It is hard to disagree that there is typically a strong correlation between some changes, for example, in prices, and a quantity demanded. Fan et al. (2019) discuss how changes in climate may have significant effects on electricity demand in China. According to the authors, since the electricity sector is rather sensitive to climate pattern modifications, the temperature may be considered the main factor influencing electricity demand (Fan et al., 2019).
The article focuses on exploring the current and evidence-based changes and their effects and forecasting the potential ones under three climate change scenarios. Overall, from 1995 to 2016, the demand for refrigeration and heating in the south became higher and lower respectfully. In the north, the situation is the opposite. As for the three scenarios, they are RCP 8.5, RCP4.5, and RCP2.6 (Fan et al., 2019, p. 11). These scenarios are different in predicted temperature and precipitation increases by 2100, the highest of which are +5.0 Co and +14% respectively (RCP 8.5) (Fan et al., 2019, p. 11). By that year, the electricity demand growth is expected to be “69.52 billion kWh, 222.74 billion kWh, and 518.58 billion kWh, representing 1.0%, 3.53%, and 8.53% of the total electricity consumption in China in 2017” (Fan et al., 2019, p. 18).
There are many changes that may have either a positive or negative effect on demand. The changes discussed in this paper are connected with the weather and climate modifications, which is a significant natural factor. Researchers predict global warming or the next ice age; that is why the electricity sector may meet an increased level of demand. People need electricity for their household appliances or heating systems (Fan et al., 2019). In case the temperature level drops or rises rapidly, it may be necessary, for example, to change the mode of the refrigerator to a cooler one, which will entail a rise in the demand for electricity.
Reference
Fan, J. L., Hu, J. W., & Zhang, X. (2019). Impacts of climate change on electricity demand in China: An empirical estimation based on panel data. Energy, 170, 1-25.