Vladimiro MIRANDA

Wind Power, Distributed Generation: New Challenges, New Solutions

This paper discusses some issues related with the growing importance of wind power and in modern power systems and some challenges raised by the emergence of distributed generation, and how computational intelligence and other modern techniques have been able to provide valuable results in solving the new problems. It presents some solutions obtained with a number of computational intelligence techniques and their application to real cases.Distributed generation is assuming an important role in modern power systems. The progress in technologieshas allowed a portfolio of solutions to now be considered and found profitable, while only a few years ago one would witness arguments stating that only large centralized power stations would be economically feasible. The most widespread distributed generation alternatives are mini-hydros, wind generation, co-generation (CHP, combined heat and power) in industry or buildings, and small independent power generators (diesel, gas, or biomass). Wind generation, in particular, has placed new challenges on system operation and planning, because of the “undispatchable” nature of wind, the difficulty in forecasting, and the impossibility of storing it. The emergence of distributed generation is coupled with the restructuring of the electric sector and the market orientation it received in recent years. This has opened business opportunities to private investors, non-institutional, in supplying power to the grid, resulting in a new inflow of capital to the sector, coming from sectors that traditionally were not investing in the energy business.

Anahtar Kelimeler:

Wind generation, distributed generation, computational intelligence

Wind Power, Distributed Generation: New Challenges, New Solutions

Keywords:

Wind generation, distributed generation, computational intelligence,

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H.L. Willis, Power Distribution Planning Reference Book, Marcel Dekker Inc., New York, 1997. ISBN: 0-8247- 0098-8.
V. Miranda, C. Monteiro, “Fuzzy inference and cellular automata in spatial load forecasting”, in Proc. IEEE PES Winter Meeting., Singapore, Dec 2000.
C. Monteiro et al., The SOLARGIS handbook – guidelines for the elaboration of regional integration plans for decentralized electricity production with renewable energies, ed. European Commission, project SOLARGIS, JOULE programme, 1996.
I.J. Ramirez-Rosado et al, “Powerful planning tools”, IEEE Power & Energy Magazine, vol.3, no.2, pp.56-63, Apr 2005.
V. Miranda, C. Monteiro, I.J. Ramirez-Rosado, “Negotiation Aid System for Promotion of Distributed Gener- ation and Renewables”, Proceedings of IEEE Transmission and Distribution Conference and Exhibition: Asia PaciŞc, Yokohama, Japan, Oct 2002.
N. Hatziargyriou et al., “The CARE system overview: advanced control advice for power systems with large scale integration of renewable energy sources”, Wind Engineering, vol. 23, no. 2, pp. 57-68, 1999.
N. Hatziargyriou et al., “MORECARE overview”, Proceedings of MedPower 2002 – 3rdMediterranean Confer- ence and Exhibition on Power Generation, Transmission, Distribution and Energy Conversion, Athens, Greece, 2002.
V. Miranda, N. Fonseca, “EPSO – Evolutionary Particle Swarm Optimization, a New Algorithm with Appli- cation in Power Systems”, Proceedings of IEEE Transmission and Distribution Conference and Exhibition:Asia PaciŞc, Yokohama, Japan, Oct 2002.
R. Billinton, R. Karki, ”Application of Monte Carlo simulation to generating system well-being analysis”, IEEE Trans. on Power Systems, Vol. 14, No. 3, pp. 1172-1177, Aug. 1999.
A.M. Leite da Silva et al, “Application of Monte Carlo simulation to generating system well-being analysis
considering renewable sources”, Proceedings of PMAPS 2004, International Conference on Probabilistic Methods
Applied to Power Systems, Iowa, USA, Sept. 2004.