User:RobbieIanMorrison/sandbox/work in progress 12

✅ transferred


 * current sub-article located on wikipedia proper :
 * the capitalization of Switch elsewhere will be fixed on transfer
 * Matthias or Switch team to confirm (either email me or make the edits yourself here):
 * suitably licensed diagram (mostly for its role in breaking up text!)
 * any reliable secondary sources to support the fact that Switch was instrumental in shifting the PUC (I have somewhat exceeded my role as a Wikipedia editor by including unsourced information)

Switch
Switch is a loose acronym for solar, wind, conventional and hydroelectric generation, and transmission. Switch is an optimal planning model for power systems with large shares of renewable energy, grid storage, and demand response. Switch is being developed by the Department of Electrical Engineering, University of Hawaiʻi, Mānoa, Hawaii, USA. The project runs a small website and hosts its codebase and datasets on GitHub. Switch is written in Pyomo, an optimization components library programmed in Python. Any solver supported by Pyomo can be used, including the open source GLPK and Cbc solvers and commercial packages like CPLEX and Gurobi.

Major version2.0 was released in August 2018 and serves as the basis for the following description.

Switch is a power system model, focused on renewables integration. It can identify which generator, storage, and transmission projects to build in order to satisfy electricity demand at the lowest cost over a several year period while also reducing emissions. Switch utilizes multi-stage stochastic linear optimization with the objective of minimizing the present value of the cost of power plants, transmission capacity, fuel usage, and an arbitrary per-tonne charge (to represent either a carbon tax or a certificate price), over the course of a multi-year investment period. Renewable portfolios and carbon caps may also be specified. Switch has two major sets of decision variables. First, at the start of each investment period, Switch selects how much generation capacity to build in each of several geographic load zones, how much power transfer capability to add between these zones, and whether to operate existing generation capacity during the investment period or to temporarily mothball it to avoid fixed operation and maintenance costs. Second, for a set of sample days within each investment period, Switch makes hourly decisions about how much power to generate from each dispatchable power plant, store at each grid storage facility, or transfer along each transmission interconnector. The system must also ensure adequite generation and transmission capacity, in which case the user can either set a planning reserve margin of say 15% above the load forecasts or alternatively specify an operating reserve margin of similar value. For each sampled hour, Switch can use electricity demand and renewable power production based on actual measurements, so that the weather-driven correlations between these elements remain intact. Switch supports partload efficiency for thermal generation and a number of established or experimental grid energy storage technologies such as pumped hydro, industrial batteries, hydrogen, and compressed air.

Following the optimization phase, the user may optionally deploy further tests. In a second phase, the proposed investment plan can be run against a more complete set of weather conditions and added backstop generation capacity so that the planning reserve margin is always met. In a third phase, the system costs can be recalculated by freezing the investment plan and operating the proposed power system over a full set of weather conditions.

A 2012 paper uses California from 2012 to 2027 as a case study for Switch. The study finds that there is no ceiling on the amount of wind and solar power that could be used and that these resources could potentially reduce emissions by 90% or more (relative to 1990 levels) without reducing reliability or severely raising costs. Furthermore, policies that encourage electricity customers to shift demand to times when renewable power is most abundant (for example, though the well-timed charging of electric vehicles) could achieve radical emission reductions at moderate cost.

, the most significant application of Switch has been to support consensus power system planning in Hawaii. In 2015, the State of Hawaii signed off on policy for a 100% renewable portfolio standard (RPS) by 2045. In parallel, the Hawaii Public Utilities Commission (PUC) was consulting on power utility planning. Testimony from Switch lead developer Matthias Fripp and the E3 consultancy, retained by incumbent utility HECO and who also ran a fork of Switch named RESOLVE, were reportedly instrumental in securing a more rapid transition to renewable generation. The Blue Planet Foundation, a clean energy NGO based in Honolulu, also advocated the use of open models and data for public planning in Hawaii.

The Switch model is also being applied in Chile, Mexico, and elsewhere.

An investigation in 2018 favorably compared Switch with the proprietary General Electric MAPS model using Hawaii as a case study.