Energy Forecasting: Past, Present, and Future
ثبت نشده
چکیده
While other industries have some form of inventory to store and buffer their products and services, electricity cannot be massively stored using today’s technologies. As a result, it has to be generated and delivered for immediate consumption; in short, utilities have to balance supply and demand every moment. Storage limitations and societal dependence on electricity lead to several interesting features of energy forecasting, including complex seasonal patterns, 24/7 data collection across the grid, and needs for precise accuracy.
منابع مشابه
Using Methods Based on Neural Networks to Predict and Manage Diseases (A Case Study of Forecasting the Trend of Corona Disease)
Aim and background: Forecasting methods are used in various fields; one of the most important fields is the field of health systems. This study aimed to use the Artificial Neural Network (ANN) method in forecasting Corona patients in Iran. Method: The present study is descriptive and analytical of a comparative type that uses past information to predict the future, the time series of Corona in...
متن کاملDifferent Methods of Long-Term Electric Load Demand Forecasting a Comprehensive Review
Long-term demand forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. One of the primary tasks of an electric utility accurately predicts load demand requirements at all times, especially for long-term. Based on the outcome of such forecasts, utilities coordinate their resources to meet the forecasted demand using a least-co...
متن کاملFORECASTING TRANSPORT ENERGY DEMAND IN IRAN USING META-HEURISTIC ALGORITHMS
This paper presents application of an improved Harmony Search (HS) technique and Charged System Search algorithm (CSS) to estimate transport energy demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast transport energy demand in Iran. These models are developed to estimate the future energy demands based on pop...
متن کاملEmpirical prediction intervals improve energy forecasting.
Hundreds of organizations and analysts use energy projections, such as those contained in the US Energy Information Administration (EIA)'s Annual Energy Outlook (AEO), for investment and policy decisions. Retrospective analyses of past AEO projections have shown that observed values can differ from the projection by several hundred percent, and thus a thorough treatment of uncertainty is essent...
متن کاملThree Approaches to Time Series Forecasting of Petroleum Demand in OECD Countries
Petroleum (crude oil) is one of the most important resources of energy and its demand and consumption is growing while it is a non-renewable energy resource. Hence forecasting of its demand is necessary to plan appropriate strategies for managing future requirements. In this paper, three types of time series methods including univariate Seasonal ARIMA, Winters forecasting and Transfer Function-...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014