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Switch 2.0: A Modern Platform for Planning High-Renewable Power Systems
- Source :
- "Switch 2.0: A modern platform for planning high-renewable power systems", SoftwareX 10:10051, 2019
- Publication Year :
- 2018
-
Abstract
- This paper describes Switch 2.0, an open-source modeling platform for planning transitions to low-emission electric power grids, designed to satisfy 21st century grid planning requirements. Switch is capable of long-, medium- and short-term planning of investments and operations with conventional or smart grids, integrating large shares of renewable power, storage and/or demand response. Applications include integrated resource planning, investment planning, economic and policy analyses as well as basic research. Potential users include researchers, educators, industry and regulators. Switch formulates generation and transmission capacity planning as a mixed integer linear program where investment and operation are co-optimized across sampled time series during multiple investment periods. High-resolution production cost modeling is supported by freezing investment decisions and including longer time series and more operational details. Modeling features include unit commitment, part-load efficiency, planning and operating reserves, fuel supply curves, storage, hydroelectric networks, policy constraints and demand response. Switch has a modular architecture that allows users to flexibly compose models by choosing built-in modules 'a la carte' or writing custom modules. This paper describes the software architecture and model formulation of Switch 2.0 and provides a case study in which the model was used to identify the best options for obtaining load-shifting and reserve services from batteries and demand response in a 100% renewable power system.
- Subjects :
- Mathematics - Optimization and Control
Physics - Physics and Society
G.1.6
Subjects
Details
- Database :
- arXiv
- Journal :
- "Switch 2.0: A modern platform for planning high-renewable power systems", SoftwareX 10:10051, 2019
- Publication Type :
- Report
- Accession number :
- edsarx.1804.05481
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1016/j.softx.2019.100251