The number of publications in demand forecasting of the energy supply chain augmented meaningfully due to the 2008 global financial crisis and its consequence on the global economy, mainly in energy supply chains. In spite of the fact that Industry 4.0 emerged during this period, its solutions and their impacts on energy demand forecasting are not covered by current reviews in the literature. This paper presents a comprehensive and up-to-date review of publications related to forecasting approaches of energy demand in the last two decades between 2000 and 2020 with an emphasis on Industry 4.0 influences and the state-of-the-art progress on this topic. A total of 267 publications are chosen and about 73 distinctive approaches of energy demand forecasting are discovered. Accordingly, among these approaches, there are eight methods with the most citations which include 56% of the total articles. Additionally, the forecasting methods are classified into traditional and intelligent methods and the most cited publications related to both are reviewed in detail. Furthermore, the advantages and disadvantages of both traditional and intelligent forecasting methods as well as research limitations and future researches are determined. The results from the literature review indicated that by employing intelligent forecasting methods, the errors and costs were reduced while these methods increase profitability.