Artificial neural networks | Regression with time series structure

Electricity price forecasting

Electricity price forecasting (EPF) is a branch of energy forecasting which focuses on predicting the spot and forward prices in wholesale electricity markets. Over the last 15 years electricity price forecasts have become a fundamental input to energy companies’ decision-making mechanisms at the corporate level. Since the early 1990s, the process of deregulation and the introduction of competitive electricity markets have been reshaping the landscape of the traditionally monopolistic and government-controlled power sectors. Throughout Europe, North America and Australia, electricity is now traded under market rules using spot and derivative contracts. However, electricity is a very special commodity: it is economically non-storable and power system stability requires a constant balance between production and consumption. At the same time, electricity demand depends on weather (temperature, wind speed, precipitation, etc.) and the intensity of business and everyday activities (on-peak vs. off-peak hours, weekdays vs. weekends, holidays, etc.). These unique characteristics lead to price dynamics not observed in any other market, exhibiting daily, weekly and often annual seasonality and abrupt, short-lived and generally unanticipated . Extreme price volatility, which can be up to two orders of magnitude higher than that of any other commodity or financial asset, has forced market participants to hedge not only volume but also price risk. Price forecasts from a few hours to a few months ahead have become of particular interest to power portfolio managers. A power market company able to forecast the volatile wholesale prices with a reasonable level of accuracy can adjust its bidding strategy and its own production or consumption schedule in order to reduce the risk or maximize the profits in day-ahead trading. A ballpark estimate of savings from a 1% reduction in the mean absolute percentage error (MAPE) of short-term price forecasts is $300,000 per year for a utility with 1GW peak load. Electricity price forecasting is the process of using mathematical models to predict what electricity prices will be in the future. (Wikipedia).

Electricity price forecasting
Video thumbnail

Interpreting Electricity Bills (1 of 3: Reading rates & costs)

More resources available at www.misterwootube.com

From playlist Applications of Measurement

Video thumbnail

How to Solar Power Your Home / House #6 - Monitoring devices to measure energy and save money

------------------------------ Click "Show more" ------------------------------------------- I take a look at several ways and devices to monitor and measure current, power and energy use / consumption. This can help guide you to save money on electricity or assist with planning and sizing

From playlist How to Solar Power your Home

Video thumbnail

Physics - E&M: Ch 41.1 Ohm's Law & Resistor Circuit Understood (32 of 42) What is Cost of kW in U.S?

Visit http://ilectureonline.com for more math and science lectures! In this video I will discuss how much does a kilowatt hour of electricity cost in the U.S. in Louisiana, Oklahoma, Washington, California, Hawaii, and the U.S. average for residential, commercial, and industrial use. Nex

From playlist PHYSICS 41.3 OHM'S LAW AND RESISTORS UNDERSTOOD

Video thumbnail

Electricity Chapter 4_5 Electric Potential.mov

Video 5 on electric potential and electric potential energy.

From playlist PHY1506

Video thumbnail

Ex: Find an Amount After a Percent Reduction (Energy Use)

This video explains how to solve a percent problem by determining an amount after a percentage decrease. http://mathispower4u.com

From playlist Percent Applications

Video thumbnail

Electricity Chapter 4_2 Electric Potential.mov

Video 2 on electric potential and electric potential energy.

From playlist PHY1506

Video thumbnail

Learn about Solar Energy and Solar Panel Installation...

Google Tech Talks September 12, 2007 ABSTRACT Learn about Solar Energy and Solar Panel Installation from an Industry Expert · Overview -- how solar works, benefits, technologies, market trends · Process for installing system · Key questions to ask & things to look for when considering

From playlist Energy and the Environment

Video thumbnail

17. (Yesterday's &) Today's Electric Power System

MIT 15.031J Energy Decisions, Markets, and Policies, Spring 2012 View the complete course: http://ocw.mit.edu/15-031JS12 Instructor: Richard Schmalensee License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 15.031J Energy Decisions, Markets, Policies, Spring 2012

