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Interconnection of distributed generation (DG) in distribution system will result in formation of islands in the event of loss of main supply. This scenario is harmful to the power system, hence quick detection is critical to halt the formation of islands. Among the common passive and active detection methods available, the hybrid detection method is identified as the most reliable method. This paper proposes a new hybrid method using the combination of passive and active technique which is the rate of change of frequency (ROCOF) and load impedance, respectively. The passive method works when the value of ROCOF exceeds the threshold value which is set at 0.3Hz/s. The active method works when it detects low value of ROCOF and immediately inject a pre-specified load into the system to increase the ROCOF value up to its threshold value. Simulation study on different case studies is carried out on distribution test system to evaluate the performance of the proposed method. Results show that this method is effective in detecting any events that could result in islanding.

Optimal Network Reconfiguration (NR) is a well-accepted approach to minimize power loss and enhance voltage profile in the Electrical Distribution Networks (EDN). Since the NR problem contains huge combinational search space, most researchers consider the meta-heuristic techniques to attain NR solution. However, these meta-heuristic techniques do not guarantee to obtain the optimal solution besides they require large processing time to converge. This is mainly due to (1) random initialization and updating of population and (2) the continuous verification of population during the search process. With the aim of reducing the computational time and improving the consistency in obtaining the optimal solution as well as minimizing power loss and enhancing the voltage profile of the EDN, this work proposes a new method based on two-stage optimizations. The proposed method introduces an approach to simplify the network into simplified network graph. Then, this approach is utilized for guided initializations and generations of the population and for the proper population’s codification. The proposed method is implemented using the firefly algorithm and verified on 33-bus and 118-bus test systems. The results show the ability of the proposed method to obtain the optimal solution within fast computational time and with superior consistency compared to the conventional methods.

Virtual synchronous generator (VSG) is an important concept toward frequency stabilisation of the modern power system. The penetration of power electronic-based power generation in power grid reduces the total inertia, and thus increases the risk of frequency instability when disturbance occurs in the grid. VSG produces virtual inertia by injecting appropriate active power value to the grid when needed. This virtual inertia can stabilise the grid frequency in case of a power imbalance between generation and loads or any disturbances that affected frequency stability. Its intensive research can see the importance of VSG in inertia control and various intelligent controller techniques. Owing to the importance of VSG in the modern power grid, this study provides a comprehensive review on the control and coordination of VSG toward grid stabilisation in terms of frequency, voltage and oscillation damping during inertia response. A review on the type of energy storage system used for VSG and their benefits is also presented. Finally, perspective on the technical challenges and potential future research related to VSG is also discussed in this study.

Reducing the self-power consumption of an off-grid solar home system is an economic model in which consumer employs photovoltaic (PV) system for its own electrical requirements. The latch-based clock gating approach has been employed in existing solar charge controllers to reduce integrated circuit (IC) power being used in the low-powered intended mode, although the reducing power is limited. This paper presents a self-power reduction technique based on wake-up power and latch-hold time; which minimize power supply during idle time for a solar home system. Wake-up power introduces a push-switch mechanism using typical transistor technology. Latch-hold time function is designed using an operational amplifier and negative-positive-negative (NPN) transistor. A technique with dynamic self-supply mechanism is also introduced for decreasing self-power consumption. The self-power consumption is identified via simulation studies where the result shows that the power usage is 70% lower than traditional approaches. This is determined using a simulated wave-shape analysis.

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

A related input parameter is used in this case study to forecast solar thermal systems (STS) capabilities and to compare which artificial neural network (ANN) algorithms and other artificial intelligence (AI) methods have the most reliable predictor for STS performance. In order to gauge the performance of the STS, this research aims to implement AI for predicting STS performance by comparing the ANN technique with other methods. Three different training algorithms which are Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Bayesian regularization (BR) are considered in this research. This research will identify acceptable parameters and the best AI technique to use in predicting the STS performance. Previous research on STS demonstrates that the efficiency of STS has been estimated using different input parameters. The results show that the prediction of the LM training algorithm is the best for STS performance.

