovoltaic (PV) system. MPPT is one of the crucial issues when working with PV system as well as the grid.  To gain the highest efficiency for PV system the maximum power has to be generated continuously. The proposed MPPT method allows PV system to have real-time maximum power all the time with high accuracy and less fluctuations. As of the developed PV system control model presented in this work, an efficient MPP can be realized taking into account changes in irradiation level and temperature which are the thorny issues for other contender algorithms. To validate the model, results obtained from the proposed algorithm is compared with incremental conductance (IC) which is a universally accepted MPPT method. The simulation results exhibited that the developed model outperforms IC method in terms of accuracy of MPP and stability of the output in presence of variable irradiations and temperature. Based on the simulation results, the proposed algorithm is suitable for practical and real-time applications with promising results in terms of solution accuracy and execution. The model is implemented in MATLAB/Simulink.
Co-Authors Ahmad Kor Bahareh Pourveis Hossein Zeynal Hossein Zeynal Izni Nadhirah Sam’ón Mashitah Mohd Hussain Md Azwan Md Yasin Nofri Yenita Dahlan Noor Hasliza Abdul Rahman Nur Iqtiyani Ilham Seyed Hamid Hosseini Zhafran Hussin Zuhaila Mat Yasin