Combining AHP and TOPSIS Methods to Evaluate Investment for Wind Farm Construction

Abstract:

Wind is one of the most promising sources of alternative energy. The construction of wind farms grows quickly in China. It is necessary for stakeholders to estimate investment costs and make good decisions on a wind power project by making a budget for the investment. However, the identification of rational investment practices is technically challenging because of the lack of scientific tools to evaluate optimal decisions. A multi-criteria evaluation method was proposed to select rational investment strategy for wind farm construction. The method is based on the analytic hierarchy process (AHP) together with a technique for order preference by similarity to ideal solution (TOPSIS). A decision problem hierarchy with three layers were investigated. The top layer is an objective layer for evaluating the investment rationality. The intermediate layer includes three evaluation criteria, that is, configuration of wind turbine generator systems, physical environment and social environment. Some relative and important indicators for each criterion are in the low layer. The evaluation results illustrate that the proposed method is practical and helpful to indentify the investment rationality for wind farms.

• Periodical: Advanced Materials Research (Volumes 860-863)
• Pages: 280-286
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.860-863.280
• Online since: December 2013
• Authors: Xiang Feng Zhang*
• Keywords: AHP, Investment Rationality, Multi-Criteria Evaluation, TOPSIS, Wind Farm

References

[1] M. Ali, I. Ilie, J. Milanovic and G. Chicco: IEEE Transactions on Power Systems, Vol. 1 (2013), pp.309-316.

[2] Q. Ai and C. H. Gu: Renewable Energy, Vol. 34 (2009), pp.608-614.

[3] J. S. Gonzalez, A.G. Rodriguez, J. C. Mora, M. B. Payan and J. R. Santos: Renewable Energy, Vol. 36 (2011), p.1973-(1982).

[4] J. Earnest and T. Wizelius. Wind power plants and project development, PHI Learning Private Limited, New Delhi (2011) , pp.391-430.

[5] W. Ho, X.W. Xu, and P.K. Dey: European Journal of Oper-ational Research. Vol. 202 ( 2010), p.16–24.

[6] M. Da˘gdeviren, S. Yavuz and N. Kılınc: Expert Systems with Applications. Vol. 36 (2009), pp.8143-8151.

[7] L. Gao and A. Hailu: Ecological Modelling. Vol. 249 (2013), p.75– 83.

[8] L. Gao and A. Hailu: Environmental, modelling & Software. Vol. 31 (2012), pp.1-18.

[9] T.L. Saaty: International Journal of Service Sciences, Vol. 1 (2008), pp.83-98.

[10] T.L. Saaty: European Journal of Operational Research. Vol. 48 (1990), pp.9-26.