Modelização de sistemas de gestão de energia em ambiente

Este trabalho propõe uma metodologia de tradução para igualar o programa de controle de PLC no ambiente Matlab/Simulink. A lista traduz automaticamente o programa de controlo de PLC para a linguagem. de software Matlab/Simulink. O programa do PlC é traduzido para uma função bloco do Matlab, dentro do ambiente Matlab/Simulink, que irá controlar o modelo do processo industrial, desde que a simulação seja executada. As entradas e saídas da lista de tradução do PLC depende do tipo de autómato que é escolhido. A lista de tradução será compatível com um ficheiro Matlab/Simulink que corresponde tradução de programa de controle de PLC. ABSTRACT: This work proposes a translation methodology to equa1 the program of control of PLC in the environment Matlab/Simulink. The list translates automatically the program of control of PLC for the language of software Matlab/Simulink. The program of the PlC is translated for a function block of the Matlab, inside the environment Matlab/Simulink, which will be going to control the model of the industrial process, since the simulation is executed. The entries and exits of the translation list of the PLC it depends on the type of automaton that is chosen. The translation list will be compatible with a filing cabinet Matlab/Simulink that corresponds translation of program of control of PLC.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.