To achieve a more sustainable supply of electricity and reduce dependency on fuels, the application of renewable energy sources-based distribution systems (DS) is stimulating. However, the intermittent nature of renewable sources reduces the overall inertia of the power system, which in turn seriously affects the frequency stability of the power system. A virtual synchronous generator can provide inertial response support to a DS. However, existing active power controllers of VSG are not optimized to react to the variation of frequency changes in the power system. Hence this paper introduces a new controller by incorporating GA-ANFIS in the active power controller to improve the performance of the VSG. The advantage of the proposed ANFIS-based controller is its ability to optimize the membership function in order to provide a better range and accuracy for the VSG responses. Rate of change of frequency (ROCOF) and change in frequency are used as the inputs of the proposed controller to control the values of two swing equation parameters, inertia constant (J) and damping constant (D). Two objective functions are used to optimize the membership function in the ANFIS. Transient simulation is carried out in PSCAD/EMTDC to validate the performance of the controller. For all the scenarios, VSG with GA-ANFIS (VOFIS) managed to maintain the DS frequency within the safe operating limit. A comparison between three other controllers proved that the proposed VSG controller is better than the other controller, with a transient response of 22% faster compared to the other controllers.

Electrical energy source in Malaysia is commonly from by fossil fuel such as coal, petroleum, LNG, LPG, kerosene, etc. However, these unrenewable sources of energy are neither economical nor favorable to the environment. Even though Malaysia produces enough electricity to meet current consumption levels, the reduction of electrical usage should be taken for us as a main consumer in this country in order to reduce energy consumption. Towards this end, solar energy seems to be a singularly legitimate and feasible source of alternative energy for heating water. Solar energy is permanently renewable, environmentally beneficial, and convertible to various energy forms. A solar water heating system is used to convert solar energy to thermal energy to heat water. This research investigates the application of solar energy to meet water heating needs especially in Malaysia and models the water heating system. Through modelling in the simulation, the average system efficiency for solar collector and thermal storage are determined as the total costs on a daily basis or monthly average.

The islanding operation of a distribution network connected with distributed generation may be a useful way to improve its power reliability. However, it requires a good control strategy for ensuring a safe operation of islanded system controlling voltage and frequency of the system within their permissible range. This paper proposed a centralized controller to coordinate the islanding operation with multiple islanding configurations for rotating type DGs. Multiple islanding configurations are introduced to maximize the benefit of islanded operation. The advantage of the proposed strategy is that DG will be able to operate in different islanding areas instead of energizing only one islanding area. The proposed controller regularly communicates with the governor and excitation controllers of the DG units with the utility grid to carry out action in case of an islanding event. The performance of the proposed controller is investigated for various simulations carried out on an existing Malaysia distribution network. The simulation results show that the islanding operation for each configuration is dynamically stable.

Cost/benefit analysis of power system is one of the most challenging task due to the impact of electric utility deregulation and market competition. However, it becomes an essential factor in order to determine the system reinforcement and expansion projects. A major role in the application reliability concepts and accomplishment of an acceptable level of reliability is economic. Therefore, it is important to determine the optimal reliability level at which the reliability investment achieves the best results in reducing the customer damage costs due to power supply interruption. This paper presents an assessment of reliability cost/benefit index of expected customer interruption cost (ECOST) by considering power system contingency which are load adjustment and transmission line tripping by applying the sensitivity analysis. ECOST index quantifies the reliability of power system in terms of monetary. The value of ECOST is evaluated based on load increment/decrement and transmission line tripping. In order to calculate ECOST, load curtailment is performed. IEEE Reliability Test System 1979 (IEEE RTS- 79) is used to validate the assessment of ECOST due to load adjustment and line tripping. The findings have proved that the ECOST increases with the increased of the total loading condition and line tripping. Therefore, this method could be applied in order to assist the power system utility in monitoring the contingency in the system.

Transient stability in power system is vital to be addressed due to large disturbances that could damage the system such as load changes and voltage increases. This paper presents a multi-machine transient stability using the Static Synchronous Series Compensator (SSSC). SSSC is a device that is connected in series with the power transmission line and produces controllable voltage which contribute to a better performance in the power system stability. As a result, this research has observed a comparison of the synchronization of a three-phase system during single-phase faults before and after installing the SSSC device. In addition, this research investigates the ability of three different types of controllers i.e. Proportional Integral (PI), Proportional Integral Derivation (PID), and Generic controllers to be added to the SSSC improve the transient stability as it cannot operate by itself. This is because the improvement is too small and not able to achieve the desired output. The task presented is to improve the synchronization of the system and time taken for the voltage to stabilize due to the fault. The simulation result shows that the SSSC with an additional controller can improve the stability of a multi-machine power system in a single phase fault.

