چكيده به لاتين
Depreciated assets are one of the most important and influential parts of the indicators used to check the reliability and reliability of electricity distribution networks. It has been one of the main concerns of electricity distribution companies and distribution regulators. To avoid creating risk in the companies and to ensure their encouragement to improve the reliability of the distribution system, also the electricity distribution companies should calculate the optimization of worn assets with approximation and low error. Several factors, including asset life, geographic factors, facilities in electricity distribution networks, culture of dealing with facilities in the network, urban planning, etc. affect the amount of aging process (wear and tear) in assets. Considering all these factors, it is practically impossible to achieve the best possible condition for depreciated assets. Also, the insufficient investment of electricity distribution companies in the past years is an important factor in the aging of assets and determining the level of failure. On the other hand, the non-investment of electricity distribution companies in the field of depreciated assets has increased the depreciation of assets. In this thesis, 4 models are presented to calculate and estimate the depreciation time of assets in the electricity distribution network, and the effects of depreciation on this index are investigated. In the first model, we start by considering the value of λ as a constant in the network of electricity distribution companies. In the second part of the model, we continue the modeling process by considering λ as a variable for assets. In the third part, we observe the full costs of reliability, including the number of crews. We examine the geographical conditions and... and in the last part we examine the condition of the assets in different lifetimes with the help of the Poisson distribution function. In this research, the calculation and model for optimizing the replacement of worn out assets has been presented, which can help the regulator in allocating budget to electricity distribution companies. Also, with the presented models, it is possible to guarantee the equipment, the possibility of more accurate evaluation of the manufacturers according to the life of the asset, the determination of the depreciation life of the assets, the possibility of accurate calculation of the economic effects of high quality assets, etc. These presented models can help the user in the qualitative assessment of the manufacturers and can determine the warranty policy and insurance of products and sales for the manufacturers so that it can be a criterion for optimal evaluation. In order to validate the presented models, information from Iran's electricity distribution companies has been used and the results have been presented.
