Public welfare, Prices, Emissions (Air pollution), and Electricity
In this study, the authors analyse the social welfare impact of the integration of Portugal and Spain in the Iberian electricity market (MIBEL), taking into account the CO2 price for emissions trading. They model the impact of emissions trading on the daily clearing prices and generation scheduling, and its effects on the benefits of integration as a whole. They compare the impact of market integration in Portugal and Spain and show that the welfare impact of the MIBEL is dependent on the CO2 prices. From their analysis, they conclude high CO2 prices lead to a change in the merit order. Moreover, natural gas is the generation technology that most benefits from transmission constraints and from high CO2 prices, as in the base case it is mainly used as a peak technology. The authors have also found that increases in the CO2 prices do not lead to higher profits. Overall, the introduction of the MIBEL will increase social welfare by reducing generation costs and prices. [ABSTRACT FROM AUTHOR]
Prices, Risk management in business, Adaptive control systems, Artificial neural networks, Power resources, and Electricity
Effective and reliable electricity price forecast is essential for market participants in setting up appropriate risk management plans in an electricity market. A reliable price prediction model based on an advanced self-adaptive radial basis function (RBF) neural network is presented. The proposed RBF neural network model is trained by fuzzy c-means and differential evolution is used to auto-configure the structure of networks and obtain the model parameters. With these techniques, the number of neurons, cluster centres and radii of the hidden layer, and the output weights can be automatically calculated efficiently. Meanwhile, the moving window wavelet de-noising technique is introduced to improve the network performance as well. This learning approach is proven to be effective by applying the RBF neural network in predicting of Mackey–Glass chaos time series and forecasting of the electricity regional reference price from the Queensland electricity market of the Australian National Electricity Market. [ABSTRACT FROM AUTHOR]
Purchasing, Prices, Market volatility, Cost control, Consumers, and Electricity
A solution technique is formulated and provided for the electricity procurement problem faced by a large consumer. The objective of this consumer is to minimise procurement cost while limiting the risk of cost fluctuation due to pool price volatility. Electricity sources include the pool, bilateral contracts and self-production. Uncertainty is related to electricity pool prices. A realistic case study is analysed and results presented. Conclusions are duly drawn. [ABSTRACT FROM AUTHOR]
Risk assessment, Finance, Stochastic analysis, Prices, Direct costing, Electricity, and Electric generators
There is a high level of financial risk associated with the direct participation of wind generation in liberalised electricity markets, due to the stochastic nature of output and imbalance charges set by market prices. The positioning of generation with respect to the market is therefore critical to successful trading activities. Examined is the use of risk characterisation to select the best output level for a wind generator to trade, dependant on maximising revenue and managing marginal costs from imbalances in a competitive market situation. Trading strategies based on utility risk assessment are presented as a possible way to improve market participation for wind generators based on these criteria. [ABSTRACT FROM AUTHOR]
Markets, Prices, Electric industries, Electricity, and Electric power systems
Achieving higher system reliability using market-based approaches is a contemporary issue that has been attracting a great deal of attention in the emerging deregulated electricity-market structure. The paper presents a methodology for the modelling and evaluation of interruptible-load programmes to tackle this issue. The interruptible-load programme is formulated as an equivalent price-based generating resource with a random outage effect, and is thus incorporated in a probabilistic production simulation of a system. The interdependence between the electricity spot-market price and the equivalent generating-resource parameters is addressed and solved by an iterative co-ordinating algorithm. The proposed approach is capable of achieving comprehensive evaluations and systematic decision making for the interruptible load programme in electricity-market operation. A numerical-case-study example is presented to illustrate the validity of the method. The results reveal that interruptible-load programmes can serve effectively as a market-based tool to achieve a proper balance between generation-capacity reliability and economics in the competitive electricity markets. [ABSTRACT FROM AUTHOR]
Prices, Forecasting, Electricity, and Electrical engineering
The paper proposes a novel method of forecasting short-term electricity price based on a two-stage hybrid network of self-organised map (SOM) and support-vector machine (SVM). In the first stage, a SOM network is applied to cluster the input-data set into several subsets in an unsupervised manner. Then, a group of SVMs is used to fit the training data of each subset in the second stage in a supervised way. With the trained network, one can predict straightforwardly the next-day hourly electricity prices. To confirm its effectiveness, the proposed model has been trained and tested on the data of historical energy prices from the New England electricity market. [ABSTRACT FROM AUTHOR]
Power Engineer. Apr/May2005, Vol. 19 Issue 2, p7-7. 1/4p.
Renewable energy sources, Power resources, Finance, Prices, and Electricity
Reports that the government's target of 10% renewable generation by 2010 will cost the consumer and taxpayer more than one billion pounds a year by the end of the decade in Great Britain. Percent increase in electricity prices; Key tool to finance renewable energy; Cost to connect future renewable energy projects to the grid by 2010.