Mohamad Fani Sulaima | Universiti Teknikal Malaysia Melaka (original) (raw)
Papers by Mohamad Fani Sulaima
ASEAN Engineering Journal
Demand side management (DSM) has been conventionally adopted in many ways to efficiently managing... more Demand side management (DSM) has been conventionally adopted in many ways to efficiently managing the appropriate electricity loads. However, with the sophisticated design of the Time of Use (TOU) tariff to reflect electricity cost reduction, implementing proper Load Management (LM) strategies is challenging. To date, consumers still struggle to define a figure for the LM percentage to be involved in the demand response program. Due to that reason, this study proposes a method to find the best load profile reflecting the new tariff offered by using a combination of optimization algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Evolutionary PSO (EPSO), and Self-Organizing Mapping (SOM). The evaluation has been made to the manufacturing operation with the existing flat tariff to be transferred to the Enhanced Time of Use (ETOU). The test results show that the ability of the proposed combination method to define the optimal outputs such as energy cons...
IAES International Journal of Artificial Intelligence, Dec 1, 2022
The world faces a significant impact from the coronavirus disease 2019 (Covid-19) pandemic, which... more The world faces a significant impact from the coronavirus disease 2019 (Covid-19) pandemic, which also influences energy consumption. This study investigates the substantial connection of the classified data between power consumption, cooling degree days, average temperature, and covid-19 cases information using mathematical and neural network approaches regression analysis, and self-organizing maps. It is well established that various data mining methods have revamped the classification process of data analytics. Specifically, this study investigates the correlation between the collected variables using regression analysis and selecting the best-matching unit under the normalization method using self-organizing maps. The selforganizing maps become better when the datasets have variations; the result denotes that this method produced high mapping quality based on the map size and normalization method. Furthermore, the data crossing connection is indicated using the regression analysis method. Finally, the classified data results during the movement control order are validated in self-organizing maps to achieve the study objective. By performing these methods, this study established that the correlation between the energy demand towards cooling degree days, average temperature, and covid-19 cases is very weak. The verification has been made where the 'logistic' normalization method has produced the best classification result.
Indonesian Journal of Electrical Engineering and Computer Science
A price-based program through a time of use tariff (TOU) program is one of the initiatives to off... more A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed...
International Journal of Power Electronics and Drive Systems (IJPEDS)
Distributed generation (DG) can be beneficially allocated in distribution power systems to improv... more Distributed generation (DG) can be beneficially allocated in distribution power systems to improve the power system's efficiency. However, specious DG's allocation and sizing may cause more power loss and voltage profile issues for distribution feeders. Therefore, optimization algorithms are vital for future intelligent power distribution network planning. Hence, this study proposes a multi-objective firefly analytical hierarchy algorithm (FAHA) for determining the optimal allocation and sizing of DG. The multi-objective function formulation is improved further by integrating analytical hierarchy process (AHP) with FA to obtain the weight of the coefficient factor (CF). The performance of the proposed approach is verified on the 118-bus radial distribution network with different bus voltage at DG location (VDG) as regulated PV-bus during load flow calculations. The calculated CF and impact of the unregulated voltage at the PV-bus on the objectives function have been analysed...
Bulletin of Electrical Engineering and Informatics
Demand response (DR) program through tariff initiative has been established in Malaysia since 199... more Demand response (DR) program through tariff initiative has been established in Malaysia since 1990. The available time of use (TOU) tariff focuses on providing price signals to consumers, especially from industrial and commercial sectors. In achieving a certain standard for off-peak tariff rider (OPTR) initiative to receive discount rate, consumers must improve load factors compared to the baseline declared. However, not all consumers are able to commit. In Universiti Teknikal Malaysia Melaka (UTeM), the TOU (C1-OPTR) tariff is proposed and applied when the available cost discount of 20% can be enjoyed by sustaining the load factor improvement (LFI). A simulator projected a flexible optimal load profile referred by the energy management team to achieve the university's sustainable energy management goal. Thus, securing the LFI would allow the energy consumption (kWh) and peak demand (kW) to be managed concurrently. As for testing results for two buildings, the load factor improv...
