Improved Loaded Quality Factor of Cavity Resonators with Cross lris Coupling

The performance of circular, rectangular and cross irises for the coupling of microwave power to rectangular waveguide cavity resonators is discussed. For the measurement of complex permittivity of materials using cavity perturbation techniques, rectangular cavities with high Q-factors are required. Compared to the conventional rectangular and circular irises, the cross Iris coupling structure provides very high loaded quality factor for all the resonant frequencies. The proposes cross iris coupling structure enhances the accuracy of complex permittivity measurements.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year