Journal of Advanced Materials in Engineering (Esteghlal)

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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 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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Fe-Co alloys have unique magnetic applications. Fe50Co50 alloy has the highest saturation magnetization value among Fe-Co alloys. Moreover, the introduction of Si into Fe can result in a decrease of magnetic anisotropy. In this study, in order to utilize combined advantages of Si and Co, the effect of adding 10 and 20 at.% Si on the microstructural and magnetic properties of Fe65Co35 alloy was investigated. For this purpose, initial powder mixtures with specific compositions were milled by means of planetary ball mill for different milling times. Microstructural properties and morphology of the obtained powders were analyzed by X-ray diffraction analysis (XRD) and scanning electron microscope (SEM). Also, magnetic properties of the samples were determined by means of vibration sample magnetometer (VSM). The results showed that the crystallite size was finer and more uniform and lattice strain was decreased slightly for longer milling times. Observations indicated that the addition of Si to the alloys leads to finer particles. The results also showed that increasing the Si content increases the reduction rate of lattice parameter and coercivity.

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Magnesium-manganese ferrite nanopowders (Mg_xMn_1-xFe₂O₄, x=0.0 up to 1 with step 0.2) were prepared by coprecipitation method. The as-prepared samples were pressed with hydrolic press to form a pellet and were sintered in 900, 1050 and 1250˚C. Scanning Tunneling Microscope (STM) images showed the particle size of powders about 17 nm. The X-ray patterns confirmed the formation of cubic single phase spinel structure in samples sintered at 1250˚C. Substituting Mg²⁺ with Mn²⁺ in these samples, the lattice parameter decreased from 8.49 to 8.35Å and magnetization saturation decreased from 74.7 to 21.2emu/g. Also, coercity (H_C ) increased from 5 to 23Oe and Curie temperature (T_C ) increased from 269 to 392˚C. Samples with x= 0.2, 0.4, 0.6 sintered at 1250 ˚C, because of their magnetic properties, can be recommended for hyperthermia applications and for phase shifters.

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