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Robust response to hydro-climatic change in electricity generation planning

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Abstract

An electricity generation planning framework incorporating adaptation to hydro-climatic change is presented. The planning framework internalizes risks and opportunities associated with alternative hydro-climate scenarios to identify a long-term system configuration robust to uncertainty. The implications of a robust response to hydro-climatic change are demonstrated for the electricity system in British Columbia (BC), Canada. Adaptation strategy is crucial in this region, mainly due to the large contribution of hydropower resources to regional electricity supply. Analysis of results from basin-scale hydrologic models driven with downscaled global climate data suggest that shifts in regional streamflow characteristics by the year 2050 are likely to increase BC’s annual hydropower potential by more than 10 %. These effects combined with an estimated decrease in electricity demand by 2 % due to warmer temperatures, could provide an additional 11 TWh of annual energy. Uncertainties in these projected climate impacts indicate technology configurations offering significant long-term operational flexibility will be needed to ensure system reliability. Results from the regional long-term electricity generation model incorporating adaptive capacity show the significant shifts required in the non-hydro capacity mix to ensure system robustness cause an increase in cumulative operating costs of between 1 and 7 %. Analysis of technology configurations involving high-penetrations of wind generation highlights interactions between flexibility requirements occurring over multiple temporal scales.

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Notes

  1. Another method for generating regional hydro-climate ensemble projections embeds a regional climate model into the assessment (Borgomeo et al. 2014).

  2. Alternative methods for addressing uncertainty in long-term energy planning analysis include stochastic programming (Messner et al. 1996; Bistline and Weyant 2013), mini-max optimization (Loulou and Kanudia 1999), real-options (Fuss et al. 2008), and hybrid approaches (Cai et al. 2009)

  3. A limitation of this approach is that the climate ensemble distribution is not a true probability distribution but instead an expert judgment with respect to potential future climatic conditions (Moss et al. 2010). Nonetheless, this is currently the best representation of future conditions regional planners have access to, and thus is used to parameterize the scenario probability space.

  4. For the hydrologic analysis, PCIC applied a modified version of the Variable Infiltration Capacity (VIC) model (Liang et al. 1996).

  5. A limitation of this approach is that it neglects structural changes in the end-use technology mix that would likely accompany a warmer climate (i.e., increased market penetration of cooling technology). Although empirical models that capture these effects have been proposed for air conditioners (Sailor and Pavlova 2003), they are unable to account for the complex interaction with other emerging technologies, such as heat pumps. This can be addressed in future work by incorporating end-use technology investment decisions into the long-term planning problem. Neglecting structural change effects means our estimates likely underestimate climate change impacts to summer electricity demand.

  6. The baseline load trajectory is further shifted by known annual energy entitlements that hydropower resources incorporated into the model currently provides.

  7. Nuclear and coal generation technologies are excluded from the analysis. Neither is considered a viable option in BC due to the province’s no-nuclear, low-carbon energy policy. Carbon capture and storage technology is also excluded from the analysis due to uncertainties surrounding its performance and regulation in the province.

  8. Demand response here refers to a technology that enables the shifting of load over periods ranging from minutes to hours. This is different from long-term demand impacts of efficiency investments and price response, which are included in the baseline load forecast (BCHydro 2013b).

  9. BC contains significant natural gas resources and thus it is assumed that use of these resources does not jeopardize self-sufficiency goals.

  10. Hydropower impacts calculated for BC are of similar magnitude as those estimated for Nordic Europe (Lehner et al. 2005; van Vliet et al. 2013). The results do not consider limitations imposed by existing hydropower capacity, which must accommodate the new conditions. This aspect is explored in the optimization model.

  11. Demand impacts calculated for BC compare well with those estimated for Canada (Isaac and Van Vuuren 2009).

  12. The robust objective function scenario weights are inferred from the percentiles, which in this case translates to a normalized value of 0.08 for both the maximum (95th percentile) and minimum (5th percentile) impact cases, and 0.84 for the average (50th percentile) case.

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Acknowledgements

Funding from Canada’s National Science & Engineering Research Council is gratefully acknowledged. This work was also supported by the Pacific Institute for Climate Solutions (PICS).

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Authors and Affiliations

  1. Institute for Integrated Energy Systems, Department of Mechanical Engineering, University of Victoria, PO Box 3055 STN CSC, Victoria, BC, Canada, V8W 3P6

    Simon C. Parkinson & Ned Djilali

  2. International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361, Laxenburg, Austria

    Simon C. Parkinson

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  1. Simon C. Parkinson
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Correspondence to Simon C. Parkinson.

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Parkinson, S.C., Djilali, N. Robust response to hydro-climatic change in electricity generation planning. Climatic Change 130, 475–489 (2015). https://doi.org/10.1007/s10584-015-1359-5

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