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In this paper, a simplified model of an isolated microgrid (IMG) with hybrid photovoltaic (PV)-battery energy storage system (BESS) is discussed. The concept of peak load shaving is also demonstrated. The developed model helps an isolated power system to minimize the demand and maximize the economic benefit. MATLAB/Simulink tool was used to simulate the electrical circuit of the IMG system. The IMG model contains four sub-systems, namely the PV model, time varying load profile model, BESS model and gas turbine generator (GTG) dispatch model. To evaluate the performance of the developed IMG, a simulation case study was conducted under realistic load conditions of Universiti Teknologi PETRONAS (UTP). Results indicated that simulation illustrates the precise situation of the real-time system, as found in the UTP microgrid. Results also revealed that the concept of peak load shaving broadly illustrated in this study. The implementation of the proposed IMG model may bring economic benefit by minimizing peak load demand. © 2021 Md Masud Rana et al.

In this study, a significant literature review on peak load shaving strategies has been presented. The impact of three major strategies for peak load shaving, namely demand side management (DSM), integration of energy storage system (ESS), and integration of electric vehicle (EV) to the grid has been discussed in detail. Discussion on possible challenges and future research directions for each type of the strategy has also been included in this review. For the energy storage system, different technologies used for peak load shaving purpose, which include their methods of operation and control have been elaborated further. Finally, the sizing of the ESS storage system is discussed. For the demand side management system, various management methods and challenges associated with DSM implementation have been thoroughly explained. A detailed discussion on the electric vehicle strategy has also been included in the review, which considers the integration, control and operation techniques for implementing the peak load shaving.

A novel peak load shaving algorithm has been proposed in this study for peak shaving application in hybrid PV-BESS connected Isolated Microgrid (IMG) system. This algorithm will help an IMG system to operate its generation systems optimally and economically along with PV generation unit. An IMG model has been developed in MATLAB/Simulink environment with actual load data, conventional Gas Turbine Generator (GTG), Photovoltaic (PV) generation system and Battery Energy Storage System (BESS). The proposed algorithm has been tested with the designed IMG model. To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. The simulation results demonstrate that the algorithm can minimize the limitations of the existing methods and it can use the PV generation system effectively. Peak shaving service can be found from this algorithm as a simple and forcible way. A comparative analysis has been conducted of the proposed algorithm with the conventional methods. The comparison results can easily reflect that the proposed algorithm can ensure the optimal use of PV generation system and can serve peak shaving service effectively. It can also ensure an economic and environment friendly system where the existing algorithms are limited to serve these. The proposed algorithm can mitigate the available power issues for hybrid PV-BESS connected system and it can also minimize the operating cost by dispatching the generation units optimally.

Aerial imagery is important in remote sensing applications. Unmanned aerial vehicle (UAV) has a wide range of applications in remote sensing and presents a substantial cost-effective soluti...

Aerial scene classification purposes to automatically label aerial images with specific semantic categories. However, cataloguing presents a fundamental problem for high-resolution remote-sensing imagery HRRS. Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network CNN approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle UAV and satellite imagery. The article has two major sections: the first describes the extraction of dense multiscale features multiple scales from the last convolutional layer of a pre-trained CNN models; the second describes the encoding of extracted features into global image features via sparse coding to achieve scene classification. The authors compared experimental outcomes with existing techniques such as Scale-Invariant Feature Transform and demonstrated that features from pre-trained CNNs generalized well with HRRS datasets and were more expressive than low-and mid-level features, exhibiting an overall 90.3% accuracy rate for scene classification compared to 85.4% achieved by SIFT with sparse coding. Thus, the proposed CNN-based sparse coding approach obtained a robust performance that holds promising potential for future applications in satellite and UAV imaging.