International Journal of Advanced Computer Science and Applications, 2020
The demand response program involves consumers to mitigate peak demand and reducing global CO2 em... more The demand response program involves consumers to mitigate peak demand and reducing global CO2 emission. In sustaining this effort, energy provider such as Tenaga Nasional Berhad (TNB) in Peninsular Malaysia has introduced Enhance Time of Use (ETOU) tariff. However, since 2015, small numbers join the ETOU program due to less confidence in managing their energy consumption profile. Thus, this study provides an optimum forecasting load profile model for TOU and ETOU tariffs using Artificial Neural Network (ANN). An industry's average energy profile has been used as a case study, while the forecasting technique has been conducted to find the optimum energy load profile congruently. The load shifting technique has been adopted under ETOU tariff price while integrating to the ANN procedure. A significant comparison in terms of cost reduction between TOU and ETOU electricity tariffs has been made. In contrast, ANN performance results in searching for the best-shifted load profile have been analyzed accordingly. From the proposed method, the total electricity cost saving has been founded to be saved for about 7.9% monthly. It is hoped that this work will benefit the energy authority and consumers in future action, respectively.
Research Journal of Applied Sciences, Engineering and Technology, 2014
This study presents the implementation of Improved Genetic Algorithm (IGA) to minimize the power ... more This study presents the implementation of Improved Genetic Algorithm (IGA) to minimize the power losses in the distribution network by improving selection operator pertaining to the least losses generated from the algorithm. The major part of power losses in electrical power network was highly contributed from the distribution system. Thus, the need of restructuring the topological of distribution network configuration from its primary feeders should be considered. The switches identification within different probabilities cases for reconfiguration purposes are comprehensively implemented through the proposed algorithm. The investigation was conducted to test the proposed algorithm on the 33 radial busses system and found to give the better results in minimizing power losses and voltage profile.
Bulletin of Electrical Engineering and Informatics, 2019
This paper presents load shifting strategy for cost reduction on manufacturing electricity demand... more This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program
Applied Sciences, 2018
The presence of optimized distributed generation (DG) with suitable distribution network reconfig... more The presence of optimized distributed generation (DG) with suitable distribution network reconfiguration (DNR) in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO) is proposed in this research. The objective function is formulated to minimize the total power losses (TPL) and to improve the voltage stability index (VSI). The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO) and iteration particle swarm optimization (IPSO). Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.
Indonesian Journal of Electrical Engineering and Computer Science, 2017
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advance... more The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are convent...
Energy Procedia, 2016
This paper investigates the impact of solar resource variability on the operation of a low-voltag... more This paper investigates the impact of solar resource variability on the operation of a low-voltage On-Load-Tap-Changer (OLTC) in a generic distribution network from the Malaysian grid. The OLTC's operation is studied in two different weather conditions-sunny and cloudy days. The aspects analysed are the OLTC's time delay setting, PV penetration levels and PV installation location. The results suggest that the number of tap changes in a cloudy day is approximately 1.5 times higher than in a sunny day. In addition, at 50% PV penetration level on a cloudy day, the OLTC operation increases by 38% and it is doubled at 100% penetration.
Research Journal of Applied Sciences, Engineering and Technology, 2014
The increase of energy demand has generated a complexity of electrical network while contributing... more The increase of energy demand has generated a complexity of electrical network while contributing to the numbers of power losses in the system. This study presents a Distribution Feeder Reconfigurtion (DFR) by using heuristic algorithm which is called as Rank Evolutionary Programming (REP). The main objectives of this study are to improve the computing time and minimize the power losses effectively. The performance of the REP method will be investigated and the impact to the test system IEEE 16-kV distribution network will be analyzed accordingly. The results of this study is hoped to help the engineers in order to secure and increase the efficiency of the real power distribution system in the future.
2014 5th International Conference on Intelligent Systems, Modelling and Simulation, 2014
Distribution network planning and operation require the identification of the best topological co... more Distribution network planning and operation require the identification of the best topological configuration that is able to fulfill the power demand with minimum power loss. This paper presents an efficient hybridization of both Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) methods which is called the Evolutionary Particle Swarm Optimization (EPSO). The proposed method is used to find the optimal network reconfiguration and optimal size of Distribution Generation (DG) simultaneously. The main objective of this paper is to gain the lowest result of real power losses in the distribution network while improve the computational time as well as satisfying other operating constraints. A comprehensive performance analysis is carried out on IEEE 33 bus distribution system. The proposed method is applied and its impact on the network reconfiguration for real power loss is investigated. The results are presented and compared with the strategy of separated DG sizing and network reconfiguration.
