تحریم خمر - طب جدید كے تناظر میں

It has been held since ages that wine is a panacea for mankind in the realm of medicine. Moreover, it is touted with emphasis that it is a great source of mental and physical solace and satisfaction and for this very reason masses in the days of ignorance, in general, would have it with relish for solace and satisfaction. Even in the contemporary advanced times, it is believed in general, that wine is the source of various medical benefits coupled with the belief that wine releases tension and stress. Under the same impression, wine is drunk, with relish in Europe and America down to this day. Modern medical science has proved all these nations as categorically wrong and baseless and has set forth that all these notions about wine are based on assumptions and abstractions with nothing concrete and solid. In the assay under consideration, the harmful and baneful influence and effects of wine have been brought under the lime light and proved, in the light of the experiments of the medical scientists, that no medical benefits, whatsoever, be derived from drinking wine rather it has detrimental impacts and that it creates mental unrest instability rather than providing the drinker with solace, ease and satisfaction

Impact of Load Modeling on Dg Integrated Distribution Systems

Renewable energy based Distributed Generation (DG) resources are crucial for sustainable energy supply infrastructure as they are non-polluting and inexhaustible. The uncertainties associated with DG resources may cause distinct economic and technical challenges which require comprehensive investigation to facilitate their integration in Distribution System (DS). Generally, DG planning studies are conducted while assuming constant generation and load models. However, such assumptions may result in misleading and inconsistent values for voltage profile, loss reduction, payback period, deferral values, and other relevant calculations.Therefore, to achieve accurate and realistic results, it is necessary to consider variations associated with generation and load. This thesis presents time varying load modeling and probabilistic solar irradiance modeling techniques and investigates their impact on Photovoltaic (PV) based DG planning. A novel Beta distribution based probabilistic generation model is proposed for solar irradiance uncertainty modeling to compute the hourly output power values produced by PV based DG. The beta distribution parameters are found by assuming the variations of irradiance patterns at consecutive time steps. Subsequently, the proposed model is employed to generate various solar irradiance generation scenarios. Then, a time varying load modeling approach is presented for PV based DG planning.Five different types of time varying load models (i.e. residential, commercial, industrial, mixed and constant) are considered. These loads are modeled by combining the time varying characteristics of residential, commercial and industrial loads with the voltage-dependent load model while assuming suitable voltage exponents. The application of these load models make the PV based DG integration more realistic as compared to the conventional model. Furthermore, a methodology has been developed to determine intermittent DG allocation for DS while considering varying load and generation. The objective is to minimize the multiobjective optimization function which involves voltage deviation, active and reactive power loss indices. Finally, the impact of time varying load modeling approach on DG integrated DS performance has been investigated. The proposed DG planning framework has been validated on IEEE 33-bus and 69-bus standard distribution test systems in MATLAB environment. A comparative assessment of different impact indices, penetration level, active and reactive power intake, active and reactive power loss and MVA support offered by the installation of PV based DG for different time varying load models has been performed. The results demonstrate that the proposed generation model is suitable for solar irradiance modeling. Moreover, time varying load modelling approach has a significant impact on DS planning studies under uncertain scenario.