In recent years significant changes in climate have pivoted the distribution system towards renewable energy, particularly through distributed generators (DGs). Although DGs offer many benefits to the distribution system, their integration affects the stability of the system, which could lead to blackout when the grid is disconnected. The system frequency will drop drastically if DG generation capacity is less than the total load demand in the network. In order to sustain the system stability, under-frequency load shedding (UFLS) is inevitable. The common approach of load shedding sheds random loads until the system&rsquo, s frequency is recovered. Random and sequential selection results in excessive load shedding, which in turn causes frequency overshoot. In this regard, this paper proposes an efficient load shedding technique for islanded distribution systems. This technique utilizes a voltage stability index to rank the unstable loads for load shedding. In the proposed method, the power imbalance is computed using the swing equation incorporating frequency value. Mixed integer linear programming (MILP) optimization produces optimal load shedding strategy based on the priority of the loads (i.e., non-critical, semi-critical, and critical) and the load ranking from the voltage stability index of loads. The effectiveness of the proposed scheme is tested on two test systems, i.e., a 28-bus system that is a part of the Malaysian distribution network and the IEEE 69-bus system, using PSCAD/EMTDC. Results obtained prove the effectiveness of the proposed technique in quickly stabilizing the system&rsquo, s frequency without frequency overshoot by disconnecting unstable non-critical loads on priority. Furthermore, results show that the proposed technique is superior to other adaptive techniques because it increases the sustainability by reducing the load shed amount and avoiding overshoot in system frequency.

This paper presents the transient stability analysis (TSA) in a power system based on one machine infinite bus (OMIB) and equal area criterion (EAC) method. A typical power system network consists of numerous components such as generators, transformers, interconnected lines and loads. Due to the enormous number of electrical components in a power system, it is difficult to perform the TSA for the entire network. Therefore, this research proposes a TSA by using one machine infinite bus (OMIB) technique. The main purpose to use OMIB is due to the fact that it could minimize the multi-machine in the network by facilitate the original large-scale system to dynamic equivalent model. The propose technique classify the multi-machine system into two groups which are: critical machines and non-critical machines, which is then reduced to only one machine infinite bus system (OMIB). This paper also presents the analysis of critical clearing angle (CCA) where it is the maximum change in the load angle curve before clearing the fault without loss of generator synchronism. Three phase fault conditions which are; pre-fault, during fault and post-fault conditions are used in the transmission line via the equal area criterion (EAC) method. This method could identify whether the condition may cause to system instability if there is a sudden load increase to the system. The main objective to perform CCA analysis is to identify the value of rotor angle that is important and could be set as a benchmark to the protection relay in order to maintain the transient stability during fault condition. This paper also proposes a monitoring mechanism by using graphical user interface (GUI) to monitor the CCA at different system loading condition. The IEEE RTS-79 is used to validate the robustness of the proposed methodology in determining the CCA.

Islanding detection is important for the protection of any distribution system supported by distributed energy resources. In this work, a number of islanding and non-islanding events are simulated to prioritise 16 different passive parameters on the basis of performance analysis. Among the parameters tested, the rate of change of frequency over reactive power (df/dq) attains the highest accuracy and consequently, a new passive technique is proposed that employs df/dq as discriminative feature. An extended study is carried out to further test the ability of the technique to differentiate the islanding from the non-islanding events of similar signatures, such as load variation, capacitor switching, faults and induction motor starting. The simulation results confirm that the technique is proficient enough to identify islanding from non-islanding events that cause minute disturbances in the power supply network.

Placing DG closer to the load in the system can improve the grid reliability and power quality, however it can lead to some technical issues such as islanding which requires attention from utility and Independent Power Producer (IPP). One of the important issues in power system distribution is islanding detection for protecting the DG when islanding operation occurred. The detection technique is employed so that the islanding event can be detected within the time frame. The main reason of detecting islanding situation at distribution level is to monitor the DG output or system parameters thus can determine the occurrence of islanding situation from the change of these parameters. Therefore, this paper presents the performance of multiple parameters of passive islanding detection technique in distribution system connected with synchronous type of DG. Sixteen passive parameters including rate of change of frequency (df/dt), rate of change of voltage (dv/dt), rate of change of active power (dp/dt), and rate of change of reactive power (dq/dt) are evaluated. The sensitivity analysis of these parameters are determined via simulation in terms of variation of loads, fault events and load switching on various events that are islanding and non-islanding events. The analysis indicates that each parameter displays a different pattern of sensitivity towards islanding event.

This work analyzes the sensitivity of 16 power system parameters that can be used in passive techniques to detect islanding and nonislanding events. It is observed that the rate of change of frequency over reactive power ( $df/dq$ ) can effectively detect minute disturbances in power supply. It is also shown that active and reactive power mismatch has an opposing effect on the variation of frequency ( df ) in real time environment. As a result of this, a new passive technique based on $df/dq$ is proposed. The simulation results indicate that the proposed technique is able to distinguish islanding from other events of similar signatures, such as load variation, capacitor switching, faults, and induction motor starting.

