Climate change, in particular temperature change, has an impact on the demand for heating and cooling. This paper explores the effect of gradually warming climate on the demand for heating and cooling in Seoul during 1995-2014 using an autoregressive distributed-lag model, a family of timeseries econometric multivariate regression model. The estimated results reveal that there are two peaks in Seoul's electricity consumption because cooling degree days (CDD) and heating degree days (HDD) are statistically highly significant. CDD’s regression coefficient for a short and long-run model is approximately twice bigger than HDD’s and the summer peak is more important in terms of electricity consumption in Seoul. Furthermore, there exists a long-run relationship between electricity consumption and the explanatory variables such as economic growth, CDD, HDD, seasonal dummies, and black out dummy.