This paper introduces the concept of sister models, and proposes a sister model based load forecast combination method to enhance the point forecasting accuracy. Using the data from the Global Energy Forecasting Competition 2014, we create a case study with 4 sister forecasts from 4 sister...

Although combining forecasts is well-known to be an effective approach to improving forecast accuracy, the literature and case studies on combining load forecasts are very limited. In this paper, we investigate the performance of combining so-called sister load forecasts with eight methods:...

In this paper we investigate whether considering the fine structure of half-hourly electricity prices, the market closing prices of fundamentals (natural gas, coal and CO2) and the system-wide demand can lead to significantly more accurate short- and mid-term forecasts of APX UK baseload prices....

Majority of the load forecasting literature has been on point forecasting, which provides the expected value for each step throughout the forecast horizon. In the smart grid era, the electricity demand is more active and less predictable than ever before. As a result, probabilistic load...

We examine convenience yields in the EU-wide CO2 emissions trading scheme (EU-ETS) during the first Kyoto commitment period (2008-2012). We find that the market has changed from initial backwardation to contango with significantly negative convenience yields in futures contracts. We further...

This paper provides detailed information on Team Poland’s approach in the electricity price forecasting track of GEFCom2014. A new hybrid model is proposed, consisting of four major blocks: point forecasting, pre-filtering, quantile regression modeling and post-processing. This universal model...

Energy forecasting is one of those areas of great importance to electric grid that gets little attention - even from power industry insiders. But you need to know how to make the best of your forecasting process. Here are 13 tips to get you started.

Using an agent-based modeling approach we show how personal attributes, like conformity or indifference, impact opinions of individual electricity consumers regarding innovative dynamic tariff programs. We also examine the influence of advertising, discomfort of usage and the expectations of...

We evaluate a recently proposed method for constructing prediction intervals, which utilizes the concept of quantile regression (QR) and a pool of point forecasts of different time series models.We find that in terms of interval forecasting of Nord Pool day-ahead prices the new QR-based approach...

In the paper, Structural Vector Autoregressive models (SVAR) are used to identify fundamental and speculative shocks, in the UK electricity market. The structural shocks are identified via short run restrictions, which are imposed on the matrix of instantaneous effects. In the research, two main...