Renewable Sources of Energy

ICT systems allow more efficient operating and maintenance of power systems using renewable sources of energy like water, wind and sunlight. For example there are approaches in development to monitor wind turbines using a model-based method of neural networks [1]. Therefore the temperature of the generator bearings is measured to predict failures. This could avoid wind turbines standing still and help increasing the productivity of such systems.

Information technology could also improve the management of distributed renewable energy sources like home photovoltaic panels. There are approaches in research that add processors to control arrays of photovoltaic units. This enables remote management of these energy generating systems and allows creating central management platforms and the establishment of integrated networks [2]. A different approach in research shows that Fuzzy models can be used to control photovoltaic power systems including the required conversion to obtain this source of energy [3].

Another example for improved management of renewable energy generators enabled by ICT is the approach to predict the amounts of energy generated by wind turbines. Therefore short-term forecasts of wind speed and direction of several observation points have to be considered and used to calculate the resulting power output of the wind turbines located in these areas [4]. As wind energy inheres large variability such predictions would be very useful to manage the compliance of energy demands in future electricity grids. Increasing efficiency of wind turbines implies techniques to estimate wind speeds. In connection to this, approaches based on self-organizing neural networks can be found in scientific literature [5].

References

[1] J. Xiang, S. Watson, and Y. Liu. Smart monitoring of wind turbines using neural networks. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 1–8. Springer Berlin Heidelberg, 2009.

[2] C. Mallett. Network-enabled intelligent photovoltaic arrays. In  Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 39–47. Springer Berlin Heidelberg, 2009.

[3] A. Hajjaji, M. BenAmmar, J. Bosche, M. Chaabene, and A. Rabhi. Integral fuzzy control for photovoltaic power systems. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 219–228. Springer Berlin Heidelberg, 2009.

[4] M. Khalid and A. V. Savkin. Development of short-term prediction system for wind power generation based on multiple observation points.  In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 89–98. Springer Berlin Heidelberg, 2009.

[5] G. Cirrincione and A. Marvuglia. A novel self-organizing neural technique for wind speed mapping. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 209–217. Springer Berlin Heidelberg, 2009.