Planning for Sustainable Development of Energy Infrastructure: Fast – Fast Simulation Tool

Planning for Sustainable Development of Energy Infrastructure: Fast – Fast Simulation Tool

R. Barelkowski 

West-Pomeranian University of Technology in Szczecin, Poland

| |
| | Citation



Energy management has significant impact on planning within local or regional scale. The consequences of the implementation of large-scale renewable energy source involves multifaceted analyses, evaluation of environmental impacts, and the assessment of the scale of limitations or exclusions imposed on potential urbanized structures and arable land. The process of site designation has to acknowledge environmental transformations by inclusion of several key issues, e.g. emissions, hazards for nature and/or inhabitants of urbanized zones, to name the most significant. The parameters of potential development of energy-related infrastructure of facility acquire its local properties – the generic development data require adjustment, which is site specific or area specific. FAST (Fast Simulation Tool) is a simple IT tool aimed at supporting sustainable planning on local or regional level in reference to regional or district scale energy management (among other issues). In its current stage, it is utilized – as a work in progress – in the assessment of wind farm structures located within the area of Poznan agglomeration. This paper discusses the implementation of FAST and its application in two conflicting areas around the agglomeration of Poznan.


renewable energy planning, spatial planning, sustainability


[1] Barelkowski, R.,The edge of the [dis]order. (eds.) The Sustainable City VII. Urban Re- generation and Sustainability, eds M. Pacetti, G. Passerini, C.A. Brebbia & G. Latini, Wessex Institute of Technology, WIT Press, Southampton & Boston, pp. 764–765, 2012. doi:

[2] C.f. Mehlg, Planning Guidelines, The Department of the Environment, Heritage and Local Government, The Minister of the Environment, Heritage and Local Government (as published in Section 28 of the Planning and Development Act, 2000), Dublin, pp. 37–44, 2007.

[3] Zhang, P.Y., Topics in wind farm layout optimization: analytical wake models, noise propagation, and energy production, University of Toronto, Canada, pp. 4–5, 2013.

[4] Kusiak, A. & Li, W., , Estimation of wind speed: a data-driven approach. Journal of Wind Engineering and Industrial Aerodynamics, 98(10), pp. 562–564, 2010. doi:

[5] Kwong, W.Y., Zhang, P.Y., Romero, D., Moran, J., Morgenroth, M. & Amon, C., Multi- objective optimization of wind farm layouts under energy generation and noise propa- gation. Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2012, Chicago, pp. 5–6, 2012.

[6] Wagner, M., Neumann, F., Veeramachaneni, K. & O’Reilly, U.-M., Optimizing the lay- out of 1000 wind turbines. European Wind Energy Association Annual Event, Brussels, Belgium, pp. 5–6, 2011, available at: pdf (accessed 22 March 2014).

[7] Tong, W., Chowdhury, S., Mehmani, A. & Messac, A., Multi-objective wind farm de- sign: exploring the trade-off between capacity factor and land use. 10th World Congress on Structural and Multidisciplinary Optimization, Orlando, FL, pp. 5–6, 2013.

[8] CWEC, Permitting setback requirements for wind turbines in California. PIER Interim Project Report, California Wind Energy Collaborative for California Energy Commis- sion, November 2006, CEC-500-2005-184, Davis, pp. 4–6, 2006.

[9] European Environment Agency, Europe’s onshore and offshore wind energy potential. An assessment of environmental and economic constraints, EEA Technical Report, Co- penhagen, vol. 10, p. 51, 2009.

[10] Ragheb, M., Orography and Wind Turbine Siting, 7, 2013.

[11] Samorani, M., The Wind Farm Layout Optimization Problem, pp. 11–12, 2011.

[12] CWET, A Technical Note on Micro-siting of Wind Turbines, Centre for Wind Energy Technology, Ministry of New & Renewable Energy, New Delhi, 15, 2011.

[13] Loemker, C. & Renkema, D., Wake model validation, GE Wind Energy, TU Delft, Billind/Hovsore, 2006, available at: docs/Task23_Billund/15%20Wake%20mod%20vali%20DR.pdf (accessed 22 March 2014).

[14] Sotiropoulos, F., Development of a high-resolution virtual wind simulator for optimal design of wind energy projects, Saint Anthony Falls Laboratory, Minneapolis, MN, pp. 18–19, 2013.

[15] Banak, M.J., Lokalizacja elektrowni wiatrowych – uwarunkowania srodowiskowe i prawne, Czlowiek i Srodowisko, 34(3–4), p. 120, 2010.

[16] Rogers, J., Slegers, N. & Costello, M., A method for defining wind turbine setback stan- dards, Wind Energy, 15(2), pp. 289–303, 2011. doi:

[17] Meyers, J. & Meneveau, C., Optimal turbine spacing in fully developed wind-farm boundary levels, Wind Energy, 15, pp. 314–315, 2011. doi: we.469

[18] C.f. Chowdhury, S., Zhang, J., Messac, A. & Castillo, L., Characterizing the influence of land configuration on the optimal wind farm performance, Multidisciplinary Design and Optimization Laboratory, ASME 2011 International Design Engineering Technical Conferences, and Computer and Information in Engineering Conference, Washington,

DC, p. 3, 2011. doi:

[19] Tzanos, J., Margellos, K. & Lygeros, J., Optimal wind turbine placement via random- ized optimization techniques, ETH Zurich, pp. 8, Summarization of Research being the part of MoVeS project, FP7-ICT-257005, supported by the European Commission, pp. 5–7, 2011.

[20] Barelkowski, R., Sustainability – myth, reality, and future. Planning and renewable en- ergy management, The Sustainable City VIII. Urban Regeneration and Sustainability, eds S.S. Zubir & C.A. Brebbia, Wessex Institute of Technology, WIT Press, Southamp- ton & Boston, pp. 792–793, 2013. doi: