Specific energy consumption values for various refrigerated food cold stores

Two benchmarking surveys were created to collect data on the performance of chilled, frozen and mixed (chilled and frozen stores operated from a single refrigeration system) food cold stores with the aim of identifying the major factors influencing energy consumption. The volume of the cold store was found to have the greatest relationship with energy use with none of the other factors collected having any significant impact on energy use. For chilled cold stores, 93% of the variation in energy was related to store volume. For frozen stores, 56% and for mixed stores, 67% of the variation in energy consumption was related to store volume. The results also demonstrated the large variability in performance of cold stores. This was investigated using a mathematical model to predict energy use under typical cold store construction, usage and efficiency scenarios. The model demonstrated that store shape factor (which had a major impact on surface area of the stores), usage and to a lesser degree ambient temperature all had an impact on energy consumption. The work provides an initial basis to compare energy performance of cold stores and indicates the areas where considerable energy saving are achievable in food cold stores. © 2013 Elsevier B.V

Methods to assess energy usage in food cold stores

A mathematical model was applied to predict energy used by cold stores. This was compared with actual energy consumption data collected in a survey of cold stores. The model was used to investigate different usage scenarios and varied ambient conditions around the chilled and frozen cold stores. This indicated that many chilled and frozen stores had very high usage and/or inefficient refrigeration systems. Less than 13% of chilled and 12% of frozen stores used less energy than an efficiently used store with an efficient refrigeration system. The model indicated that smaller stores of less than 25,000 m3 tended to use more energy than the model predicted, even at the least efficient, highest usage scenario. With further validation the model could be used to benchmark the energy usage of cold stores and help identify where energy savings could be best achieved

Rendimiento Energético Delalmacenamiento en Frío (Cold store energy performance)

Un modelo matemático fue aplicado para predecir la energía utilizada por las cámaras frigoríficas. Esto se comparó con los datos de consumo de energía reales recogidos en un estudio de las cámaras frigoríficas. El modelo se utilizó para investigar diferentes escenarios de uso y variadas condiciones ambientales alrededor de las cámaras frigoríficas refrigeradas y congeladas. Esto indica que muchos almacenes refrigerados y congelados tenían un uso muy alto y/o sistemas de refrigeración ineficientes. Menos de un 13% de enfriado y un 12% de congelado de los almacenes utilizó menos energía que un almacén que utilizó de manera eficiente un sistema de refrigeración eficiente. El modelo indica que los almacenes pequeños de menos de 25.000 m3 tendían a usar más energía que el modelo predicho, incluso en el más alto escenario de uso menos eficiente. Con una otra validación el modelo podría ser utilizado para comparar el uso de la energía de las cámaras frigoríficas y ayudar a identificar dónde el ahorro de energía pueda conseguirse mejor

Métodos para evaluar el uso de energía en los almacenes frigoríficos para alimentos (Methods to assess energy usage in food cold stores)

Un modelo matemático fue aplicado para predecir la energía utilizada por las cámaras frigoríficas. Esto se comparó con los datos de consumo de energía reales recogidos en un estudio de las cámaras frigoríficas. El modelo se utilizó para investigar diferentes escenarios de uso y variadas condiciones ambientales alrededor de las cámaras frigoríficas refrigeradas y congeladas. Esto indica que muchos almacenes refrigerados y congelados tenían un uso muy alto y/o sistemas de refrigeración ineficientes. Menos de un 13% de enfriado y un 12% de congelado de los almacenes utilizó menos energía que un almacén que utilizó de manera eficiente un sistema de refrigeración eficiente. El modelo indica que los almacenes pequeños de menos de 25000 m3 tendían a usar más energía que el modelo predicho, incluso en el más alto escenario de uso menos eficiente. Con otra validación el modelo podría ser utilizado para comparar el uso de la energía de las cámaras frigoríficas y ayudar a identificar dónde el ahorro de energía pueda conseguirse mejor. Métodos para evaluar el uso de energía en los almacenes frigoríficos para alimentos / Methods to assess energy usage in food cold stores. Available from: https://www.researchgate.net/publication/293592225_Metodos_para_evaluar_el_uso_de_energia_en_los_almacenes_frigorificos_para_alimentos_Methods_to_assess_energy_usage_in_food_cold_stores [accessed May 22, 2017]

Cold store energy performance

Considerable energy savings can be achieved in cold stores and cold store users are extremely keen to identify these savings as energy is a major cost in the operation of any sized cold store. Work within the ICE-E (Improving Cold storage Equipment in Europe) project examined methods to reduce energy use in cold stores. Results from 28 cold store audits carried out across Europe are presented. Common faults and issues are discussed and methods to improve performance elaborated. The potential for large energy savings of at minimum 8% and at maximum 72% were identified by optimising usage of stores, repairing current equipment and by retrofitting of energy efficient equipment. Often these improvements had short payback times of less than 1 year

Methods to assess energy usage in food cold stores

A mathematical model was applied to predict energy used by cold stores. This was compared with actual energy consumption data collected in a survey of cold stores. The model was used to investigate different usage scenarios and varied ambient conditions around the chilled and frozen cold stores. This indicated that many chilled and frozen stores had very high usage and/or inefficient refrigeration systems. Less than 13% of chilled and 12% of frozen stores used less energy than an efficiently used store with an efficient refrigeration system. The model indicated that smaller stores of less than 25,000 m3 tended to use more energy than the model predicted, even at the least efficient, highest usage scenario. With further validation the model could be used to benchmark the energy usage of cold stores and help identify where energy savings could be best achieved

Specific energy consumption values for various refrigerated food cold stores

Two benchmarking surveys were created to collect data on the performance of chilled, frozen and mixed (chilled and frozen stores operated from a single refrigeration system) food cold stores with the aim of identifying the major factors influencing energy consumption. The volume of the cold store was found to have the greatest relationship with energy use with none of the other factors collected having any significant impact on energy use. For chilled cold stores, 93% of the variation in energy was related to store volume. For frozen stores, 56% and for mixed stores, 67% of the variation in energy consumption was related to store volume. The results also demonstrated the large variability in performance of cold stores. This was investigated using a mathematical model to predict energy use under typical cold store construction, usage and efficiency scenarios. The model demonstrated that store shape factor (which had a major impact on surface area of the stores), usage and to a lesser degree ambient temperature all had an impact on energy consumption. The work provides an initial basis to compare energy performance of cold stores and indicates the areas where considerable energy saving are achievable in food cold stores

Can qualitatively similar temperature-histories be obtained in different pilot HP units?

An experimental protocol to harmonize the pressure and temperature-histories of model samples treated in different individual high pressure pilot units was developed. This protocol was based on the endpoint strategy. Step zero of this protocol consisted of an exploratory measurement of the pressure, temperature-history of the pressure transmitting medium in the different chambers without the use of a container. In steps one and two of the protocol, the temperature of a sample was measured, which was placed in a container. Two types of samples were considered, a pure water sample allowing free convection (step 1) and a viscous water-based system (using a water soluble thickener) preventing free convection in the sample container (step 2). The high pressure units differed primarily in pressure build-up and pressure release times. The suggested endpoint strategy enabled the minimization of differences in temperature-histories during the pressure holding phase. Pressure, temperature-histories measured in the different high pressure units and information on the inactivation kinetics of a-amylase based systems were used to compare the process impact of different pressure, temperature-histories on the enzyme inactivation. The differences in temperature-histories significantly influenced the degree of enzyme inactivation; in particular the temperature-histories during the pressure build-up phase substantially contributed to differences in residual enzyme activity