Predictability, constancy and contingency in electric load profiles

Electric load profile forecasting is among the most important tasks in power system operation. This task has been performed reasonably well with minimal disruption from renewables over the past decades. The expected high penetration of renewables in the system is challenging this classical task. Moreover, the blossom of demand side management programs warrants the necessity of load profile forecasting even for individual (residential as well as industrial) consumers. In this paper, we seek to define predictability in a rigorous way from an information theoretic perspective, which shed light on comparing the predictability between different kinds of loads. Then, we identify two separable components of predictability - constancy and contingency. We further exploit the key parameters in deciding the predictability, which challenge the commonly-held beliefs. For example, does a finer granularity imply a lower predictability? To what degree does the law of large numbers help improve the predictability?