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• W389944303 abstract "Several countries, such as Portugal and Spain, have a significant installed capacity of large-scale reversible hydro power plants with reservoir (pump-hydro storage – PHS) in its portfolio. For instance, in Portugal, installed PHS capacity is 983 MW, corresponding to 22% of the wind and solar power capacity and 5.1% of the total generation capacity. The PHS flexibility can be combined with wind farms in order to smooth wind power variations and hedge risk associated to generation uncertainty. In this dissertation, a new stochastic optimization model for optimizing the coordination between a wind farm and a PHS unit, which participates in the day-ahead electrical energy market, is described. The proposed optimization problem has the following innovative characteristics compared to the state of the art: (a) the wind power uncertainty is modelled through a set of scenarios that capture the temporal dependency of forecast errors (i.e., decision variables that satisfy all constraints in all scenarios are determined); (b) different attitudes of the decision-maker towards risk are modelled with utility theory concepts (i.e., expected utility maximization, in contrast to the expected value paradigm). The objective function includes costs associated to imbalances, spilled wind power, as well as profit from price arbitrage. After the day-ahead optimization, and during the operating day, it is necessary to operate the wind-PHS system in order to minimize the deviation between accepted bids and actual energy delivered. This is accomplished by designing a constrained optimization problem that, based on updated wind power forecasts, minimizes the absolute deviation between bids and actual generation values. This second problem is a novelty in the state of the art and enables an effective calculation of the total profit associated to the market participation. The results, for real wind power generation data and PHS unit, show that the stochastic model achieves a marginally higher total profit compared to a deterministic model (i.e., uses wind power point forecasts as input). The impact of different decision-makers risk profiles is also evaluated." @default.
• W389944303 created "2016-06-24" @default.
• W389944303 creator A5048979552 @default.
• W389944303 creator A5071086175 @default.
• W389944303 date "2014-07-18" @default.
• W389944303 modified "2023-09-25" @default.
• W389944303 title "Optimization Strategies for Pump-Hydro Storage and Wind Farm Coordination Including Wind Power Uncertainty" @default.
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• W389944303 hasPublicationYear "2014" @default.
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