As of now, energy demand of the world increases year by year and many nations are facing with the critical environmental issues related to conventional energy sources. Along this line, utilities and clients have broadly acknowledged the utilization of contamination-free sustainable energy-source based power generations, including solar energy. Solar energy is an alluring choice and has attracted a great attention and consideration since the most recent couple of decades because of the significant price drop in photovoltaic (PV) cells.

An improvement for a new hybrid power system model is presented. The improvement considers the most accurate model that gives the exact energy output from the Solar photovoltaic (SPV) system to give more accurate result about the perfect size of the PV in the hybrid photo-voltaic and gas turbine generator (GTG) (H-PVGTG) system. This result will affect the size of both the battery bank and the GTG units. The values must justify the technical requirements of the system reliability. This value is recommended to be 0.01 in Malaysia, and it is known as the Loss of Load Probability (LLP). The main goal of the research is to get the most accurate system size with the lowest Annualized Total Life-Cycle Cost (ATLCC). The mathematical model (Math-M) that has been used in the optimization algorithm saved more than 38 % from the operating cost of the power system that is used to supply the power to Universiti Teknologi PETRONAS (UTP). However, it has an error in the power output compared with the actual site power output. Due to the high operating cost of GTG system compared even with the grid supply in Malaysia, Tenaga Nasional Berhad (TNB). This paper proposed an Artificial Intelligent (AI) model to overcome the increase in the operating cost with lower power output error than the Math-M. The main challenge of the mathematical model was the low accuracy as it has +6.09% error than the actual power output of the SPV system and that is why a black box model (BB-M) has been trained to overcome this problem. A comparison between the BB-M, Math-M, GTG system, and TNB has been presented in this paper. The result concluded that BB-M has more accuracy than Math-M if compared with the actual power output of SPV system.

In this study, the performance of an islanded gas turbine power generation system in Malaysia was investigated. Considering the low fuel efficiency of the plant during peak and part-load operations, an economic analysis was also carried out, over the period of one year (2017). The case study was conducted on the isolated electrical network of the Universiti Teknologi PETRONAS (UTP), which consists of two gas turbine units with a total capacity of 8.4 MW. Simple performance indicators were developed to assess the performance, which can also be applied to other power stations in Malaysia and elsewhere. Meanwhile, the economy of variable load operations was analyzed using the statistical data of generation, fuel consumption, and loads. The study reveals that the capacity factor of the microgrid in the period was between 52.77&ndash, 63.32%, as compared to the industrial best practice of 80%. The average plant use factor for the period under review was 75.04%, with a minimum of 70.93% and a maximum of 78.61%. The load factor of the microgrid ranged from 56.68&ndash, 65.47%, as compared to the international best practice of 80%, while the utilization factor was between 44.22&ndash, 67.655%. This study further reveals that high fuel consumption rates, due to the peak and part-load operations, resulted in a revenue loss of approximately 17,379.793 USD per year. Based on the present performance of the microgrid, suggestions are made for the improvement of the overall performance and profitability of the system. This work can be valuable for microgrid utility research to identify the most economical operating conditions.

Dengue and chikungunya fevers are transmitted by the common mosquito vector Aedes and malaria by Anopheles. Concurrent infections are reported due to co-circulation of these pathogens, especially in endemic regions. We report a rare case of triple infection with 3 arthropod-borne pathogens (Plasmodium vivax and the dengue and chikungunya viruses) in a 3-year-old child from New Delhi, India, in August 2016. The viruses were identified by RT-PCR and the parasite by microscopy and antigen detection. The dengue virus serotype 3 sequence was clustered in the genotype III by the phylogenetic analysis. Mixed infection with multiple pathogens is a challenge for accurate diagnosis due to the overlapping clinical symptoms. The accurate and timely diagnosis of multiple pathogens in such cases is important for rapid and effective patient management.

