12 resultados para electricity market

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


Relevância:

100.00% 100.00%

Publicador:

Resumo:

Price forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naive and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naive and that it performs slightly better than the direct price forecast.

Relevância:

70.00% 70.00%

Publicador:

Resumo:

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

Relevância:

60.00% 60.00%

Publicador:

Resumo:

In this paper, the development of bidding strategies is investigated for a wind farm owner. The optimization model is characterized by making the analysis of scenarios. The proposed approach allows evaluating alternative production strategies in order to submit bids to the electricity market with the goal of maximizing profits. The problem is formulated as a linear programming problem. An application to a case study is presented

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica na Área de Especialização de Energia

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Relevância:

60.00% 60.00%

Publicador:

Resumo:

The increasing integration of larger amounts of wind energy into power systems raises important operational issues, such as the balance between power generation and demand. The pumped storage hydro (PSH) units are one possible solution to mitigate this problem, once they can store the excess of energy in the periods of higher generation and lower demand. However, the behaviour of a PSH unit may differ considerably from the expected in terms of wind power integration when it operates in a liberalized electricity market under a price-maker context. In this regard, this paper models and computes the optimal PSH weekly scheduling in a price-taker and price-maker scenarios, either when the PSH unit operates in standalone and integrated in a portfolio of other generation assets. Results show that the price-maker standalone PSH will integrate less wind power in comparison with the price-taker situation. Moreover, when the PSH unit is integrated in a portfolio with a base load power plant, the role of the price elasticity of demand may completely change the operational profile of the PSH unit. (C) 2014 Elsevier Ltd. All rights reserved.

Relevância:

60.00% 60.00%

Publicador:

Resumo:

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Eletrotécnica

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de energia

Relevância:

20.00% 20.00%

Publicador:

Resumo:

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.