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The purpose of this study is to evaluate the reliability of the technique for estimating solar radiation in areas of rough topography and to detect the source of error and means for improvement.

Spatial data of the study area in the form of digital elevation model (DEM) coupled with geographic information system (GIS) were used to estimate the monthly solar radiation at locations with rough topography. The generated data were compared with measured data collected from all the selected locations using NASA data.

The results show that the variation in topographic parameters has a strong influence on the amount of solar radiation received by two close locations. However, the method performed well for solar radiation estimated in the areas of rough topography.

The proposed approach overestimates the monthly solar radiation as compared with NASA data due to the impact of topographic parameters accounted for by the model which are not accounted by conventional methods of measurements. This approach can be improved by incorporating the reflected component of radiation in the model used to estimate the solar radiation implemented in the GIS.

The approach of using GIS with DEM to estimate solar radiation enables to identify the spatial variability in solar radiation between two closest locations due to the influence of topographic parameters, and this will assist in proper energy planning and decision making for optimal areas of solar photovoltaic installation.

This study aims to propose a sensitivity-based methodology for the optimum accommodation of distributed generation (DG) units in meshed power networks with appropriate technologies. The effect of load variation is incorporated into the proposed methodology to identify the most trusted locations for DG placement.

The effectiveness of minimizing active power losses is considered a key criterion. A priority list comprising both sensitivity indexes and realistic indicators is deduced to rank the optimum sites for the placement of DG units. A sorting index for distinguishing the suitable DG type(s) for each candidate location is organized. Three common DG types are considered in this work. The modified IEEE 30-bus meshed system is chosen to perform the proposed methodology.

Results demonstrate that the obtained priority index can be used to achieve the best real loss minimization rates. Numerous load buses can be safely excluded as candidate locations using the proposed approach. Consequently, the methodology can minimize the computational process of diagnosing the optimum sites for DG accommodation.

The findings determine that instead of installing many DG units at various locations with one DG type, a few certain load buses can be used to accommodate more than one DG type and significantly reduce losses.

The paper aims to develop a CAD tool power electronics converters.

Integration of knowledge base techniques with OOP paradigm. Using Visual Basis class builder, 15 classes were built to form the kernel of the tool's KB.

A knowledge‐based CAD tool was developed to ease the design of power electronics converters. It can be considered a learning aid tool too.

The knowledge base of developed tool can be expanded to accommodate large number of topologies. The GUI can be also ameliorated to a better look and interaction process.

With proper enhancements, the purpose of the developed tool can be upgraded from educational one to industrial one.

Beside the methodology, the new thing in the paper is the specificity of the application of the tool (i.e. in power electronics).