The objective of this study is to propose a decision-tree-based peak shaving algorithm for islanded microgrid. The proposed algorithm helps an islanded microgrid to operate its generation units efficiently. Effectiveness of the proposed algorithm was tested with a BESS-based MATLAB/Simulink model of an actual microgrid under realistic load conditions which were recorded. To evaluate the performance, simulation case studies were conducted under various load conditions and results were compared with conventional techniques. Results showed that the proposed algorithm offers a simple and effective way of peak load shaving without heavy computational burdens often needed in other methods. The comparison analysis verified that the proposed algorithm can effectively mitigate the peak load demand regardless of the schedule of the generators, where conventional methods were limited. The financial benefit investigation shows that microgrid utility can enjoy substantial savings, while reducing of the peak demand of the microgrid. Thus, the islanded microgrid that include fuel-based generation can implement the proposed technique to reduce the consumption of fuel and increase the efficiency of fuel-based generation through peak load mitigation.

A Dry-Low Emission (DLE) gas turbine is introduced due to a stringent requirement of government policy on Carbon Monoxide (CO) and Nitrogen Oxide (NOx) emissions in industry. The establishment demands a reliable model for dynamic and stability study where the conventional gas turbine model need to be adjusted. A well-established model for a gas turbine study is Rowen’s model but it still need to be modified to fit DLE gas turbine requirement. The most significant difference is the introduction of Pilot Gas Fuel Valve in DLE instead of only Main Gas Fuel Valve. Thus, the objective of this research is to model and perform system identification of gas fuel valves in Rowen’s Model for DLE gas turbine suitability. The operational data were used to model main and pilot fuel valve in system identification and integrated into the widely used Rowen’s model. The result of the transfer functions were compared and the first order transfer function exhibits a good fit and high accuracy model for DLE gas turbine and the operational behavior of pilot gas fuel valve. The modification of Rowen’s model is able to produce a high accuracy model for DLE gas turbine and the operational behavior of pilot gas fuel valve can be studied after the integration.

Load flow (LF) analysis is an inextricable part of an in-depth study on microgrid. In this study, AC load flow method was used in MATLAB environment to evaluate the performance of an islanded microgrid. The future directions had also been outlined from the analysis results to improve the overall performance of the microgrid. Simulation case study was conducted on an isolated electrical network of Universiti Teknologi PETRONAS (UTP) which consists of 27 buses. To achieve the goal, voltage magnitude and phase angle at each bus bar, total power flow (both active and reactive) in branches, and power losses in microgrid were computed from load flow analysis. The comparison and analysis of load flow results revealed that this simulation approximately depict the precise situation of the real time system as found in the UTP microgrid. Every component of UTP microgrid network tested to determine whether it is under or over loaded. These results indicated that all elements are within TNBs specifications. After the full load simulation, the impact of several parameters upon the performance was demonstrated, and alternatives were suggested to improve the performance.

A new adaptive power system harmonic estimator is presented, which is competent of tracking power system harmonic components. The proposed estimator technique is based on the normalized Least Mean Square (LMS), which is a stochastic gradient descent algorithm. The learning method of the proposed estimator is based upon the recursive estimate of the signal power, and is faster tracking of harmonic components as compared to the introduced Adaptive Linear Element (ADALINE).

The objective of this paper is to investigate the impact of the spiral coil shape of inductive coupled power transfer on its performance. The coil shapes evaluated are: circular, square and pentagon spiral shapes. The coils are modelled in Ansoft Maxwell software. Simulations are carried out to determine the mutual inductance, coupling coefficient and magnetic flux density. The performance in term of magnetic flux density, mutual inductance and coupling coefficient of the three coils shapes are compared. Of the three shapes, the pentagon is shown to have the best performance in term of its mutual inductance, coupling coefficient and magnetic flux density.

Hybrid renewable energy system is introduced in this new era as an effective solution to provide remote residential villages, off-grid small commercial or industrial areas and off-grid offshore installations which do not require extensive generation capability with clean and cheap power supply.

