Steady-state analysis of the impact of climate change on distribution transformer

Abstract

Climate change could cause several issues such as decreasing water availability, increasing intensity of storm events, flooding and sea level rise, increasing air, and water temperatures. One aspect of climate change is the increase in ambient temperature. According to, the average global surface temperature is expected to increase around 1.8°C to 4°C, while the average increase of global ambient temperature is predicted from 1.4°C to 5.8°C, in the periods of 1990 to 2100. Climate change can also affect distribution systems in terms of reliability and loadability. A 1°C rise in global temperature increases peak demand by 4.6%. In 2013, U.S. weather–related power outages may have reached 180 events per year. Further, climate change leads to high temperature, and many factors might change. An increase in ambient temperature leads to increase in transformer loading, which leads to a reduction of lifetime of transformers and low insulation value due to degradation of degree of polymerization. As ambient temperature and operation temperature increase can cause thermal aging of transformers, it is important to control a loaded transformer to mitigate aging effect. Thus, demand response is an important and effective feature of thermal management of a transformer. Multiple models are discussed and explained to obtain accurate results and a good prediction for the three factors: ambient temperature, operation temperature, and demand response. Therefore, IEEE standard C57.91-2011 is used for calculating thermal characteristics and the loss of life of distribution transformers. It also provides an example using rated parameters of a 25 MVA distribution transformer, real data of temperature, load available in the public domain for Fort Collins, Colorado, USA. Moreover, demand response is considered in this calculation in order to study the effect of changing load levels on the transformer insulation life and aging acceleration factor. Four scenarios of load levels will be applied as follow: pre-DR, 3%, 6% and 9% peak load reduction.