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Planning Low-cost, Low-carbon Power System Investments Using the Switch Optimization Model
With Switch (a loose acronym for Solar, Wind, Hydro and Conventional generators and Transmission), researchers can explore generation, transmission, and storage options for the future electricity grid. The model identifies cost-effective investment decisions for meeting future electricity demand, taking into account the existing grid as well as projections of future technological developments, renewable energy potential, fuel costs, and public policy.
Switch was created by Dr. Matthias Fripp and applied to California for his doctoral dissertation at the Energy and Resources Group at UC Berkeley. The model uses time-synchronized load and renewable generation data to evaluate future capacity investments while ensuring that load is met reliably and policy goals are reached at minimum cost. The optimization is formulated as a deterministic mixed integer program, which is solved by standard commercial software.
The CITRIS cluster has been the primary engine for running simulations with SWITCH and for testing changes to code. SWITCH is a high-resolution long-term grid planning model for evaluating policies and planning for a low-cost and low-emission electrical grid. To date, researchers have run 508 large optimizations on the cluster, evaluating different policy/cost/demand scenarios and different versions of the code.
The results indicate that very deep emission reductions are possible without a large increase in the cost of power. The model has geographic and temporal resolution that is unprecedented in investment planning models.
Switch was created by Dr. Matthias Fripp and applied to California for his doctoral dissertation at the Energy and Resources Group. The model uses time-synchronized load and renewable generation data to evaluate future capacity investments while ensuring that load is met reliably and policy goals are reached at minimum cost. The optimization is formulated as a deterministic mixed integer program, which is solved by standard commercial software. RAEL has adapted the model to the Western Electricity Coordinating Council (WECC).
The current team working on Switch-WECC at RAEL includes:
Josiah Johnston (siah @ berkeley.edu)
Ana Mileva (amileva @ berkeley.edu)
Jimmy Nelson (jimmynelson @ berkeley.edu)
RAEL has added features to the model, including:
In our publication in the April 2012 issue of Energy Policy, we show that WECC power sector emissions can be reduced to 54% of 1990 levels by 2030 (consistent with a 450 ppm climate stabilization scenarios) using different portfolios of existing generation technologies. Under a range of resource cost scenarios, most coal power plants would be replaced by solar, wind, gas, and/or nuclear generation, with intermittent renewable sources providing at least 17% and as much as 29% of total power by 2030. Assuming carbon price revenues are reinvested in the power sector, the cost of power is found to increase by at most 20% relative to business-as-usual projections. Figures from this study are found below:



