Optimal Design of the Power Generation Network in California: Moving towards 100% Renewable Electricity by 2045
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Optimal Design of the Power Generation Network in California: Moving towards 100% Renewable Electricity by 2045

Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt


To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, binary quadratic programming.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3669281

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[1] IPCC (2018): Global Warming of 1.5 °C. Cambridge, Intergovernmental Panel on Climate Change, Cambridge University Press.
[2] CARB (2019): California Greenhouse Gas Emission Inventory: 2000 - 2017W. Sacramento, California Air Resources Board.
[3] Lyon, T. P. Drivers and impacts of renewable portfolio standards. Annu. Rev. Resour. Econ. 8, 141–155 (2016).
[4] C.A. Legis. Assemb. SB-100. Reg. Sess. (2018).
[5] Fripp, M. Switch: A planning tool for power systems with large shares of intermittent renewable energy. Environ. Sci. Technol. 46, 6371-6378 (2012).
[6] Short, W.; Blair, N.; Sullivan, P.; Mai, T. ReEDS model documentation: base case data and model description; National Renewable Energy Laboratory: Golden, CO, August, 2009; p 95.
[7] MacDonald, A. et al. Future cost-competitive electricity systems and their impact on US CO2 emissions. Nat. Clim. Change 6, 526–531 (2016)
[8] Leibowitz, L.P. California's geothermal resource potential, Energy Sources, 3:3-4, 293-311 (1978)
[9] Yen-Nakafuji, D. California wind resources, Intra-state IEPR Workshop, Sacramento, CA, May, 2005; p 27.
[10] Simons, G. and J. McCabe, California solar resources in support of the 2005 integrated energy policy report, draft staff paper, CEC-500-2005-072-D, 2005
[11] California Complete Count office, https://census.ca.gov/regions/
[12] Kern Economic Development Corporation, http://kedc.com/site-selection/target-industries/energy-natural-resources/