Dynamic mixed integer nonlinear programming applied to the resolution of the optimal power flow problem incorporating the definition of sequences of control adjustments

• Grant number: 19/25104-0
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2020
• End date: July 31, 2022
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Guilherme Guimarães Lage
• Grantee: Guilherme Guimarães Lage
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated research grant(s): 24/16016-8 - LVI Brazilian Symposium on Operational Research (SBPO 2024), AR.BR

Abstract

Although Optimal Power Flow (OPF) formulations in the correlate literature focus on "solely" determining the optimal adjustments of power system controls, defining a sequence of control adjustments is a critical task for the practical use of OPFs in real-time optimal operation of power systems, as all control adjustments must be coordinated whilst the current operation point smoothly moves toward the optimum. Many approaches in the literature deploy local differential sensitivity analysis to define such sequence of control adjustments, however, such techniques are only effective in a neighborhood around the current operating point given the nonlinear and non convex characteristic of OPF formulations. In this context, the objective of this research project is to solve the OPF problem incorporating the definition of a sequence of control adjustments (more specifically, the optimal reactive dispatch problem for the minimization of active power losses in transmission power systems), whose formulation is methodologically founded on Mixed-Integer Dynamic Nonlinear Programming (MIDNLP) problems. For this, a review on the literature will explicit the concepts associated with resolution techniques of MIDNLP problems and continuous relaxation techniques of binary variables by penalty and/or sigmoidal functions that transform the original problem into a Nonlinear Programming (NLP) problem. The model proposed in this research project will be implemented in the AMPL environment for mathematical programming and its resolution will be carried out by commercial solvers. Numerical results for IEEE test-systems and realistic power systems whose data are available in the correlate literature will be used to validate the proposed resolution approach. (AU)

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

BARROS, RAFAEL MARTINS; LAGE, GUILHERME GUIMARAES; LIRA RABELO, RICARDO DE ANDRADE. Sequencing paths of optimal control adjustments determined by the optimal reactive dispatch via Lagrange multiplier sensitivity analysis. European Journal of Operational Research, v. 301, n. 1, p. 13-pg., 2022-08-16. (19/25104-0)

BARROS, RAFAEL MARTINS; LAGE, GUILHERME GUIMARAES; RABELO, RICARDO DE ANDRADE LIRA. Globally optimal sequencing of optimal reactive dispatch control adjustments to minimize operational losses in transmission systems by graph shortest path, parallel computing, and dynamic programming. European Journal of Operational Research, v. 320, n. 1, p. 17-pg., 2024-09-04. (19/25104-0)

BARROS, RAFAEL MARTINS; LAGE, GUILHERME GUIMARAES; LIRA RABELO, RICARDO DE ANDRADE; IEEE. Graph Shortest Path and Dynamic Programming Applied to Sequencing ORD Control Adjustments. 2023 IEEE BELGRADE POWERTECH, v. N/A, p. 6-pg., 2023-01-01. (19/25104-0)