Total assessment and optimization of telecommunication sectors by an integrated multivariate approach

290-298This paper presents an integrated multivariate approach (IMA) for total assessment, ranking and optimization of telecommunication sectors based on standard indicators identified by International Telecommunication Union (ITU). The integrted approach is based on Data Envelopment Analysis (DEA) and Principal Component Analysis (PCA) and Numerical Taxonomy. Results of DEA are verified by PCA and Numerical Taxonomy by Spearman correlation technique. Indicators are catagorized as telephone network size, other services, quality of service, traffic, tariffs, staff, demography, economy, information technology, broadcasting and mobile services. To present applicability of IMA, data for 2003 of 27 developed and developing countries are used. A total of 9 indicators are considered, out of which 4 are inputs and 5 are outputs. The results identifies the most efficient inputs or outputs which can aid management in overal assessment and optimization. This is the first study that presents an IMA for total assessment, improvement and optimization of the telecommunication sectors. The integrated approach of this study may be easily used for performance assessment and optimization of other telecommunication sectors

Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator

Improvement of microgrid dynamic performance under fault circumstances using ANFIS for fast varying solar radiation and fuzzy logic controller for wind system

The microgrid (MG) technology integrates distributed generations, energy storage elements and loads. In this paper, dynamic performance enhancement of an MG consisting of wind turbine was investigated using permanent magnet synchronous generation (PMSG), photovoltaic (PV), microturbine generation (MTG) systems and flywheel under different circumstances. In order to maximize the output of solar arrays, maximum power point tracking (MPPT) technique was used by an adaptive neuro-fuzzy inference system (ANFIS); also, control of turbine output power in high speed winds was achieved using pitch angle control technic by fuzzy logic. For tracking the maximum point, the proposed ANFIS was trained by the optimum values. The simulation results showed that the ANFIS controller of grid-connected mode could easily meet the load demand with less fluctuation around the maximum power point. Moreover, pitch angle controller, which was based on fuzzy logic with wind speed and active power as the inputs, could have faster responses, thereby leading to flatter power curves, enhancement of the dynamic performance of wind turbine and prevention of both frazzle and mechanical damages to PMSG. The thorough wind power generation system, PV system, MTG, flywheel and power electronic converter interface were proposed by Rusing Mat-lab/Simulink

Discontinuous Feedback Linearization of an Electrically Driven Fast Robot Manipulator

A multivariable discontinuous feedback linearization approach is proposed to position control of an electrically driven fast robot manipulator. A desired performance is achieved by selecting a useful controller and suitable sampling rate and considering saturation for actuators. There is a high flexibility to apply the proposed control approach on different electrically driven manipulators. The control approach can guarantee the stability and satisfactory tracking performance. A PUMA 560 robot driven by geared permanent magnet dc motors is simulated. The simulation results show a desired performance for control system under technical specifications

Performance assessment and optimization of thermal power plants by DEA BCC and multivariate analysis

860-872This study presents an integrated Data Envelopement Analysis (DEA) methodology using Banker Charnes Cooper (BCC) input oriented model for assessment and optimization of conventional thermal power plants (gas, steam and combined cycles). Installed capacity, fuel consumption, labor cost, internal power, forced outage hours and operating hours are used as input parameters whereas total power generation is used as output parameter. Moreover, 40 power plants in Iran were used as decision-making units and DEA-BCC model was used to assess their efficiency and rank during 1997-2000. Principal Component Analysis (PCA) and Numerical Taxonomy (NT) together with Spearman correlation technique were used to verify and validate the findings of DEA-BCC approach. In addition, all regional power plants have been ranked, assessed and optimized in comparison with all thermal power plants