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Abstract(s)
As companhias de retalho alimentar têm vindo a aumentar os seus portfólios de lojas de forma relevante, enquanto cresce a necessidade de garantir que as lojas são operadas da forma mais eficiente possível. Com portfólios tão grandes, é imperiosa a utilização de ferramentas que permitam comparar o desempenho energético das lojas. Este tipo de ferramentas, quando bem desenvolvidas, devem permitir identificar de forma simples mas fiável, as lojas com pior desempenho energético (de forma a que o mesmo seja corrigido), as lojas com bom desempenho energético (de forma a migrar as boas práticas para o restante portfólio) bem como as lojas com sistemas instalados menos eficazes, para as quais devem ser canalizados os esforços de investimento em eficiência energética da companhia. Diversas vezes este tipo de comparação de grandes portfólios é feito recorrendo a indicadores simplistas, como os consumos por área (kWh/m2 ). Estes indicadores, têm a vantagem de serem simples, mas escondem diversas imperfeições que podem induzir conclusões erradas quanto ao desempenho, como efeitos climáticos, horário de abertura ao público, sistema de AVAC instalado, entre outros. Assim, surge o conceito de benchmarking operacional, como um contributo para uma comparação de diversos edifícios de uma forma mais "justa". Trata-se de um indicador de desempenho energético que é calculado através da comparação entre o consumo real de uma determinada loja (faturas) e o consumo expectável para essa mesma loja, considerando inputs como o seu clima, horário de abertura ao público, dimensões e sistemas instalados. Para tal, é indispensável avaliar quais os sistemas energéticos relevantes, caracterizá-los corretamente e calcular os respetivos consumos expectáveis (targets). A generalidade dos consumos energéticos expectáveis foi calculada recorrendo a um software de simulação energética detalhada de edifícios. Assim, este trabalho teve como principal objetivo desenvolver uma ferramenta de benchmarking do desempenho dos principais sistemas energéticos existentes num hipermercado, a fim de detetar eventuais situações de ineficiência e permitir a sua correção. Essa ferramenta de cálculo foi posteriormente implementada para cinco casos reais (cinco lojas de retalho alimentar). Desta forma, foi possível desenvolver o benchmarking operacional e retirar conclusões acerca do desempenho global das lojas reais. Foi possível concluir que todas as lojas analisadas apresentavam problemas de eficiência e/ou controlo no sistema de AVAC. Das lojas reais analisadas apenas uma se encontrava dentro do consumo expectável obtendo um benchmarking operacional de 0,95. Esta ferramenta foi e é útil na identificação das ineficiências operacionais das lojas estudadas o que, de outra forma, não seria possível verificar.
Além disso, esta ferramenta permitiu também uma análise detalhada do desempenho dos principais sistemas energéticos, o que poderá ser extremamente útil, não só para identificar quais serão as “melhores práticas”, mas também para detetar rapidamente quais os componentes que apresentam situações de ineficiência, de forma a conseguir corrigi-las de forma célere e eficaz.
Food retail companies have been significantly increasing their store portfolios, while the need to ensure that stores are operated in the most efficient way possible is growing. With such large portfolios, it is imperative to use tools that make it possible to compare the energy performance of stores. This type of tools, when well developed, should allow to identify in a simple but reliable way, the stores with the worst energy performance (so that it is corrected), the stores with good energy performance (in order to migrate good practices to the rest of the portfolio), as well as stores with less efficient installed systems, to which the company's energy efficiency investment efforts should be channeled. This type of comparison of large portfolios is often made using simplistic indicators, such as consumption by area (kWh/m2 ). These indicators have the advantage of being simple, but they hide several imperfections that can induce wrong conclusions regarding performance, such as climatic effects, opening hours to the public, HVAC system installed, among others. In this way, the concept of operational benchmarking emerges, as a contribution to a comparison of several buildings in a “fairer” way. This’s an energy performance indicator that’s calculated by comparing the actual consumption of a given store (invoices) and the expected consumption for that store, considering inputs such as its climate, opening hours to the public, dimensions and installed systems. To this end, it is essential to assess which energy systems are relevant, characterize them correctly and calculate the respective expected consumption (targets). Note that most expected consumption is calculated using detailed building energy simulation software. So, this work had as main objective to develop a benchmarking tool for the performance of the main energy systems existing in a hypermarket, in order to detect eventual inefficiency situations and allow their correction. This calculation tool was subsequently implemented for five real cases (five food retail stores). In this way, it was possible to develop a operational benchmarking and remove the overall performance of real stores. It was possible to conclude that all the analyzed stores had problems of efficiency and/or control in the HVAC system. Of the actual stores analyzed only one was in the expected consumption, obtaining an operational benchmarking of 0,95. This tool was and is useful in identifying operational inefficiencies in the stores studied or that, otherwise, it is not seriously possible to verify. In addition, this tool also allowed a detailed analysis of the performance of the main energy systems, which can be extremely useful, not only to identify which are the “best practices”, but also to quickly detect which components present inefficient situations, in order to be able to correct them quickly and effectively.
Food retail companies have been significantly increasing their store portfolios, while the need to ensure that stores are operated in the most efficient way possible is growing. With such large portfolios, it is imperative to use tools that make it possible to compare the energy performance of stores. This type of tools, when well developed, should allow to identify in a simple but reliable way, the stores with the worst energy performance (so that it is corrected), the stores with good energy performance (in order to migrate good practices to the rest of the portfolio), as well as stores with less efficient installed systems, to which the company's energy efficiency investment efforts should be channeled. This type of comparison of large portfolios is often made using simplistic indicators, such as consumption by area (kWh/m2 ). These indicators have the advantage of being simple, but they hide several imperfections that can induce wrong conclusions regarding performance, such as climatic effects, opening hours to the public, HVAC system installed, among others. In this way, the concept of operational benchmarking emerges, as a contribution to a comparison of several buildings in a “fairer” way. This’s an energy performance indicator that’s calculated by comparing the actual consumption of a given store (invoices) and the expected consumption for that store, considering inputs such as its climate, opening hours to the public, dimensions and installed systems. To this end, it is essential to assess which energy systems are relevant, characterize them correctly and calculate the respective expected consumption (targets). Note that most expected consumption is calculated using detailed building energy simulation software. So, this work had as main objective to develop a benchmarking tool for the performance of the main energy systems existing in a hypermarket, in order to detect eventual inefficiency situations and allow their correction. This calculation tool was subsequently implemented for five real cases (five food retail stores). In this way, it was possible to develop a operational benchmarking and remove the overall performance of real stores. It was possible to conclude that all the analyzed stores had problems of efficiency and/or control in the HVAC system. Of the actual stores analyzed only one was in the expected consumption, obtaining an operational benchmarking of 0,95. This tool was and is useful in identifying operational inefficiencies in the stores studied or that, otherwise, it is not seriously possible to verify. In addition, this tool also allowed a detailed analysis of the performance of the main energy systems, which can be extremely useful, not only to identify which are the “best practices”, but also to quickly detect which components present inefficient situations, in order to be able to correct them quickly and effectively.
Description
Keywords
Benchmarking Eficiência energética Consumo elétrico Lojas de retalho alimentar Energy efficiency Electric consumption Food retail buildings