Programme Educational Objectives (PEOs) are specific goals that are aligned with the vision and mission of an institution of higher learning. The PEOs describe the expected achievements of the graduates in their career and professional accomplishment after graduation. At Faculty of Electrical Engineering, Universiti Teknologi MARA, the PEOs of undergraduate programmes are particularly designed to ensure that the graduates are well-equipped with a broad foundation of theoretical and practical knowledge in various electrical engineering areas of interest and to prepare them for the rapidly changing engineering technology. These PEOs are carefully aligned with the vision and mission of the university and faculty and should be achieved by the graduates 3 to 4 years after graduating. These PEOs must be assessed and evaluated to determine the PEOs’ attainment of the programme. Therefore, assessment and evaluation activities must be available to plan and organize the process of obtaining the PEOs’ attainment. Surveys on graduate attributes need to be conducted to gain feedbacks from stakeholders 3 to 4 years after graduation. In this study, anonymous online questionnaire survey was created to obtain the feedbacks from the alumni. These feedbacks are then analysed to assess the PEOs’ attainment. In order to evaluate the performance of the PEOs, performance indicators are developed and used in the evaluation. Outcomes from this study are used to determine the achievement of PEOs and to propose the improvement as part of continuous quality improvement (CQI).

Long term load forecasting data is important for grid expansion and power system operation. Besides, it also important to ensure the generation capacity meet electricity demand at all times. In this paper, Least-Square Support Vector Machine (LSSVM) is used to predict the long-term load demand. Four inputs are considered which are peak load demand, ambient temperature, humidity and wind speed. Total load demand is set as the output of prediction in LSSVM. In order to improve the accuracy of the LSSVM, Grey Wolf Optimizer (GWO) is hybridized to obtain the optimal parameters of LSSVM namely GWO-LSSVM. Mean Absolute Percentage Error (MAPE) is used as the quantify measurement of the prediction model. The objective of the optimization is to minimize the value of MAPE. The performance of GWO-LSSVM is compared with other methods such as LSSVM and Ant Lion Optimizer – Least-Square Support Vector Machine (ALO-LSSVM). From the results obtained, it can be concluded that GWO-LSSVM provide lower MAPE value which is 0.13% as compared to other methods.

The increasing penetration of electric vehicle (EV) at distribution system is expected in the near future leading to rising demand for power consumption. Large scale uncoordinated charging demand of EVs will eventually threatens the safety operation of the distribution network. Therefore, a charging strategy is needed to reduce the impact of charging. This paper proposes an optimal centralized charging schedule coordination of EV to minimize active power losses while maintaining the voltage profile at the demand side. The performance of the schedule algorithm developed using particle swarm optimization (PSO) technique is evaluated at the IEEE-33 Bus radial distribution system in a set time frame of charging period. Coordinated and uncoordinated charging schedule is then compared in terms of active power losses and voltage profile at different level of EV penetration considering 24 hours of load demand profile. Results show that the proposed coordinated charging schedule is able to achieve minimum total active power losses compared to the uncoordinated charging.

This paper presents a new under-frequency load shedding technique based on the combination of random and fixed priority of loads. It has been observed that placing all of the loads in the distribution system with fixed priority results in un-optimum load shedding. On the other hand, designing the load priority with a combination of random and fixed priority provides the technique with some sort of flexibility in achieving the optimal load shedding. The validation of the proposed scheme on different scenarios proves that the proposed technique is capable of achieving the optimal load shedding and recovering frequency to nominal value without any overshoot.

This paper presents a voltage stability assessment based approach to determine the congested line with optimal sizing and location. FVSI, a voltage stability index is chosen as the indicator for congested line identification, while particle swarm optimization technique (PSO) is used for optimal location and sizing of FACTs devices installation. Congested line is identified by increasing the reactive load at chosen load buses until they reach the maximum loadability level. PSO is applied for identifying the optimal location and sizing of FACTs devices as the compensating device. Results obtained from the implementation on IEEE 30 Bus RTS revealed that the proposed technique can manage the congestion subject to various disturbances.

Interconnection of Distributed Generation (DG) in distribution system presents many potential benefits as well as drawbacks. The impacts of DG might vary with the types of generator. This paper presents a study on the impacts of synchronous DG's interconnection in distribution system. Steady state analysis is carried out to analyze the impact of DG on voltage profile and short circuit current considering before and after DG interconnection. Dynamic analysis is also performed for investigating the performance of DG when a part of distribution system is being islanded. Results show that the penetration of DG contributes to the changes of power flow in the system, hence give impacts to the overall system performance.

