Journal of Advanced Materials in Engineering (Esteghlal)

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In this article, an effective method to control a power system during emergency conditions is presented. Based on Fuzzy Linear Programming (FLP), a new technique is developed to solve the Load Shedding and Generation Reallocation (LSGR) optimization Problem. The objective function consists of terms of load curtailments and deviations in generation schedules. The constraints are power system variables limitations. The objective function and constraints coefficients are uncertain, thus it is more appropriate to use fuzzy linear programming. Considering the network frequency as an essential variable, and using the electrical load model, a fuzzy environment is prepared to solve more realistically and successfully the LSGR optimization problem. The results of various cases of fuzzy and crisp modes of the problem are demonstrated. It will be observed that the application of the FLP on one hand, will provide a more realistic model of power systems, and on the other hand, will cause a reduction in the values of the objective function.

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This paper deals with the design and evaluation of a robust controller for static VAR compensator (SVC) in remote industrial power systems to enhance the voltage profile for three-phase single cage induction motor (SCIM) loads. The controller design is based on H∞ theory to deal with uncertainties arising in industrial network modelling. The performance of the H∞ controller has been evaluated extensively through non-linear time domain simulation. It is concluded that the robust controller (RSVC) enhances the voltage profile for SCIM loads compared with the optimal (OSVC) type which consists of optimal state feedback (LQR).

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Load modeling is widely used in power system studies. Two types of modeling, namely, static and dynamic, are employed. The current industrial practice is the static modeling. Static modelss are algebraic equations of active and reactive power changes in terms of voltage and frequency deviations. In this paper, a component based on static modeling is employed in which the aggregate model is derived based on the sensitivity coefficients and participation factors of load components. As an induction motor comprises a significant portion of industrial loads, Artificial Neural Network (ANN) is employed to derive its static model readily from nameplate data as accurately as possible.

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In order to evaluate the performance of biofilter for H2S removal from contaminated air, a 120×14 cm column biofilter was constructed using clear polyacrylic material in conjunction with H2S production and control systems. The column was divided into four stages using perforated plates. The column was packed with a mixture of mushroom compost and snail shell (4:1). The performance of biofilter was evaluated during 4 months of operation under various flow rates and H2S concentrations in ambient temperature. According to the results, the removal effeciency of H2S in polluted air for concentrations of up to 150 ppm, average temperature of 26.9°C and under flow rates of 6 and 12 l.min-1 was more than 95% the results for average temperature of 20.5°C and the flow rates of 19.5 and 26 l.min-1 but constant H2S concentration was more than 85%. The maximum removal rate (Vm) was measured as 0.075 g S/kg-dry compost.h and average saturation constant (Ks) was 32.5 ppm

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Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determined by a sufficiently rapid and precise method. In this paper, a new algorithm based on assigning a vector to each power system bus is presented. These vectors indicate buses conditions from the viewpoint of voltage stability. In this new method, using the clustering methods such as kohonen neural network, fuzzy C-Means algorithm and fuzzy kohonen algorithm, voltage control areas are determined The proposed method has advantages such as determining PV and PQ buses which belong to the weak area simultanously, under all operating conditions and without a need to system model. Also by comparing the results of applying clustering methods, it has been observed that, due to simplicity of implementation and precision of the results, the two dimensional kohonen neural network is a more suitable tool for clustering power system to voltage control areas than the fuzzy C-Means and fuzzy kohonen methods. Keywords: Voltage stability, Voltage weak area, Voltage control area, Corrective control, Pattern recognition, Kohonen neural network, Fuzzy C-Means algorithm, Fuzzy Kohonen algorithm.

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In this paper, two algorithms have been developed for allocation and size determination of Active Power Filters (APF) in power systems. In the first algorithm, the objective is to minimize harmonic voltage distortion. The objective in the second algorithm is to minimize the new APF injection currents while satisfying harmonic standards. Genetic algorithm is proposed for these two optimization problems. The simulation results for an 18-bus system show the effectiveness of the genetic algorithm for these two optimization problems. Keywords: Genetic Algorithm, Active Power Filter, Harmonics, Allocation, Optimization

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In a de-regulated open access environment, reactive power is one of the ancillary services which must be provided by an Independent System Operator (ISO). In this paper, a new algorithm is proposed in which reactive power resources are initially so tuned that optimum security in terms of voltage profile and voltage stability are achieved while at the same time, the system losses are minimized. The resulting optimization case is solved as an Extended Multi-objective Optimal Power Flow (EMOPF) problem using Lexico Graphic Method (LGM). Thereafter, using the concept of Fair Resource Allocation (FRA), the reactive powers generated are distributed among existing transactions so that the costs incurred are properly and fairly recovered. The algorithm is successfully tested on a typical power system. Keywords: Reactive Power, Reactive Power Management, Reactive Power Pricing, Voltage Profile, Voltage Stability, Deregulated Environment, Open Access

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Generation Expansion Planning (GEP) is one of major modules of power system planning studies, normally performed for the nex 10-30 years horizon. The current industrial practices are to find the generation requirements based on a nodal analysis. In this way, the allocations are not determined and subequent studies are required to find the exact locations which as decomposed from the earlier stage, may result in non-optimum solution. A new approach is proposed in this paper in which, based on dynamic programming and sensitivity factors, GEP is performed with due to consideration of transmission system effects. In this way, the allocations of justified generation plants are also determined. The results for Iranian Power Grid for the years 2011 to 2021 are demonstracted.

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In the present investigation, spherical nanoparticles of nickel ferrite with uniform structure were successfully produced by hydrothermal method in the presence of polyethylene glycol (PEG) as a polymeric surfactant at 180°C for 12 hour aging time and the effects of the synthesis time, temperature and surfactant were investigated. According to the X-ray analysis, conversion of nickel oxide and hematite to nickel ferrite was a way to produce NiFe2O4. At 140‌°C, agglomerated particles without specific shape were formed, but at 180°C particles were homogenous with spherical shape. Saturation magnetization increased by increasing the hydrothermal process aging time.