Applied Mechanics and Materials, 2015
The installation of distributed generation (DG) gives advantages to the environment such as, it c... more The installation of distributed generation (DG) gives advantages to the environment such as, it contribute in the reduction of non-peak operating cost, diversification of energy resources, lower losses thus improving overall organization. These advantages might be rescinded if no proper location and sizing of DGs are considered before the DG’s installation. This paper offers an optimal location and sizing of multiple DGs using heuristic method called gravitational search algorithm (GSA). The suggested algorithm is tested on 13-bus radial distribution system. This method is being compared with particle swarm optimization (PSO) in terms of system power loss, voltage deviation and total voltage harmonic distortion (THDv). GSA shows the ability to locate and sized DG optimally with a better performance and more reliable than PSO.
This paper focuses on the case study of engineering ethics for Gas Pipeline Explosion at Ghisleng... more This paper focuses on the case study of engineering ethics for Gas Pipeline Explosion at Ghislenghien, Belgium. The tragedy happened on 30 th of July, 2004 and investigation was conducted to find the root cause. However, the question is remains unsolved. Investigators and experts listed few reasons that may affecting the gas pipeline including safety regulations not being observed due to deadline given is too short, soil erosion and used of mechanical diggers within one meter of the gas pipe. Rescue operation was initiated immediate after the gas explosion. This tragedy causes 24 dead including 5 fire fighters and indicated an amount of 100 million euros lost and lead to multiple reformation. Therefore, a case study of engineering ethics has been done and the analysis has been made in terms of ethical framework and ethical theories respectively. The recommendation of this study is hoped to help the engineers in order to reduce the numbers of accident in their work place.
The increment of the numbers for accidents due to building safety system errors has created a ser... more The increment of the numbers for accidents due to building safety system errors has created a serious disaster over the year. Due to that reason, this paper presents the entitled Building Heat Detection System (BHD System) by the objectives to develop the proper circuit in order to secure the detection device during the building fire attack. A BHD system, also known as fire protection system consists of heat sensing and monitoring system. The sensors detect extreme heat in an area or zone; the control unit processes the signals and sets off evacuation alarms to alert building occupants. This study focused on the design and fabrication of the system prototype to demonstrate the operation of a BHD system in case of fire accidents. Hose reel indicator is included to display the exact location in a building to aid in firefighting. On top of that, exit indicators were added to show the available exits should fire breaks out in a building. This study is hoped to help the system engineers to improve and secure their building safety system in the future.
This paper presents the implementation of Multi Objective Particle Swarm Optimization in controll... more This paper presents the implementation of Multi Objective Particle Swarm Optimization in controlling motion control of Gantry Crane System. Three objective functions are considered to be optimized, named (i) steady state error, (ii) overshoot, and (iii) settling time. Six cases with different setting of weight summation are analyzed in order to obtain five parameters (PID and PD) controller. A combination of PID and PD controller is observed and utilized for controlling trolley movement to desired position and reduced the payload oscillation concurrently. Various cases of weight summation values will affect to the controller parameters and system responses. The performances of the system is conducted and presented within Matlab environment.
The complexity of modern power system has contributed to the high power losses and over load in t... more The complexity of modern power system has contributed to the high power losses and over load in the distribution network. Due to that reason, Feeder Reconfiguration (FR) is required to identify the best topology network in order to fulfill the power demand with reduced power losses while stabilizing the magnitude of voltage. This paper addresses a new optimization method which is called as Rank Evolutionary Particle Swarm Optimization (REPSO). It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. The main objective of this paper is to improve the voltage profile while solves the overload problem by reducing the power losses respectively. The proposed method has been implemented and the real power losses in the 33kVdistribution system has been investigated and analyzed accordingly. The results are compared to the conventional Genetic Algorithm (GA), EP and PSO techniques and it is hoped to help the power system engineer in securing the network in the future.
In the worldwide trend toward restructuring the electricity network; there are a lot of problems.... more In the worldwide trend toward restructuring the electricity network; there are a lot of problems. Where with the increasing of electricity demand, intelligence algorithm is one of the optimization search engine that may help in minimizing the power losses in the power distribution network. This paper presents a method of 16kV Distribution Network Reconfigurtion (DNR) by using Evolutionary Programming (EP). The main objectives of this study are to minimize the power losses and improve the voltage profile while analyzing the consistency and computing time effectively. The performance of the Evolutionary Programming method will be investigated and the impact to the 16kV distribution network will be analyzed. Thereal result will be compared with the conventional initial network and other optimization technique which is Genetic Algorithm (GA). The results of this study is hoped to help the power system engineers in Malaysia in order to solve the losses problem in the plant at the same time increasing the efficiency of the real 16-bus distribution system.