The exponential growth in electricity demand has driven the Distributed Generation (DG) technology a boost in the power system. The use of DG is beneficial to power utilities, DG owners׳, and end-users in terms of reliability, power quality, and economics. However, to fully utilize the benefits of DGs, some technical issues need to be addressed. Islanding condition is one of the most important issue in this context. Until now, several islanding detection techniques have been proposed for detecting the islanding condition. This paper presents a brief overview of existing islanding detection techniques with their relative merits and demerits. Apart from this, the paper presents an islanding detection strategy suitable for hybrid DG resources of mini-hydro and Bio-Mass. The proposed strategy uses average rate of change of reactive power and load shift strategy to detect islanding of the distribution network. The performance of proposed strategy is validated on various islanding and non-islanding events. The results of proposed strategy are compared with other existing techniques in terms of fast islanding detection, and non-detection zone. The simulation results show that the proposed strategy is effective in detecting islanding phenomenon possesses fast detection and negligible non-detection zone region compared to existing islanding detection techniques.

In many countries around the world, the electric power systems are operating in a deregulated environment where the generation, transmission and distribution systems owned by different companies will enhance intense competition in the electricity market among them in order to provide more reliable, cost effective and efficient electricity to the consumers. For that reason, the power system dynamic security assessment and control is becoming more challenging task in the transfer capability determination due to several new constraints, obligations and challenges that need to be encountered by the utility. Dynamic response of a system plays an imperative role in the analysis of system stability and blackout events that usually caused by the impact of enormous and unforeseen occurrence of fault, unexpected generation and load outages, and abrupt disengagement of loads. This paper presents a monitoring tool by using the Graphical User Interface (GUI) in order to monitor the frequency response of a power system due to the effect of contingency event. The proposed technique has been validated by using the IEEE Reliability Test System. This technique can assist the utility in order to monitor the stability of a power system in the event of contingency.

Power system is heavily loaded with increase in electricity demand. Frequency instability during islanding scenarios is an important issue to be addressed. Frequency instability happens when the power balance between generation and load demand is not met. During islanding, Under-Frequency Load Shedding (UFLS) technique is implemented to stabilize the system frequency and to ensure uninterrupted power supply to the customers. This paper proposes an optimal load shedding approach using Particle Swarm Optimization (PSO) technique for islanded mode of operation. The technique determines the optimal amount of load that needs to be shed considering power imbalance. The proposed load shedding approach is developed using MATLAB and is validated on distribution system modeled using PSCAD software. Simulation results show that the proposed PSO based approach was able to stabilize the system frequency by shedding the load optimally.

The aim of this research is to anticipate the stability status of a power system when the system is exposed to a change in frequency and rotor angle due to small disturbances. The proposed study was implemented on the IEEE Reliability Test System 1979 (IEEE RTS-79) which contains 24 buses, 38 transmission lines and 32 generators. Steady state stability limit of a system refers to the maximum amount of power that is permissible through the system without loss of its steady state stability. This research proposes the development of a Graphical User Interface (GUI) to observe the frequency and rotor angle stability due to the effect of small disturbances using the One Machine Infinite Bus (OMIB) technique. This proposed technique could ease the power system utility especially the power system operation to observe and examine the system frequency and rotor angle stability due to small disturbances. The findings from this research has proven that the proposed technique to observe the frequency and rotor angle stability due to small disturbances has successfully been developed using a GUI.

Prediction of solar irradiance is important for minimizing energy costs and providing high power quality in a photovoltaic (PV) system. This paper proposes a new technique for prediction of hourly-ahead solar irradiance namely Grey Wolf Optimizer- Least-Square Support Vector Machine (GWO-LSSVM). Least Squares Support Vector Machine (LSSVM) has strong ability to learn a complex nonlinear problems. In GWO-LSSVM, the parameters of LSSVM are optimized using Grey Wolf Optimizer (GWO). GWO algorithm is derived based on the hierarchy of leadership and the grey wolf hunting mechanism in nature. The main step of the grey wolf hunting mechanism are hunting, searching, encircling, and attacking the prey. The model has four input vectors: time, relative humidity, wind speed and ambient temperature. Mean Absolute Performance Error (MAPE) is used to measure the prediction performance. Comparative study also carried out using LSSVM and Particle Swarm Optimizer-Least Square Support Vector Machine (PSO-LSSVM). The results showed that GWO-LSSVM predicts more accurate than other techniques.

Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system.