A stringent requirement of government policy on Carbon Monoxide (CO) and Nitrogen Oxide (NOx) emissions leads to the introduction of dry-low emission (DLE) gas turbines. Although Rowen's model is well established for a gas turbine dynamic study, its utilization for a DLE representation has not been extensively studied. Thus, the objective of this research is to study the suitability of using the Rowen's Model for the DLE gas turbine operational performance. All the available actual operation parameters were correlated to measure its dependency and only Rowen's parameters were selected. The operational data were used to calculate Rowen's block and the proposed model was assessed using a series of inlet guide vane and gas fuel flow command, a temperature setpoint and the actual speed data as an input. The behavior of the output; power, average turbine temperature and gas engine fuel flow were analyzed. Indeed, Rowen's model is capable to produce a good fit and high accuracy model for DLE gas turbine operational behavior.

Dry Low Emission (DLE) operation mode for gas turbine is introduced to reduce nitrogen oxide (NOx) emission and to meet current stringent environment regulation imposed on gas turbine. A good gas turbine model is essential for simulation study or fault prediction. However, there are no effort on modelling DLE gas turbine currently. Nonlinear Autoregressive with Exogenous Input (NARX), a black-box modelling approach has been identified as the suitable option for modelling gas turbine in DLE mode as it enables the development of good model without any assumptions. The results show that the developed NARX model can be used to represent the behavior of the DLE gas turbine with high accuracy and good generalization.

The third harmonic current produced by salient pole synchronous generator has always been associated with high neutral current causing problem to neutral earthing resistor, telecommunication system, and earthfault protection. In this paper, the third harmonic model for salient pole synchronous generator in symmetrical component domain is proposed that comprise of generator parameter and generated voltage. The new computational technique in determining the third harmonic zero-sequence synchronous impedance is introduced. In completing the model, the method to characterize generated third harmonic zero-sequence voltage under balanced combine resistive and inductive load is described. In order to study the third harmonic current flowing in the network, the propagation model is also established. The third harmonic synchronous generator parameters are measured and comparatively validated with laboratory experiment results. In addition to that, the third harmonic generated voltage is characterized and validated experimentally.

Frequency estimation is a vital tool for many power system applications such as load shedding, power system security assessment and power quality monitoring. Moreover, the complexity and noisiness of modern power system networks have created challenges for many power system applications. Fast and accurate frequency estimation in the presence of noise is a challenging task. Sliding window with the complex form of least mean square (LMS) algorithm has been utilized in this study in order to improve the frequency estimation in noisy power system. Different simulation cases have been examined for signal with different signal to noise ratio (SNR) and to evaluate the performance of sliding window method for better frequency estimation. The results obtained show that the sliding window method with LMS is able to improve and enhance the frequency estimation even when the (SNR) is small compared to the existing LMS method.

Zika virus is an arthropod-borne re-emerging pathogen associated with the global pandemic of 2015-2016. The devastating effect of Zika viral infection is reflected by its neurological manifestations such as microcephaly in newborns. This scenario evoked our interest to uncover the neurotropic localization, multiplication of the virus, and the mechanism of microcephaly. The present report provides an overview of a possible molecular mechanism of Zika virus-induced microcephaly based on recent publications. Transplacental transmission of Zika viral infection from mother to foetus during the first trimester of pregnancy results in propagation of the virus in human neural progenitor cells (hNPCs), where entry is facilitated by the receptor (AXL protein) leading to the alteration of signalling and immune pathways in host cells. Further modification of the viral-induced TLR3-mediated immune network in the infected hNPCs affects viral replication. Downregulation of neurogenesis and upregulation of apoptosis in hNPCs leads to cell cycle arrest and death of the developing neurons. In addition, it is likely that the environmental, physiological, immunological, and genetic factors that determine in utero transmission of Zika virus are also involved in neurotropism. Despite the global concern regarding the Zika-mediated epidemic, the precise molecular mechanism of neuropathogenesis remains elusive.

