Using an agent-based modeling approach we study the temporal dynamics of consumer opinions regarding switching to dynamic electricity tariffs and the actual decisions to switch. We assume that the decision to switch is based on the unanimity of $\tau$ past opinions. The resulting model explains...

We show that incorporating the intra-day and inter-zone relationships of electricity prices in the Pennsylvania--New Jersey--Maryland (PJM) Interconnection improves the accuracy of short- and medium-term forecasts of average daily prices for a major PJM market hub -- the Dominion Hub in...

This paper proposes an agent-based modeling (ABM) approach to study the diffusion and adoption of dynamic electricity tariffs. We discuss the difference between opinions and decisions of electricity consumers regarding dynamic pricing. By means of a simple ABM, we provide a plausible explanation...

We examine possible accuracy gains from using factor models, quantile regression and forecast averaging for computing interval forecasts of electricity spot prices. We extend the Quantile Regression Averaging (QRA) approach of Nowotarski and Weron (2014) and use principal component analysis to...

Probabilistic load forecasting is becoming crucial in today's power systems planning and operations. We propose a novel methodology to compute interval forecasts of electricity demand, which applies a Quantile Regression Averaging (QRA) technique to a set of independent expert point forecasts....

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 show that incorporating the intra-day relationships of electricity prices improves the accuracy of forecasts of daily electricity spot prices. We use half-hourly data from the UK power market to model the spot prices directly (via ARX and Vector ARX models) and indirectly (via factor models)....

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

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....

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...