A new computational algorithm for the calculation of maximum wind energy penetration in autonomous electrical generation systems

[1]  Dionysis Assimacopoulos,et al.  Evaluation of Renewable Energy potential using a GIS decision support system , 1998 .

[2]  John Kabouris,et al.  Wind electricity in Greece: recent developments, problems and prospects , 2000 .

[3]  Arthouros Zervos,et al.  Impact of social costing on the competitiveness of renewable energies: the case of Crete , 2000 .

[4]  John K. Kaldellis,et al.  Optimum autonomous wind–power system sizing for remote consumers, using long-term wind speed data , 2002 .

[5]  John K. Kaldellis,et al.  Feasibility evaluation of Greek State 1990–2001 wind energy program , 2003 .

[6]  John K. Kaldellis,et al.  Income loss due to wind energy rejected by the Crete island electrical network – the present situation , 2004 .

[7]  John K. Kaldellis,et al.  Investigation of Greek wind energy market time-evolution , 2004 .

[8]  J. Kaldellis Social attitude towards wind energy applications in Greece , 2005 .

[9]  Daniel Weisser,et al.  Instantaneous wind energy penetration in isolated electricity grids: concepts and review , 2005 .

[10]  G. C. Bakos,et al.  A new energy planning methodology for the penetration of renewable energy technologies in electricity sector—application for the island of Crete , 2006 .

[11]  Stavros A. Papathanassiou,et al.  Power limitations and energy yield evaluation for wind farms operating in island systems , 2006 .

[12]  D. Zafirakis,et al.  Present situation and future prospects of electricity generation in Aegean Archipelago islands , 2007 .

[13]  John K. Kaldellis,et al.  Maximum wind potential exploitation in autonomous electrical networks on the basis of stochastic analysis , 2008 .

[14]  D. Fadare The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria , 2010 .

[15]  John K. Kaldellis,et al.  Combining hydro and variable wind power generation by means of pumped-storage under economically viable terms , 2010 .

[16]  Jing Shi,et al.  On comparing three artificial neural networks for wind speed forecasting , 2010 .

[17]  K. A. Kavadias,et al.  Energy balance analysis of wind-based pumped hydro storage systems in remote island electrical networks , 2010 .