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Advisor(s)
Abstract(s)
O sistema de refrigeração de uma loja de retalho alimentar contribui para cerca de metade de todo o consumo elétrico da loja. O seu consumo elétrico deve, por isso, ser monitorizado e o seu desempenho analisado com frequência regular a fim de avaliar a eficiência do sistema e detetar possíveis ineficiências. O trabalho realizado incidiu na otimização de um simulador energético utilizado nessa avaliação de eficiência. O simulador, que calcula o consumo elétrico expectável de um sistema de refrigeração e o compara ao valor real através de indicadores de benchmarking, carecia de duas otimizações a fim de aproximar o consumo calculado ao valor real. A primeira prendia-se com a correção climática do consumo expectável, enquanto a segunda dizia respeito à correção da eficiência dos compressores no cálculo do consumo no simulador. O consumo elétrico expectável é calculado com um clima padrão médio correspondente à localização geográfica da loja em avaliação. Como o clima utilizado é distinto do clima real, que varia de ano para ano, foi proposto o desenvolvimento de uma ferramenta para a correção climática do consumo calculado. Para estudar e identificar o processo de correção mais indicado para a construção da ferramenta, foram selecionadas três lojas reais que serviram de casos de estudo. A correção do consumo foi realizada com dados climáticos em formatos diferentes, ou seja, temperatura diária, temperatura mensal, GD diários e GD mensais. Pretendia-se, assim, identificar, caso fosse possível, um que se destacasse dos restantes para ser empregue em futuras análises mais práticas. Uma vez concluída, a ferramenta de correção climática foi validada aplicando- -a uma loja real. A eficiência dos equipamentos decresce ao longo do tempo de utilização. No entanto, para efeitos de cálculo, o simulador considerava a eficiência nominal dos compressores. Assim, foi necessário penalizar a eficiência dos compressores aplicando um fator de correção que contabilizasse o tempo de funcionamento dos mesmos. Concluiu-se que a correção climática pode auxiliar na aproximação do consumo expectável ao consumo real. A taxa de sucesso verificada nos indicadores de benchmarking expectável foi de cerca de 68,8%. Não obstante, constatou-se que o impacto do clima no consumo elétrico de um sistema de refrigeração não é de grande magnitude. A correção climática nas quatro lojas reais permitiu a redução do desvio máximo entre os consumos expectável e real de 11,3% para 8,5%, aproximadamente.
The refrigeration system in a food retail store contributes to about half of the store's entire electrical consumption. Its electrical consumption should therefore be monitored and its performance analysed regularly in order to assess the system’s efficiency and detect possible inefficiencies. The work carried out focused on the optimization of an energy simulator used in that efficiency assessment. The simulator, which calculates the expected electrical consumption of a refrigeration system and compares it to the actual value through benchmarking indicators, lacked two optimizations to approximate the calculated consumption to the actual value. The first was related to the climatic correction of the expected consumption, while the second concerned the correction of the compressor efficiency in the consumption calculation in the simulator. The expected electrical consumption is calculated with an average standard climate corresponding to the geographic location of the store under evaluation. As the climate used is distinct from the actual climate, which varies from year to year, it was proposed the development of a tool for the calculated consumption climate correction. To study and identify the most suitable correction process for the tool’s construction, three real stores were selected to serve as case studies. The consumption correction was carried out with climatic data in different formats, i.e., daily temperature, monthly temperature, daily CDD and monthly CDD. It was intended, therefore, to identify, if possible, one that stood out from the rest to be used in future more practical analyses. Once completed, the climate correction tool was validated by applying it to a real store. Equipment efficiency decreases over the time of use. However, for calculation purposes, the simulator considered the nominal efficiency of the compressors. Thus, it was necessary to penalize the efficiency of the compressors by applying a correction factor that would account for their operating time. It was concluded that the climate correction can help in the approximation of the expected consumption to the real consumption. The success rate observed in the expected benchmarking indicators was about 68.8%. Nevertheless, it was found that the climate’s impact on the electrical consumption of a refrigeration system is not of great magnitude. The climate correction in the four real stores allowed the reduction of the maximum deviation between expected and real consumption from 11.3% to 8.5%, approximately.
The refrigeration system in a food retail store contributes to about half of the store's entire electrical consumption. Its electrical consumption should therefore be monitored and its performance analysed regularly in order to assess the system’s efficiency and detect possible inefficiencies. The work carried out focused on the optimization of an energy simulator used in that efficiency assessment. The simulator, which calculates the expected electrical consumption of a refrigeration system and compares it to the actual value through benchmarking indicators, lacked two optimizations to approximate the calculated consumption to the actual value. The first was related to the climatic correction of the expected consumption, while the second concerned the correction of the compressor efficiency in the consumption calculation in the simulator. The expected electrical consumption is calculated with an average standard climate corresponding to the geographic location of the store under evaluation. As the climate used is distinct from the actual climate, which varies from year to year, it was proposed the development of a tool for the calculated consumption climate correction. To study and identify the most suitable correction process for the tool’s construction, three real stores were selected to serve as case studies. The consumption correction was carried out with climatic data in different formats, i.e., daily temperature, monthly temperature, daily CDD and monthly CDD. It was intended, therefore, to identify, if possible, one that stood out from the rest to be used in future more practical analyses. Once completed, the climate correction tool was validated by applying it to a real store. Equipment efficiency decreases over the time of use. However, for calculation purposes, the simulator considered the nominal efficiency of the compressors. Thus, it was necessary to penalize the efficiency of the compressors by applying a correction factor that would account for their operating time. It was concluded that the climate correction can help in the approximation of the expected consumption to the real consumption. The success rate observed in the expected benchmarking indicators was about 68.8%. Nevertheless, it was found that the climate’s impact on the electrical consumption of a refrigeration system is not of great magnitude. The climate correction in the four real stores allowed the reduction of the maximum deviation between expected and real consumption from 11.3% to 8.5%, approximately.
Description
Keywords
Refrigeração Eficiência energética Benchmarking energético Lojas de retalho alimentar Correção climática Refrigeration Energy efficiency Energy benchmarking Food retail stores Climatic correction