Browsing by Author "Zheiry, Modar"
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- Air Conditioning Consumption Optimization Based on CO2 Concentration LevelPublication . Khorram Ghahfarrokhi, Mahsa; Zheiry, Modar; Faria, Pedro; Vale, ZitaNowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios.
- Application of demand response programs for peak reduction using load aggregatorPublication . Zheiry, Modar; Vale, Zita Maria Almeida doO aumento do consumo de energia requer atenção. Os especialistas propuseram muitas soluções para otimizar o uso de energia e propõem um sistema de gestão de energia eficiente. No entanto, desenvolver um sistema de energia que contempla agregadores de carga é óbvio para aprimorar o processo de gestão de energia. Este trabalho discute um sistema de gestão de energia para implementar programas de Demand Response (DR) usando abordagens de agregação de carga. Neste trabalho, dois estudos de caso comparam as diferentes respostas do sistema. O objetivo principal é discutir o papel de diferentes modelos de agregador de carga no sistema de energia, implementando um programa de DR. Esses agregadores de carga controlam diferentes tipos de cargas. Neste contexto, vários tipos de cargas domésticas são consideradas cargas controláveis. No processo de agregação, o objetivo é agregar as cargas que possuem as mesmas características usando a análise de agrupamento das cargas. A contribuição científica desta dissertação está relacionada com a redução da ponta e a agregação de cargas, considerando as cargas controláveis e os recursos de geração no sistema. Para atingir o objetivo anterior, foram realizados dois estudos de caso. Cada estudo de caso consiste em três cenários baseados no modelo de agregação de carga. Os resultados dos estudos indicam as respostas do sistema aos diferentes cenários e ilustram os méritos do modelo de agregador de carga. Além disso, os resultados demonstram como o agrupamento dos dispositivos de carga no sistema pode efetivamente fornecer redução de pico com recurso a programas de DR.
- Energy Consumption Management in Buildings in the Context of Voluntary and Mandatory Demand Response Programs in Smart GridsPublication . Khorram Ghahfarrokhi, Mahsa; Zheiry, Modar; Faria, Pedro; Vale, ZitaEnergy consumption is increasing around the world and has been made many consequences such as increasing greenhouse emissions, global warming, and climate changes. Demand response programs can be considered as techniques to manage and control electricity consumption based on user flexibility. There are several types of demand response programs that are categorized in price-based programs and incentive-based programs. This paper analyzes real demand response implementations according to a dataset provided by the Federal Energy Regulatory Commission. Real demand response programs are analyzed based on customer type, program type, potential and capability of the programs, and controllable loads. In the case study, an optimization approach is proposed to control the loads and achieve the power reduction goals of the demand response programs. The obtained results show how buildings can be participants in demand response programs, choosing the more advantageous program.