ASEAN Engineering Journal
Demand side management (DSM) has been conventionally adopted in many ways to efficiently managing... more Demand side management (DSM) has been conventionally adopted in many ways to efficiently managing the appropriate electricity loads. However, with the sophisticated design of the Time of Use (TOU) tariff to reflect electricity cost reduction, implementing proper Load Management (LM) strategies is challenging. To date, consumers still struggle to define a figure for the LM percentage to be involved in the demand response program. Due to that reason, this study proposes a method to find the best load profile reflecting the new tariff offered by using a combination of optimization algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Evolutionary PSO (EPSO), and Self-Organizing Mapping (SOM). The evaluation has been made to the manufacturing operation with the existing flat tariff to be transferred to the Enhanced Time of Use (ETOU). The test results show that the ability of the proposed combination method to define the optimal outputs such as energy cons...
IAES International Journal of Artificial Intelligence, Dec 1, 2022
The world faces a significant impact from the coronavirus disease 2019 (Covid-19) pandemic, which... more The world faces a significant impact from the coronavirus disease 2019 (Covid-19) pandemic, which also influences energy consumption. This study investigates the substantial connection of the classified data between power consumption, cooling degree days, average temperature, and covid-19 cases information using mathematical and neural network approaches regression analysis, and self-organizing maps. It is well established that various data mining methods have revamped the classification process of data analytics. Specifically, this study investigates the correlation between the collected variables using regression analysis and selecting the best-matching unit under the normalization method using self-organizing maps. The selforganizing maps become better when the datasets have variations; the result denotes that this method produced high mapping quality based on the map size and normalization method. Furthermore, the data crossing connection is indicated using the regression analysis method. Finally, the classified data results during the movement control order are validated in self-organizing maps to achieve the study objective. By performing these methods, this study established that the correlation between the energy demand towards cooling degree days, average temperature, and covid-19 cases is very weak. The verification has been made where the 'logistic' normalization method has produced the best classification result.
Indonesian Journal of Electrical Engineering and Computer Science
A price-based program through a time of use tariff (TOU) program is one of the initiatives to off... more A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed...
International Journal of Power Electronics and Drive Systems (IJPEDS)
Distributed generation (DG) can be beneficially allocated in distribution power systems to improv... more Distributed generation (DG) can be beneficially allocated in distribution power systems to improve the power system's efficiency. However, specious DG's allocation and sizing may cause more power loss and voltage profile issues for distribution feeders. Therefore, optimization algorithms are vital for future intelligent power distribution network planning. Hence, this study proposes a multi-objective firefly analytical hierarchy algorithm (FAHA) for determining the optimal allocation and sizing of DG. The multi-objective function formulation is improved further by integrating analytical hierarchy process (AHP) with FA to obtain the weight of the coefficient factor (CF). The performance of the proposed approach is verified on the 118-bus radial distribution network with different bus voltage at DG location (VDG) as regulated PV-bus during load flow calculations. The calculated CF and impact of the unregulated voltage at the PV-bus on the objectives function have been analysed...
Bulletin of Electrical Engineering and Informatics
Demand response (DR) program through tariff initiative has been established in Malaysia since 199... more Demand response (DR) program through tariff initiative has been established in Malaysia since 1990. The available time of use (TOU) tariff focuses on providing price signals to consumers, especially from industrial and commercial sectors. In achieving a certain standard for off-peak tariff rider (OPTR) initiative to receive discount rate, consumers must improve load factors compared to the baseline declared. However, not all consumers are able to commit. In Universiti Teknikal Malaysia Melaka (UTeM), the TOU (C1-OPTR) tariff is proposed and applied when the available cost discount of 20% can be enjoyed by sustaining the load factor improvement (LFI). A simulator projected a flexible optimal load profile referred by the energy management team to achieve the university's sustainable energy management goal. Thus, securing the LFI would allow the energy consumption (kWh) and peak demand (kW) to be managed concurrently. As for testing results for two buildings, the load factor improv...