Video thumbnail

Electric Power (3 of 3) Calculating the Cost of Electric Power

This video shows you how to calculate the cost of electric power usage by calculating the cost to pop popcorn. Electric power describes how fast electric potential energy is convert to other forms of energy such as heat, light and motion. Power is measured in watts. One watt is when one

From playlist DC Circuits; Resistors in Series and Parallel

Video thumbnail

Heath Winning - Climate action is a young person's game

Heath speaks about his work at ZEN Energy in data analysis and load forecasting, the opportunities for Australia in an era where the energy system is undergoing a rapid transition to renewables, and what young people can do to get behind that disruption and push. This was recorded as part

From playlist Metauni

Video thumbnail

Turning an Idea into a Data Driven Production System An Energy Load Forecasting Case Study - MATLAB

Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE We solve a wide range of problems in our daily lives that do not require excessive thinking, instead relying on data from past experiences. Somewhere in our brain we use data-

From playlist MATLAB and Simulink Conference Talks

Video thumbnail

Fourth SIAM Activity Group on FME Virtual Talk

Title: Panel Discussion on Energy Markets Abstract: The aim is to discuss recent events in energy/electricity/commodity markets, such as negative prices, as well as related mathematical modeling challenges. Moderator: Ronnie Sircar, Operations Research and Financial Engineering, Princeto

From playlist SIAM Activity Group on FME Virtual Talk Series

Video thumbnail

Operational Risk Financialization of Electricity Under Stochasticity

SIAM Activity Group on FME Virtual Talk Series Join us for a series of online talks on topics related to mathematical finance and engineering and running every two weeks until further notice. The series is organized by the SIAM Activity Group on Financial Mathematics and Engineering. Spea

From playlist SIAM Activity Group on FME Virtual Talk Series

Video thumbnail

Boost Your Data Career with Predictive Analytics! Learn How ? | Edureka

Watch Sample Recording : http://www.edureka.co/about-advanced-predictive-modelling-in-r?utm_source=youtube&utm_medium=webinar&utm_campaign=apmr-19-03-2015 Predictive modelling leverages statistics to predict outcomes.[1] Most often the event one wants to predict is in the future, but pred

From playlist Webinars by Edureka!

Video thumbnail

Key New Mathematica Features for SystemModeler

Speaker: Malte Lenz This talk shows how new Mathematica and Wolfram Language features can be used to enhance the design and analysis workflow for SystemModeler users. For more training resources, please visit: http://www.wolfram.com/Training/

From playlist Wolfram SystemModeler Virtual Conference 2014

Video thumbnail

Reinventing Fire - Amory Lovins

Amory Lovins Rocky Mountain Institute September 28, 2013 More videos on http://video.ias.edu

From playlist Dreams of Earth and Sky

Video thumbnail

Lecture7. Time series forecasting

Data Science for Business. Lecture 7 slides: https://drive.google.com/file/d/17Fn0uhOVs4I8T1ut2BWM4OY1a8M9nzMk/view?usp=sharing

From playlist Data Science for Business, 2022

Video thumbnail

Electricity Chapter 4_3 Electric Potential.mov

Video 3 on electric potential and electric potential energy.

From playlist PHY1506

Related pages

Shrinkage (statistics) | Autoregressive–moving-average model | Temperature | Percentile | Feature selection | Statistics | Exponential smoothing | Support vector machine | Autoregressive model | Prediction interval | Risk management | Autoregressive fractionally integrated moving average | Marginal distribution | Jump diffusion | Game theory | Econometric model | Quantile regression | Regularization (mathematics) | Autoregressive conditional heteroskedasticity | Committee machine | Artificial intelligence | Volatility (finance) | Quantile regression averaging | Lasso (statistics) | Consensus forecast | Stepwise regression | Mathematical model | Mean absolute percentage error | Artificial neural network | Ridge regression | Probabilistic forecasting | Fahrenheit | Agent-based model | Degree (temperature) | Autoregressive integrated moving average | Econometrics