Abstract
The power system static operation planning has a main objective the determination of performance strategies which satisfy operational criteria. A fuzzy set decision model which takes the load attainment and the compromise between optimality and critical operational constraints into account is presented. The prime characteristic of this methodology is the incorporation of the planner`s preferences structure in a decision process modeled by fuzzy sets. A routine of optimal power flow calculation is used as a computational tool for solving the nonlinear model of the electric power system and for defining the universe of discourse of the decision-making problem. tests were carried on a 30-bus IEEE system in order to find a compromise solution of electric operational goal versus reactive power generation limits. Results and conclusions are presented. (author) 28 refs., 32 figs.
Citation Formats
Valenca, Mauricio Mendonca.
A fuzzy set decision making model applied to electric power systems operation planning; Um modelo de decisao baseado em conjuntos nebulosos aplicado ao planejamento da operacao de sistemas de energia eletrica.
Brazil: N. p.,
1993.
Web.
Valenca, Mauricio Mendonca.
A fuzzy set decision making model applied to electric power systems operation planning; Um modelo de decisao baseado em conjuntos nebulosos aplicado ao planejamento da operacao de sistemas de energia eletrica.
Brazil.
Valenca, Mauricio Mendonca.
1993.
"A fuzzy set decision making model applied to electric power systems operation planning; Um modelo de decisao baseado em conjuntos nebulosos aplicado ao planejamento da operacao de sistemas de energia eletrica."
Brazil.
@misc{etde_335560,
title = {A fuzzy set decision making model applied to electric power systems operation planning; Um modelo de decisao baseado em conjuntos nebulosos aplicado ao planejamento da operacao de sistemas de energia eletrica}
author = {Valenca, Mauricio Mendonca}
abstractNote = {The power system static operation planning has a main objective the determination of performance strategies which satisfy operational criteria. A fuzzy set decision model which takes the load attainment and the compromise between optimality and critical operational constraints into account is presented. The prime characteristic of this methodology is the incorporation of the planner`s preferences structure in a decision process modeled by fuzzy sets. A routine of optimal power flow calculation is used as a computational tool for solving the nonlinear model of the electric power system and for defining the universe of discourse of the decision-making problem. tests were carried on a 30-bus IEEE system in order to find a compromise solution of electric operational goal versus reactive power generation limits. Results and conclusions are presented. (author) 28 refs., 32 figs.}
place = {Brazil}
year = {1993}
month = {May}
}
title = {A fuzzy set decision making model applied to electric power systems operation planning; Um modelo de decisao baseado em conjuntos nebulosos aplicado ao planejamento da operacao de sistemas de energia eletrica}
author = {Valenca, Mauricio Mendonca}
abstractNote = {The power system static operation planning has a main objective the determination of performance strategies which satisfy operational criteria. A fuzzy set decision model which takes the load attainment and the compromise between optimality and critical operational constraints into account is presented. The prime characteristic of this methodology is the incorporation of the planner`s preferences structure in a decision process modeled by fuzzy sets. A routine of optimal power flow calculation is used as a computational tool for solving the nonlinear model of the electric power system and for defining the universe of discourse of the decision-making problem. tests were carried on a 30-bus IEEE system in order to find a compromise solution of electric operational goal versus reactive power generation limits. Results and conclusions are presented. (author) 28 refs., 32 figs.}
place = {Brazil}
year = {1993}
month = {May}
}