MATPOWER Optimal Scheduling Tool (MOST) User's Manual

Autor: Zimmerman, Ray D., Murillo-Sánchez, Carlos E.
Jazyk: angličtina
Rok vydání: 2019
Předmět:
DOI: 10.5281/zenodo.3251047
Popis: This is the User's Manual for the MATPOWER Optimal Scheduling Tool (MOST), a framework for solving generalized steady-state electric power scheduling problems. MOST can be used to solve problems as simple as a deterministic, single period economic dispatch problem with no transmission constraints or as complex as a stochastic, security-constrained, combined unit-commitment and multiperiod optimal power flow problem with locational contingency and load-following reserves, ramping costs and constraints, deferrable demands, lossy storage resources and uncertain renewable generation. While the problem formulation is general and incorporates a full nonlinear AC network model, the current implementation is limited to DC power flow modeling of the network. Some work has been done on an AC implementation, but it is not yet ready for release. The primary developers of MOST are Carlos E. Murillo-Sanchez and Ray D. Zimmerman, with significant contributions from Daniel Munoz-Alvarez and Alberto J. Lamadrid. It is built on top of MATPOWER, a package of MATLAB/Octave M-files for solving power flow and optimal power flow problems.
{"references":["R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, \"MATPOWER: Steady-State Operations, Planning and Analysis Tools for Power Systems Research and Education,\" Power Systems, IEEE Transactions on, vol. 26, no. 1, pp. 12–19, Feb. 2011. doi: 10.1109/TPWRS.2010.2051168.","C. E. Murillo-Sanchez, R. D. Zimmerman, C. L. Anderson, and R. J. Thomas, \"Secure Planning and Operations of Systems with Stochastic Sources, Energy Storage and Active Demand,\" Smart Grid, IEEE Transactions on, vol. 4, no. 4, pp. 2220–2229, Dec. 2013. doi: 10.1109/TSG.2013.2281001.","A. J. Lamadrid, D. Munoz-Alvarez, C. E. Murillo-Sanchez, R. D. Zimmerman, H. D. Shin and R. J. Thomas, \"Using the MATPOWER Optimal Scheduling Tool to Test Power System Operation Methodologies Under Uncertainty,\" Sustainable Energy, IEEE Transactions on, 2018. doi: 10.1109/TSTE.2018.2865454."]}
Databáze: OpenAIRE
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