Due to the advance in technology nowadays the application of nonlinear load is very demanding. The nonlinear loads that consist of power electronics devices in many applications may leads to power quality problems, and one of the major problems in power quality is harmonics. Active filter is a common tool has been used for harmonic mitigation, however the active filter use digital signal processing (DSP) to calculate the harmonic information which cause time delay between measured and injected harmonic that can results in failure to fully cancel the harmonics. This paper presents the concept, method and function of adaptive filters using Least Mean Square (LMS) and Recursive Least Square (RLS) to predict real time harmonics that may use in active filter to compensate for the time delay caused by the process of acquiring harmonic information. The results shown that the RLS and NLMS algorithms present a better performance than LMS and the mean square error (MSE) in general is increased when the harmonic order numbers that construct the signal increases.

In recent times, the Gas District Cooling (GDC) plant in Universiti Teknologi PETRONAS (UTP) has suffered faults throughout the power system network due to many reasons. It was reported that third harmonic component exists in its fault current. Synchronous generator is one of the triplen harmonic sources and third harmonic is the major component. Therefore, this paper intends to study the contribution of third harmonic produced by synchronous generator during three-phase to ground fault. Lab scale experiments are conducted to investigate the contribution of third harmonic towards overall fault current. The third harmonic current during normal operation is first measured and considered as base data. Then, third harmonic current during three-phase to ground fault is measured and compared with the base data. During three-phase to ground fault, the load impedance is removed from the circuit and the line is connected directly to the ground. It is found out that the contribution of third harmonic during three-phase to ground fault is significantly high compared to normal operation. The third harmonic fault current depends on effective zero sequence impedance of the circuit. During the fault, the effective zero sequence impedance of the circuit reduces and inversely the third harmonic current increases greatly.

Third harmonic (TH) current from salient-pole synchronous generator that return to its neutral via cable capacitance or other neutral grounding points in the network can cause the neutral earthing resistor (NER) to experience high temperature. Generator neutral earthing reactance (NERX) can be used to mitigate the TH current flowing in the neutral under normal condition. This paper aims to study the suitable design of NERX to be implemented in Universiti Teknologi PETRONAS (UTP) distribution system to reduce the TH current at the generator neutral. The model of UTP distribution system is developed using MATLAB Simulink in order to simulate the flow of TH current. NERX is then designed and implemented to the system to mitigate the magnitude of TH current. Various values of NERX are applied to the system as the neutral current and fault current are recorded and graphed. The application of 0.175 H NERX increased the TH neutral current in island mode and normal operation to 33.18 %. However, the NERX causes the TH fault current to reduce to 44.33 % under fault. For parallel mode, 78.27 % of TH neutral current and also 42.91 % of TH fault current are reduced under normal operation and fault respectively.

Summary Conducted experiment proves that third harmonic (TH) component of salient-pole synchronous generator behaves differently compared with fundamental frequency component in terms of generated voltage. Fundamental frequency-generated voltage depends on the excitation system, and the generated voltages before and during fault are almost the same. However, TH-generated voltage is independent of the excitation system. In other words, variation of the excitation current does not affect the generation of TH voltage as much as it affects the generation of fundamental frequency voltage. On top of that, the generation of TH voltage before and during fault varies significantly. Hence, a typical method to solve fault analysis for 3-phase–to–ground fault is not applicable in TH domain. Therefore, in this article, a method to find TH-generated voltage is proposed. The TH-generated voltage during 3-phase–to–ground fault is presented in terms of percentage called the harmonic fundamental ratio, which is the ratio of TH zero-sequence–generated voltage to fundamental frequency–positive sequence-generated voltage during fault. The harmonic fundamental ratio is obtained by short circuiting the generator terminal prior to the application in the system. It turns out that the generated TH voltage by synchronous generator depends on the zero-sequence TH impedance of the TH fault current path. Lastly, the proposed method to obtain TH-generated voltage by salient-pole synchronous generator is validated by comparing the calculated TH fault current with the actual TH fault current obtained from experiment.