International Journal of Advanced Computer Science and Applications, 2020
The demand response program involves consumers to mitigate peak demand and reducing global CO2 em... more The demand response program involves consumers to mitigate peak demand and reducing global CO2 emission. In sustaining this effort, energy provider such as Tenaga Nasional Berhad (TNB) in Peninsular Malaysia has introduced Enhance Time of Use (ETOU) tariff. However, since 2015, small numbers join the ETOU program due to less confidence in managing their energy consumption profile. Thus, this study provides an optimum forecasting load profile model for TOU and ETOU tariffs using Artificial Neural Network (ANN). An industry's average energy profile has been used as a case study, while the forecasting technique has been conducted to find the optimum energy load profile congruently. The load shifting technique has been adopted under ETOU tariff price while integrating to the ANN procedure. A significant comparison in terms of cost reduction between TOU and ETOU electricity tariffs has been made. In contrast, ANN performance results in searching for the best-shifted load profile have been analyzed accordingly. From the proposed method, the total electricity cost saving has been founded to be saved for about 7.9% monthly. It is hoped that this work will benefit the energy authority and consumers in future action, respectively.
Research Journal of Applied Sciences, Engineering and Technology, 2014
This study presents the implementation of Improved Genetic Algorithm (IGA) to minimize the power ... more This study presents the implementation of Improved Genetic Algorithm (IGA) to minimize the power losses in the distribution network by improving selection operator pertaining to the least losses generated from the algorithm. The major part of power losses in electrical power network was highly contributed from the distribution system. Thus, the need of restructuring the topological of distribution network configuration from its primary feeders should be considered. The switches identification within different probabilities cases for reconfiguration purposes are comprehensively implemented through the proposed algorithm. The investigation was conducted to test the proposed algorithm on the 33 radial busses system and found to give the better results in minimizing power losses and voltage profile.
Bulletin of Electrical Engineering and Informatics, 2019
This paper presents load shifting strategy for cost reduction on manufacturing electricity demand... more This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program
Applied Sciences, 2018
The presence of optimized distributed generation (DG) with suitable distribution network reconfig... more The presence of optimized distributed generation (DG) with suitable distribution network reconfiguration (DNR) in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO) is proposed in this research. The objective function is formulated to minimize the total power losses (TPL) and to improve the voltage stability index (VSI). The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO) and iteration particle swarm optimization (IPSO). Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.
Indonesian Journal of Electrical Engineering and Computer Science, 2017
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advance... more The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are convent...
Energy Procedia, 2016
This paper investigates the impact of solar resource variability on the operation of a low-voltag... more This paper investigates the impact of solar resource variability on the operation of a low-voltage On-Load-Tap-Changer (OLTC) in a generic distribution network from the Malaysian grid. The OLTC's operation is studied in two different weather conditions-sunny and cloudy days. The aspects analysed are the OLTC's time delay setting, PV penetration levels and PV installation location. The results suggest that the number of tap changes in a cloudy day is approximately 1.5 times higher than in a sunny day. In addition, at 50% PV penetration level on a cloudy day, the OLTC operation increases by 38% and it is doubled at 100% penetration.
Research Journal of Applied Sciences, Engineering and Technology, 2014
The increase of energy demand has generated a complexity of electrical network while contributing... more The increase of energy demand has generated a complexity of electrical network while contributing to the numbers of power losses in the system. This study presents a Distribution Feeder Reconfigurtion (DFR) by using heuristic algorithm which is called as Rank Evolutionary Programming (REP). The main objectives of this study are to improve the computing time and minimize the power losses effectively. The performance of the REP method will be investigated and the impact to the test system IEEE 16-kV distribution network will be analyzed accordingly. The results of this study is hoped to help the engineers in order to secure and increase the efficiency of the real power distribution system in the future.
2014 5th International Conference on Intelligent Systems, Modelling and Simulation, 2014
Distribution network planning and operation require the identification of the best topological co... more Distribution network planning and operation require the identification of the best topological configuration that is able to fulfill the power demand with minimum power loss. This paper presents an efficient hybridization of both Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) methods which is called the Evolutionary Particle Swarm Optimization (EPSO). The proposed method is used to find the optimal network reconfiguration and optimal size of Distribution Generation (DG) simultaneously. The main objective of this paper is to gain the lowest result of real power losses in the distribution network while improve the computational time as well as satisfying other operating constraints. A comprehensive performance analysis is carried out on IEEE 33 bus distribution system. The proposed method is applied and its impact on the network reconfiguration for real power loss is investigated. The results are presented and compared with the strategy of separated DG sizing and network reconfiguration.
