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| 1 |
ID:
104912
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| Publication |
2011.
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| Summary/Abstract |
After a long stagnating period during the second half of the 1990s, the market of wind energy in Greece was described by remarkable but unstable growth rates that resulted in the operation of 1 GW of wind power by the end of 2009. Still though, penetration of wind energy is not the one anticipated. On the other hand, national targets regarding the Renewable Energy Sources' (RES) contribution and existence of excellent wind potential areas across Greece challenge new wind energy investments. Acknowledging the unsteady development rates of wind power in Greece, efficiency of the State support mechanisms is currently investigated. Based on an analytical evaluation model, the investigation undertaken is extended to provide a detailed cost-benefit analysis of several wind energy case studies, including mainland and island applications as well as comparison with both conventional power stations and photovoltaic plants. For this purpose, the financial support provided by the State is directly compared with benefits accruing from the operation of wind parks, considering also the avoidance of social costs deriving from thermal power stations. Based on the results obtained, the beneficial characteristics of wind energy applications for the Greek society are clearly demonstrated, especially in the case of non-interconnected island grids.
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| 2 |
ID:
168689
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| Summary/Abstract |
Renewable energy sources, where wind energy is an important part, are increasingly participating in developing economies and environmental benefits. Wind power is strongly dependent on wind velocity and thus identifying patterns in wind speed data is an important issue for forecasting the generated power from a wind turbine and it has significant importance for the renewable energy market operations. In this work we approach the problem of identification of the underlying dynamic characteristics and patterns of wind behavior using two approaches of non-linear time series analysis tools: Recurrence Plots (RPs) and Complex Network analysis. The proposed methodology is applied on wind time series collected by cup anemometers located on a wind turbine installed in Greece. We show that the proposed approach provides useful information which can characterize distinct two time intervals of the data, one ranging from 2 to 4.5 days and another from 5 to 8.5 days. Also analysis can identify and detect dynamical transitions in the system's behavior and also reveals information about the changes in state inside the whole time series. The results will be useful in wind markets, for the prediction of the produced wind energy and also will be helpful for wind farm site selection.
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