In this paper we present an analysis of the results of a study into wholesale (spot) electricity price forecasting with Support Vector Machines (SVM) utilising past price and demand data and Projected Assessment of System Adequacy (PASA) data. The forecasting accuracy was evaluated using Australian National Electricity Market (NEM), New South Wales regional data over the year 2002. The inclusio...

Sums of Lévy-driven Ornstein-Uhlenbeck processes seem appropriate for modelling electricity spot price data. In this paper we present a new estimation method with particular emphasis on capturing the high peaks, which is one of the stylized features of such data. After introducing our method we show it at work for the EEX Phelix Base electricity price index. We also present a small simulation s...

This paper reports on work the Consortium for Electric Reliability Technology Solutions (CERTS) has been pursuing to hasten the arrival of meaningful load participation in competitive electricity markets. The activities include: experimental economic analysis of the effect of price responsive load in reducing market prices and price volatility; assessments of emerging demand response programs a...

The European Emissions Trading Scheme (ETS) limits CO2 emissions from covered sectors, especially electricity until December 2007, after which a new set of Allowances will be issued. The paper demonstrates that the impact of controlling the quantity rather than the price of carbon is to reduce the elasticity of demand for gas, amplifying the market power of gas suppliers, and also amplifying th...

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. The Smart Grid is a set of emerging technologies that will facilitate "real-time pricing" for electricity and increase price elasticity of demand. This paper simulates the e¤ects of this increased demand elasticity using counterfactual simulations in a ...

Assessment of the electricity market shows that, electricity market data can be considered "big data". this data has been analyzed by both conventional and modern data mining methods. The predicted variables of supply and demand are considered to be the input of a defined multi-objective for predicting electricity price, which is the result of the defined model. This shows the advantage of appl...

Most models that are used to analyze support policies for renewable electricity neglect important market features like oligopolistic behavior, emission trading, and restricted cross-border transmission capacities. We use a quantitative electricity market model that accounts for these aspects and decompose the impact of the German Feed-in tariff (FIT) into two frequently counteracting effects: a...