Applied Mechanics and Materials, 2015
The installation of distributed generation (DG) gives advantages to the environment such as, it c... more The installation of distributed generation (DG) gives advantages to the environment such as, it contribute in the reduction of non-peak operating cost, diversification of energy resources, lower losses thus improving overall organization. These advantages might be rescinded if no proper location and sizing of DGs are considered before the DG’s installation. This paper offers an optimal location and sizing of multiple DGs using heuristic method called gravitational search algorithm (GSA). The suggested algorithm is tested on 13-bus radial distribution system. This method is being compared with particle swarm optimization (PSO) in terms of system power loss, voltage deviation and total voltage harmonic distortion (THDv). GSA shows the ability to locate and sized DG optimally with a better performance and more reliable than PSO.
This paper focuses on the case study of engineering ethics for Gas Pipeline Explosion at Ghisleng... more This paper focuses on the case study of engineering ethics for Gas Pipeline Explosion at Ghislenghien, Belgium. The tragedy happened on 30 th of July, 2004 and investigation was conducted to find the root cause. However, the question is remains unsolved. Investigators and experts listed few reasons that may affecting the gas pipeline including safety regulations not being observed due to deadline given is too short, soil erosion and used of mechanical diggers within one meter of the gas pipe. Rescue operation was initiated immediate after the gas explosion. This tragedy causes 24 dead including 5 fire fighters and indicated an amount of 100 million euros lost and lead to multiple reformation. Therefore, a case study of engineering ethics has been done and the analysis has been made in terms of ethical framework and ethical theories respectively. The recommendation of this study is hoped to help the engineers in order to reduce the numbers of accident in their work place.
The increment of the numbers for accidents due to building safety system errors has created a ser... more The increment of the numbers for accidents due to building safety system errors has created a serious disaster over the year. Due to that reason, this paper presents the entitled Building Heat Detection System (BHD System) by the objectives to develop the proper circuit in order to secure the detection device during the building fire attack. A BHD system, also known as fire protection system consists of heat sensing and monitoring system. The sensors detect extreme heat in an area or zone; the control unit processes the signals and sets off evacuation alarms to alert building occupants. This study focused on the design and fabrication of the system prototype to demonstrate the operation of a BHD system in case of fire accidents. Hose reel indicator is included to display the exact location in a building to aid in firefighting. On top of that, exit indicators were added to show the available exits should fire breaks out in a building. This study is hoped to help the system engineers to improve and secure their building safety system in the future.
This paper presents the implementation of Multi Objective Particle Swarm Optimization in controll... more This paper presents the implementation of Multi Objective Particle Swarm Optimization in controlling motion control of Gantry Crane System. Three objective functions are considered to be optimized, named (i) steady state error, (ii) overshoot, and (iii) settling time. Six cases with different setting of weight summation are analyzed in order to obtain five parameters (PID and PD) controller. A combination of PID and PD controller is observed and utilized for controlling trolley movement to desired position and reduced the payload oscillation concurrently. Various cases of weight summation values will affect to the controller parameters and system responses. The performances of the system is conducted and presented within Matlab environment.
The complexity of modern power system has contributed to the high power losses and over load in t... more The complexity of modern power system has contributed to the high power losses and over load in the distribution network. Due to that reason, Feeder Reconfiguration (FR) is required to identify the best topology network in order to fulfill the power demand with reduced power losses while stabilizing the magnitude of voltage. This paper addresses a new optimization method which is called as Rank Evolutionary Particle Swarm Optimization (REPSO). It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. The main objective of this paper is to improve the voltage profile while solves the overload problem by reducing the power losses respectively. The proposed method has been implemented and the real power losses in the 33kVdistribution system has been investigated and analyzed accordingly. The results are compared to the conventional Genetic Algorithm (GA), EP and PSO techniques and it is hoped to help the power system engineer in securing the network in the future.
In the worldwide trend toward restructuring the electricity network; there are a lot of problems.... more In the worldwide trend toward restructuring the electricity network; there are a lot of problems. Where with the increasing of electricity demand, intelligence algorithm is one of the optimization search engine that may help in minimizing the power losses in the power distribution network. This paper presents a method of 16kV Distribution Network Reconfigurtion (DNR) by using Evolutionary Programming (EP). The main objectives of this study are to minimize the power losses and improve the voltage profile while analyzing the consistency and computing time effectively. The performance of the Evolutionary Programming method will be investigated and the impact to the 16kV distribution network will be analyzed. Thereal result will be compared with the conventional initial network and other optimization technique which is Genetic Algorithm (GA). The results of this study is hoped to help the power system engineers in Malaysia in order to solve the losses problem in the plant at the same time increasing the efficiency of the real 16-bus distribution system.