Yasin Khan

Experimental study and design of smart energy meter for the smart grid

The demand for energy is increasing as a result of the growth in both population and industrial development. To improve the energy efficiency, consumers need to be more aware of their energy consumption. In recent years, utilities have started developing new electric energy meters which are known as smart meters. A smart meter is a digital energy meter that measures the consumption of electrical energy and provides other additional information as compared to the traditional energy meter. The aim is to provide the consumer and supplier an easy way to monitor the energy. Smart meters are considered a key component of the smart grid as these will allow more interactivity between the consumers and the provider. Smart meters will enable two-way and real-time communication between the consumers and the provider. Considering the increase of electricity demand in Saudi Arabia, smart meters can decrease the overall energy consumption. This paper presents the development of a GSM and ZigBee based smart meter. This meter can measure the energy and send the information to the service provider, who can store this information and notify the consumer through SMS messages or through the internet.

Utilization of artificial neural network for the estimation of size and position of metallic particle adhering to spacer in GIS

The defects caused by the presence of metallic particles are the most frequent threats in Gas-Insulated Substation (GIS). These particles can move freely in the GIS enclosure and thereby when they come in the vicinity of spacers they can adhere to the solid spacer surface due to electrostatic forces resulting in the initiation of partial discharges (PDs) affecting the GIS reliability. The magnitude and frequency of these PDs depend among others on the size and position of particles. Thus the knowledge of the size and position of contaminating particles and its PD characteristics is essential for the improvement of the reliability of such equipment. This paper is aimed at the use of the Back-Propagation Artificial Neural Network (BP-ANN) technique for recognizing the PD patterns to estimate the particle size (length) and position on the spacer surface in a simulated GIS. The PD patterns were characterized by a number of statistical operators describing the shapes of distributions of the PD signals acquired from the measurements carried out using IEC 60270 method. In developing the BP-ANN, some parameters were varied to find the most optimal network. The results show that the best-developed ANN in this study is able to recognize various PD patterns in the employed GIS model and is able to estimate particle length and position on the spacer surface at different SF6 pressures. The achieved accuracy in detecting the size and location of particle was about 92%. Thus, the proposed method constitutes a helpful tool in improving the reliability of GIS as well as for diagnosis.

Optimized pit configuration for efficient grounding of the power system in high resistivity soils using low resistivity materials

In an electrical power system, the integrity of the grounding system is very important to maintain a reference point of potential for equipment and personnel safety, to provide a discharge point for lightning currents as well as to prevent excessive high voltages on the power system. Therefore, to maintain ground system effectiveness, proper design, installation and testing of grounding system is required. In Saudi Arabia, the weather is dry and the soil resistivity varies significantly from area to area because the geodetic terrain varies from sea shore to the arid desert and dry mountains. In most of the inland desert areas, the soil resistivity is significantly high and it is difficult to get the low earth resistance with conventional methods. Therefore to get a low value of grounding resistance, a good design of the grounding pit is necessary which can be achieved by using low resistivity materials. When such materials are used, it is important to optimize the pit design in order to have an economical and efficient grounding system. This paper presents a novel technique for finding the optimum size of grounding pits commonly used in the electrical power systems. With this technique, we can easily find out an optimized pit design that can effectively reduce the grounding resistance to an acceptable value. The obtained results can be readily used by engineers to obtain a good earth pit configuration for efficient grounding of the power system in the high resistivity soils by using low resistivity materials (LRM).

Loss and Recovery of Hydrophobicity of EPDM Insulators in Simulated Arid Desert Environment

Electrical insulators form a very important component of high voltage electric power networks. Along with the traditional insulators i.e. glass and porcelain, etc. presently the polymeric insulators are also used world widely. These polymeric insulators are very sensitive to various environmental parameters such temperature, environmental pollution, UV-radiations, etc. which seriously effect their electrical, chemical and hydrophobic properties. The UV radiation level in the central region of Saudi Arabia is high as compared to the IEC standard for the accelerated aging of the composite insulators. Commonly used suspension type of composite EPDM (ethylene propylene diene monomer) insulator was subjected to accelerated stress aging as per modified IEC standard simulating the inland arid deserts atmospheric condition and also as per IEC-61109 standard. The hydrophobic characteristics were studied by measuring the contact angle along the insulator surface before and after the accelerated aging of the samples. It was found that EPDM insulator loses it hydrophobic properties more proportional to the intensity of UV radiations and its rate of recovery is very low as compared to Silicone Rubber insulator. The effect of water salinity and drop size on the contact angle characteristics was also investigated.

