Your browser does not support JavaScript!

access icon openaccess Multi-domain analysis of photovoltaic impacts via integrated spatial and probabilistic modelling

replace with: Currently, the impacts of wide-scale implementation of photovoltaic (PV) technology are evaluated in terms of such indicators as rated capacity, energy output or return on investment. However, as PV markets mature, consideration of additional impacts (such as electricity transmission and distribution infrastructure or socio-economic factors) is required to evaluate potential costs and benefits of wide-scale PV in relation to specific policy objectives. This study describes a hybrid GIS spatio-temporal modelling approach integrating probabilistic analysis via a Bayesian technique to evaluate multi-scale/multi-domain impacts of PV. First, a wide-area solar resource modelling approach utilising GIS-based dynamic interpolation is presented and the implications for improved impact analysis on electrical networks are discussed. Subsequently, a GIS-based analysis of PV deployment in an area of constrained electricity network capacity is presented, along with an impact analysis of specific policy implementation upon the spatial distribution of increasing PV penetration. Finally, a Bayesian probabilistic graphical model for assessment of socio-economic impacts of domestic PV at high penetrations is demonstrated. Taken together, the results show that integrated spatio-temporal probabilistic assessment supports multi-domain analysis of the impacts of PV, thereby providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives.


    1. 1)
      • 14. Zhu, J., Betts, T., Gottschalg, R., Hutchins, M., Pearsall, N.: ‘Accuracy assessment of models estimating total irradiance on inclined planes in Loughborough’. Fourth Photovoltaic Science, Applications and Technology Conf. (PVSAT-4), Bath, UK, 2008, pp. 207210.
    2. 2)
      • 4. Rowley, P., Gough, R., Doylend, N., Thirkill, A., Leicester, P.: ‘From smart homes to smart communities: Advanced data acquisition and analysis for improved sustainability and decision making’. In Information Society (i-Society), IEEE 2013 Int. Conf. on Smart Data’, June 2013, pp. 263268.
    3. 3)
      • 30. Anderson, B.: ‘Estimating small area income deprivation : an iterative proportional fitting approach’, in Tanton, R., Edwards, K. (Eds.): ‘Spatial microsimulation: A reference guide for users’ (Springer, 2013), pp. 4967.
    4. 4)
    5. 5)
      • 25. Pearl, J., Kaufmann, M.: ‘Probabilistic reasoning in intelligent systems: networks of plausible inference’, 1988, ISBN 1558604790, i9781558604797.
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
      • 11. Hofstra, N., Haylock, M., New, M., Jones, P., Frei, C.: ‘Comparison of six methods for the interpolation of daily European climate data’, J. Geoph. Res., 2008, D21, p. 113.
    14. 14)
    15. 15)
      • 23. Fenton, N., Neil, M.: ‘Risk assessment and decision analysis with bayesian networks’ (CRC Press, 2012), ISBN 1439809100, i9781439809105.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • 10. UK Meteorological Office: ‘Met office integrated data archive system (MIDAS) land and marine surface stations data (1853-current)’, NCAS British Atmospheric Data Centre, 2012,, accessed October 2014.
    20. 20)
      • 1. UK Government FiT Statisitics’., accessed October 2014.
    21. 21)
    22. 22)
    23. 23)
      • 32. Rowley, P., Leicester, P., Thornley, P., et al: ‘WISE-PV: Whole system and socio-economic impacts of wide scale PV integration’. Proc. of the European Photovoltaic Solar Energy (EU-PVSEC) Conf., Amsterdam, September 2014.
    24. 24)
    25. 25)
    26. 26)
      • 12. Strous, L.: ‘Position of the Sun’, 2011,, accessed October 2014.
    27. 27)
    28. 28)
    29. 29)
    30. 30)
    31. 31)
      • 27. Koller, D., Pfeffer, A.: ‘Object-oriented Bayesian networks’. Proc. of the 13th Annual Conf. on Uncertainty in Artificial Intelligence, Providence, Rhode Island, 1997.
    32. 32)

Related content

This is a required field
Please enter a valid email address