Water tree degradation is categorized as a pre-breakdown mechanism associated with Medium voltage (MV) power insulation failure. It is a slow degradation process, which turns into deterioration of dielectric properties of the cable insulation. The presence of water trees in cable insulation causes the generation of harmonic current components in the loss current. The water tree distribution in varying portions of the cable insulation has been modeled and simulated by utilizing MATLAB/Simulink in this study. The water tree degraded portion in the cable insulation was modeled by utilizing a nonlinear equation. In order to examine the frequency dependence on induced water tree degradation, two different test techniques were utilized in MATLAB/Simulink. Namely, the 3rd harmonic current-based method and the series resonant-based test method. In the first test method, the model was simulated by 50 Hz to 150 Hz by a step increase of test frequency by 25 Hz. The series resonant test method was utilized to test the water tree degraded cable insulation model; the test setup consisted of an inductor (L). The test was implemented by a variable frequency of 0 to 1000 Hz. The results of both test techniques show that the water tree distribution in varying cable insulation lengths can be quantified precisely.

Recently, in the world wide the use of power electronics devices increases sharply. As a result, harmonic pollution becomes a vital problem than before. Harmonics rotate in the power system network and interfere with the system equipments, disturbing their normal operation which can deteriorate the quality of the delivered power. Therefore, efficient method with low computational time is a critical tool to estimate and quantify the harmonic that can be used in online control and mitigation of harmonics. Least Mean Square (LMS) is simple and popular algorithm that has been applied in many applications, but, noise can affect its performance. This paper presents and compare the performance of Least Mean Square (LMS), Least Mean Fourth (LMF) and a combined (LMS/LMF) in estimation harmonic component for the signal corrupted with noise contain low signal to noise ratio (SNR). The results show that LMF and LMS/LMF have better steady state performance as compared to LMS.

Frequency estimation is an essential technique to the power system network especially when many power system applications such as load shedding, security assessment and protection relays rely on it. Therefore, rapid and precise frequency estimator is required. This paper present normalized variable step size least mean square with the complex form to estimate the fundamental power system frequency. The complex form of the voltage signal is obtained from the three phase voltages using transforming method. To evaluate the performance of the presented method several simulation cases that may be found in real system have been conducted and the results compared to the existing variable step size least mean square frequency estimation method. Moreover, the result reveals that the presented method has fast convergence speed as compared to the existing method.

The widespread use of power electronics devises and nonlinear loads in power system grids is increasing in the last decades leads to rise of harmonic in power system signals. Great damage to power system gird can happen due to harmonics. Thus it is important to precisely estimate the harmonics components that may help to avoid its harmful effect of the electrical grid performance. The more common algorithm that has been used to estimate the harmonic component is the Fast Fourier Transform (FFT), however FFT has few limitations, furthermore, modern power system network getting complex and noisy. Therefore, fast and accurate harmonic estimation in the presence of noise is needed. Sliding window based least mean square (LMS) algorithm is introduced in this paper to estimate the harmonic components in noisy environment. The result shows that the sliding window method able to give a good estimation to the harmonic component even when the signal to noise ratio (SNR) is 0 dB.

The third harmonic has caused much power quality problem in the neutral of distribution system. Salient pole synchronous generator has been recognized as one of the triplen/third harmonic sources. This research is aimed at studying the characteristic of third harmonic from generator flowing through the load directly, via transformer and shunt connection to rectifier. Lab scale experiments have been conducted to vary load impedance and transformer winding configuration. When generator is connected directly to a combined resistive and inductive load, the third harmonic current and voltage depend on the load impedance magnitude and phase angle. Since the third harmonic voltage produced by generator are in phase or zero sequence in nature, the third harmonic current depend on transformer winding configuration, the load impedance magnitude and phase angle. When full-wave bridge rectifier is shunt connected between generator and load, the third harmonic current at both rectifier and load are actually coming from generator that depend on load impedance magnitude and phase angle. It is recommended that the study on third harmonic voltage and current propagation from generator should be done by performing harmonic measurement and analysis at all parts of the network. Third harmonic voltage and current magnitude alone may not give correct indication to their severity because they are vector quantity and rely on zero sequence network, load impedance magnitude and phase angle.

Medium voltage (MV) cross linked polyethylene (XLPE) insulated power cables are being used in electrical power distribution system networks throughout the world. Deterioration like voids, cracks, delimitation, protrusions and contaminants in the cable insulation may initiate water tree, electrical tree and partial discharge. Water treeing is the main cause of insulation failure in MV power cables. The nonlinear dielectric response of water tree generates harmonics in the AC loss current. This paper presents a detailed study of the characterization of XLPE cable insulation. The morphological study of XLPE cable samples has been carried out by using the Scanning Electron Microscope (SEM) and the chemical analysis has been carried out by using Fourier Transform Infrared spectroscopy (FTIR). The MATLAB/SIMULINK program has been used to model and simulate degradation in the power cable due to water tree. This model is simulated with supply frequencies at 50 Hz, 100 Hz and 150 Hz. The 3rd harmonic current has been recorded from the total current flowing through the cable insulation. The generated harmonics have a good relationship with degradation caused by water tree.

Salient pole synchronous generator is one of harmonic sources that causes various power system harmonic problem especially related to neutral. This paper aims to study the characteristics of third harmonic voltage and current from generator when connected to balanced load via cable, generator load connection with different generator neutral grounding resistor and generator load connection shunted by zig-zag transformer. Lab scale experiments have been conducted to vary all parameters related to cable capacitor and generator neutral grounding resistor under various combined resistive and inductive load. Cable capacitance which depends on cable length, size and number of parallel cable, combined with load impedance determines the third harmonic current magnitude. The presence of cable capacitance that interact with generator inductance resulted to series harmonic resonance at 9th and 15th harmonic order that causes high 9th and 15th harmonic current flowing between generator and cable capacitor. Generator neutral grounding resistor can effectively reduce the third harmonic in the phase and neutral. However care should be taken not to use very high generator neutral grounding resistor that can also restrict earth fault current that may pose problem to the sensitivity of earth fault protection system. Zig-zag transformer efficiently divert third harmonic current from generator to enter the load but high circulating third harmonic current between generator and zig-zag transformer may pose heating problem to the equipments.

Medium voltage (MV) crosslink polyethylene (XLPE) power cables are extensively utilized in power distribution networks throughout the world. Reliable power delivery depends on the condition of the power cable and distribution system network components. Failure of power cables can cause loss in terms of power outages, capital, and human resources. This is a prime area for research. Degradation of the physical properties of the insulation over time is the usual cause of power cable failure. Factors responsible for XLPE cable degradation include but are not limited to mechanical, electrical and chemical stresses, flaws in manufacturing, and conditions in the environment. The aforesaid degradation factors cause water trees, electrical trees and partial discharge, and finally result into power cable failure. The nonlinear nature of a water tree results in harmonic generation in the AC loss current. The magnitude of the higher harmonics thus generated, depends on the amount of nonlinearity, therefore, amplitude and phase angel of the third harmonic current can be utilized to detect and quantify the degradation level. The main objective of this papers is to present a brief review on methods introduced in literature to utilize the third harmonic current as a diagnostic tool to identify and quantify the power cable degradation.

Harmonics distortion is a major arising issue in power networks. In almost every study done, the source of harmonics often referred to non-linear loads. In this study, the author concerntrates only on harmonics induced by synchronous generators at generation-end. The objective of paper is to provide a complete process review on implementing a practical and efficient technique to forecast triplen harmonics voltages and corresponding phase angles at every network busses. Real-time data from the 11-kV generation system at Gas District Cooling (GDC) distribution network in Universiti Teknologi PETRONAS (UTP) would be fed into the proposed algorithm for harmonic estimation and forecasting. Based on a thorough review on various methods of harmonics state estimation (HSE), neural networks (NN) method was suggested and studied to estimate and forecast the harmonic voltage vectors.

