7. Conclusions

One of the most important conclusions is the fact that wind power as a non-dispatchable kind of energy, when employed in a hybrid system with implementation of forecast, can be managed as a semi-dispatchable energy. The generation can be modeled based on the needs of the end user or as a base energy for long periods of time, depending on the capacity of the storage and output power required for the system. Consequently, the frequency of the system will not be compromised because of sudden changes in wind power. The proposed HS is meant to work in the distribution level for housing sectors and small stores.

References

847996

2012.12.004

j.apenergy.2016.03.096

apenergy.2011.04.011

S0378-7796(03)00050-6

apenergy.2016.05.052

apenergy.2013.10.030

790-809. DOI: 10.1016/j.renene.2015.07.004

rser.2015.01.059

[1] Zhang H, Xing F, Cui H-Z, Chen D-Z, Ouyang X, Xu S-Z, et al. A novel phase-change cement composite for thermal energy storage: Fabrication, thermal and mechanical prop-

A Proposed Energy Management System to Overcome Intermittence of Hybrid Systems Based on Wind, Solar,…

http://dx.doi.org/10.5772/intechopen.76760

41

[2] Bagen BR. Evaluation of different operating strategies in small stand-alone power systems. IEEE Transactions on Energy Conversion. 2005;20:654-660. DOI: 10.1109/TEC.2005.

[3] Ma T, Yang H, Lu L. Performance evaluation of a stand-alone photovoltaic system on an isolated island in Hong Kong. Applied Energy. 2013;112:663-672. DOI: 10.1016/j.apenergy.

[4] Bouffard F, Galiana FD. Stochastic security for operations planning with significant wind

[5] Zhao Y, Ye L, Li Z, Song X, Lang Y, Su J. A novel bidirectional mechanism based on time series model for wind power forecasting. Applied Energy. 2016;177:793-803. DOI: 10.1016/

[6] Wang J, Botterud A, Bessa R, Keko H, Carvalho L, Issicaba D, et al. Wind power forecasting uncertainty and unit commitment. Applied Energy. 2011;88:4014-4023. DOI: 10.1016/j.

[7] Bathurst GN, Strbac G. Value of combining energy storage and wind in short-term energy and balancing markets. Electric Power Systems Research. 2003;67:1-8. DOI: 10.1016/

[8] Exizidis L, Kazempour SJ, Pinson P, de Greve Z, Vallée F. Sharing wind power forecasts in electricity markets: A numerical analysis. Applied Energy 2016;176:65-73. DOI: 10.1016/j.

[9] Fathima AH, Palanisamy K. Optimization in microgrids with hybrid energy systems– A review. Renewable and Sustainable Energy Reviews. 2015;45:431-446. DOI: 10.1016/j.

[10] McKenna R, Hollnaicher S, Fichtner W. Cost-potential curves for onshore wind energy: A high-resolution analysis for Germany. Applied Energy. 2014;115:103-115. DOI: 10.1016/j.

[11] Santamaría-Bonfil G, Reyes-Ballesteros A, Gershenson C. Wind speed forecasting for wind farms: A method based on support vector regression. Renewable Energy. 2016;85:

[12] Kavasseri RG, Seetharaman K. Day-ahead wind speed forecasting using f-ARIMA models. Renewable Energy. 2009;34:1388-1393. DOI: 10.1016/j.renene.2008.09.006

power generation. 2008. pp. 1-11. doi:10.1109/PES.2008.4596307

erties. Applied Energy. 2016;170:130-139. DOI: 10.1016/j.apenergy.2016.02.091

In real life application, this HS model will help to keep the net frequency in the tolerance rate, given the fact that it will not be disturbed by the HS when connected as DG into the network, thanks to the no uncertainty and no intermittence in the HS output power.

When the priority is completely given to the FC generation, there is a high risk of running out of hydrogen and not meeting the full capacity of the HS.

Another finding is the fact that to generate a completely linear power output, there is a need to "sacrifice" other features such as magnitude power, storage limits, and even the times to recharge the hydrogen tank according to the needs of the end user; hence, it is recommended to compromise the involved parties regarding the HS.

The implementation of forecast is demonstrated to be of great importance in planning the dispatch of power, improving and taking contingency measurements as to avoid disturbing the network or even improving the network in the connection point if necessary.

Forecast applied to wind power and used for the MPC allows the manipulation of the elements that make the HS obtain the desired output power while avoiding penalties.