Performance of Composite Insulators in Simulated Environmental Conditions Related to Central Region of Saudi-Arabia

High voltage composite insulators are being accepted increasingly for use in outdoor installations. This research work aims at assessing the experimental performance of the two types of polymeric composite insulators being prepared for use in high voltage overhead transmission and distribution networks. Experimental investigations were carried out to study the effect of ultraviolet radiations as well as heat on the performance of composite insulators simulating the environmental conditions of Central region of Saudi Arabia. To achieve this objective, modified accelerated aging test was performed as per IEC standard 61109 to simulate the field aging of the polymeric insulators and compared various electrical and optical tests results of the laboratory aged insulators with new ones. The results will help in assessing the performance and suitability of polymeric insulators for their applications in Saudi Arabia

Performance of inverter fed induction motor under open circuit DC link capacitor

Induction motors are widely used in industry due to their promising performance. Majority of induction motors are used in inverter based drives in industrial setups. Efforts are being put in the fault analysis of induction motors. Most of the analysis available in literature discusses the failure of electronic components like power MOSFET, optocoupler failure, failure of pulse generation card etc. This research work is a continuation of fault analysis studies of an inverter fed induction motor drives under different fault conditions. This paper presents the effect of dc link capacitor open circuit on the performance of inverter fed induction motor. Effect on stator current, inverter output, the speed and torque of the motor are particularly studied in this paper. The faults in the DC link is generally not that common but there is always a chance of capacitor failure. The simulated results presented in this paper can augment the efforts for the reliability enhancement of induction motor drives.

Efficient use of low resistivity material for grounding resistance reduction in high soil resistivity areas

Power system is generally protected from lightning strokes by surge arresters which are provided with a low earth resistance connection to enable the large currents encountered to be effectively discharged to the general mass of earth. This offers some resistance to the flow of current which depends on electrode arrangements as well as the surrounding soil resistivity. In Saudi Arabia, the soil resistivity varies in a large range because the geodetic terrain varies from sea shore to the arid desert and dry mountains. Therefore, getting an acceptable low value of grounding resistance is very important in those areas where the soil resistivity is very high. This can be achieved by efficient use of low resistivity material (LRM). When the LRM is used in too high volume, it does not reduce the grounding resistance in a corresponding manner and thus may not be economical and effective. This paper studies the effect of different design parameters of the earthing pit on the grounding resistance and finally a general approach for finding the optimized pit design is suggested that can effectively reduce the grounding resistance to an acceptable lower value. The suggested method can be readily used by engineers to obtain a good earthing pit configuration for efficient grounding of the power system components in high resistivity soils.

Emission constrained economic dispatch for hybrid energy system in the presence of distributed generation and energy storage

Due to the concerns about the increasing price of fossil fuels, greenhouse gas emissions and energy supply sustainability, power utilities are being forced to examine their operational policies. The use of hybrid power system and the minimization of overall generation cost of such systems employing distributed generation and distributed energy storage facilities with limited amounts of pollutants emission is the main objective of the optimization carried out in this work. The analysis considers the generation cost of thermal, renewable and storage based hybrid power plants along with the cost paid for health and environmental damages caused by the emissions. The analysis is carried out using MATLAB simulations with sequential quadratic programming algorithm. It is shown that the actual cost of fossil fuel based electricity generation is higher than that of the renewable power generation if the hidden costs of conventional generation related to environmental impacts are considered as well.

Effect of Gas Flowrate on Nucleation Mechanism of MWCNTs for a Compound Catalyst

Activation of the catalyst particles during a CVD process can be anticipated from the carbon feeding rate. In this study, Fe2O3/Al2O3 catalyst was synthesized with uniformly dispersed iron over alumina support for onward production of multiwalled carbon nanotubes (MWCNTs) in a fluidized bed chemical CVD reactor. The effect of the ethylene flowrate on catalytic activity of the compound catalyst and morphology of the as-grown MWCNTs was also investigated in this study. The dispersed active phases of the catalyst and optimized gas flowrate helped in improving the tube morphology and prevented the aggregation of the as-grown MWCNTs. The flowrates, below 100 sccm, did not provide sufficient reactants to interact with the catalyst for production of defect-free CNT structures. Above 100 sccm, concentration of the carbon precursor did not show notable influence on decomposition rate of the gas molecules. The most promising results on growth and structural properties of MWCNTs were gained at ethylene flowrate of 100 sccm. At this flowrate, the ratio of and intensity peaks () was deliberated about 1.40, which indicates the growth of graphitic structures of MWCNTs.

Partial discharge analysis using PCA and ANN for the estimation of size and position of metallic particle adhering to spacer in Gas-Insulated System

The presence of metallic particles can adversely affect the reliability of Gas-Insulated Substation (GIS) by initiating partial discharges (PDs). Therefore, the investigation of PD characteristics and particle size and position on the spacer surface are the significant steps toward the reliability improvement of the GIS equipments. This paper presents the use of Back-Propagation Artificial Neural Network (BP-ANN) technique supplemented with Principal Component Analysis (PCA) as the PD pattern recognition tools for the estimation of the particle size (length) and position on the spacer surface in a simulated GIS. PD features acquisition was performed by collecting their fingerprints from the measurements carried out using IEC 60270 method. The role of PCA is to reduce the dimension of the collected PD fingerprint data. The obtained results show that PCA can significantly improve the BP-ANN performance in terms of execution time. Without PCA, 88% and 92% accuracies can be achieved when BP-ANN was implemented with 1 and 2 hidden layers, respectively. With the integration of PCA, execution times were greatly reduced while retaining fairly high accuracy, i.e. 88% and 88%. Thus the proposed method is a contribution in development of the tool for improving the reliability of GIS.