Triplen harmonics study for harmonics produced by salient pole synchronous generator is very important because their presence have caused communication line interference, damage to neutral earthing resistor etc. The purpose of this paper is to study the characteristics of triplen harmonics under balanced/unbalanced resistive/inductive loads, different generator neutral earthing resistor values and various transformer winding configurations. Lab scale salient pole synchronous generator is used for the experiment and third harmonic currents are recorded for analysis to represent triplen harmonics currents characteristics. Under balanced load, third harmonic current is inversely proportional to load impedance and neutral current is three times the phase current. During unbalanced load condition, the neutral current is lower than arithmetic sum of phase current due to different phase current magnitude and angle. The phase and neutral third harmonic currents magnitude is inversely proportional to generator NER resistance under balanced load. Transformer winding configurations under balanced load permit third harmonic current flowing through them in accordance to zero sequence network for the transformer apart from higher transformer reactive impedance at third harmonic. This study provides a very important input to mitigation method in reducing triplen harmonics currents propagation in the network.

Short term load forecasting (STLF) method is the basis of efficient operation for power system. It has an important role in planning and operation of power system. In this paper, a practical STLF using artificial neural network method (ANN) for Gas District Cooling (GDC) power plant of Universiti Teknologi PETRONAS (UTP) is presented. As a sole customer of GDC power plant, the load data from 2006 till 2009 are gathered and utilized for model developments. The developed models forecast electricity load for one week ahead. The paper proposes a method of a multilayer perceptron neural network and it is trained and simulated by using MATLAB. The models have been tested with the actual load data and perform relatively good results.

Load forecasting has an important role in planning and operations in power generation plant. Many new forecasting systems have been presented and proposed in recent years. Gas District Cooling (GDC) plant was built to supply electricity and chilled water for Universiti Teknologi PETRONAS (UTP). It operates on island operation during normal mode with utility company supply on hot standby mode. The plant has two generation units rated at 4.2 MW each, with a maximum generation capacity of 8.4 MW. In this paper, a practical short term load forecasting (STLF) method for UTP is presented. In the proposed method, a fuzzy logic approach was used and STLF model was designed based on UTP 2008 electricity demand data. The proposed model was tested with actual load data for January till June 2009 period. The test results show that the mean absolute percentage error of 4.59%.

As the demand for power increases, the need for harmonic state estimation (HSE) has been increasing as well. Harmonics, injected by the non-linear equipments along the distribution networks, causes several power quality issues. Therefore, HSE plays an important role in harmonics monitoring and control. Various HSE techniques and algorithms have been developed since 1989, which would be reviewed and discussed in this paper. The author outlines the role of artificial intelligence (AI) in the field and the process overview of neural network and also a hybrid algorithm which combines particle swarm optimization (PSO) and gradient descent (GD) to train the weights of neural network (NN).

Electricity supply to Universiti Teknologi PETRONAS (UTP) comes from gas district cooling (GDC) plant as a primary source of energy and utility company Tenaga Nasional Berhad (TNB) as a backup. With a maximum capacity of 8.4 MW which comes from 2 nos of gas turbine generators rated at 4.2 MW each, this work aims to forecast short term electricity demand of the plant. As a sole customer of the plant, UTP 2008 electricity demand data is being used as a basis to design a forecast model using Fuzzy Logic. With the forecast model, it will help GDC for pre-planned scheduling and maintenance of the plant and also as guidance for the daily operation of the plant. The proposed fuzzy logic model is applied to obtain one week forecast load demand data for GDC. The forecast accuracy is obtained and it is represented in mean absolute percentage error (MAPE).