Energy Consumption Benchmarks Research Articles

Energy-Efficient Clusters for Object Tracking Networks

Smart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object tracking device, on a corner at an intersection for example has a limited scope of view, so more object tracking devices are added to broaden the view. As an increasing number of object tracking devices are constructed on streets, their efficient energy consumption becomes a significant issue. This work is concerned with decreasing the energy required to power these systems, and proposes energy-efficient clusters (EECs) of object tracking systems to achieve energy savings. First, we analyze a current object tracking system to establish an equivalent model. Second, we arrange the object tracking system in a cluster structure, which facilitates the evaluation of energy costs. Third, the energy consumption is assessed as either dynamic or static, which is a more accurate system for determining energy consumption. Fourth, we analyze all possible scenarios of the object’s location and the resulting energy consumption, and derive a number of formulas for the fast computation of energy consumption. Finally, the simulation results are reported. These results show the proposed EEC is an effective way to save energy, compared with the energy consumption benchmarks of current technology.

Benchmarking energy performance for cooling in large commercial buildings

Urban development rapidly increases the total area and the energy consumption of large commercial buildings. Accordingly, the total energy consumption is the focus of numerous energy saving studies. An optimal benchmarking system provides a recommended energy consumption level for each building as well as identifying and prioritizing challenges to energy saving in each building. Based on detailed sub-metering system data and building operational data, this paper presents a simplified energy consumption benchmarking method for air-conditioning systems that cool large commercial buildings. Firstly, a multi-level benchmarking index system is established. Next, the energy performance data of eight large shopping centers in China validates the simplified benchmarking method and finally, the energy performance data of the participating shopping centers is analyzed under the present method. Our data focus on the energy saving potential, as well as informing improvement strategies for building energy performance, that can be used for efficient energy benchmarking process for cooling in large-scale commercial buildings.

Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings

Energy conservation in residential buildings has gained increased attention due to its large portion of global energy use and potential of energy savings. Occupant behavior has been recognized as a key factor influencing the energy use and load diversity in buildings, therefore more realistic and accurate air-conditioning (AC) operating schedules are imperative for load estimation in equipment design and operation optimization. With the development of sensor technology, it became easier to access an increasing amount of heating/cooling data from thermal energy metering systems in residential buildings, which provides another possible way to understand building energy usage and occupant behaviors. However, except for cooling energy consumption benchmarking, there currently lacks effective and easy approaches to analyze AC usage and provide actionable insights for occupants. To fill this gap, this study proposes clustering analysis to identify AC use patterns of residential buildings, and develops new key performance indicators (KPIs) and data analytics to explore the AC operation characteristics using the long-term metered cooling energy use data, which is of great importance for inhabitants to understand their thermal energy use and save energy cost through adjustment of their AC use behavior. We demonstrate the proposed approaches in a residential district comprising 300 apartments, located in Zhengzhou, China. Main outcomes include: Representative AC use patterns are developed for three room types of residential buildings in the cold climate zone of China, which can be used as more realistic AC schedules to improve accuracy of energy simulation; Distributions of KPIs on household cooling energy usage are established, which can be used for household AC use intensity benchmarking and performance diagnoses.

Benchmarking of energy consumption in municipal wastewater treatment plants - a survey of over 200 plants in Italy.

One of the largest surveys in Europe about energy consumption in Italian wastewater treatment plants (WWTPs) is presented, based on 241 WWTPs and a total population equivalent (PE) of more than 9,000,000 PE. The study contributes towards standardised resilient data and benchmarking and to identify potentials for energy savings. In the energy benchmark, three indicators were used: specific energy consumption expressed per population equivalents (kWh PE-1 year-1), per cubic meter (kWh/m3), and per unit of chemical oxygen demand (COD) removed (kWh/kgCOD). The indicator kWh/m3, even though widely applied, resulted in a biased benchmark, because highly influenced by stormwater and infiltrations. Plants with combined networks (often used in Europe) showed an apparent better energy performance. Conversely, the indicator kWh PE-1 year-1 resulted in a more meaningful definition of a benchmark. High energy efficiency was associated with: (i) large capacity of the plant, (ii) higher COD concentration in wastewater, (iii) separate sewer systems, (iv) capacity utilisation over 80%, and (v) high organic loads, but without overloading. The 25th percentile was proposed as a benchmark for four size classes: 23 kWh PE-1 y-1 for large plants > 100,000 PE; 42 kWh PE-1 y-1 for capacity 10,000 < PE < 100,000, 48 kWh PE-1 y-1 for capacity 2,000 < PE < 10,000 and 76 kWh PE-1 y-1 for small plants < 2,000 PE.

Introducing innovative energy performance metrics for high-level monitoring and diagnosis of telecommunication sites

This paper aims at deepening the theme of monitoring and energetic diagnosis of telecommunication (TLC) central offices, via the development and application of innovative performance parameters, whose objective is to detect the presence of anomalous energy absorption of the electronic equipment and cooling systems. Firstly, extensive energy analysis is conducted by using the heating degree days (HDD) parameter, which is already consolidated in the field of efficient thermal management of data-centers. Secondly, properly designed indicators are added to this metric: the parameter of central utilization (PUC), which allows distinguishing the multi-use (e.g. combined TLC rooms and offices) from pure central offices; the index of cluster reliability (ICR), which evaluates the stability in time of the acquired data, and the reliability index (RI). The last parameter was specifically introduced to assess if a data center exhibits an unusual energy behavior with respect to a reference energy consumption benchmark, here defined for the group the site belongs to. The innovative contribution of the paper lies in the introduction and joint use of ICR and RI parameters, which can be set up as an effective diagnostic tool for telecommunications sites. The combined verification of current ICR and RI values allows outlining four possible scenarios, differentiated on the basis of the data reliability. Particularly, immediate determination of reliable and unreliable TLC sites is enabled, while the diagnostic potential is exploited to determine whether deeper investigation of energetic consumption trajectories is required. Specifically, the joint assessment of the ICR-RI pair was successfully applied to detecting the presence of anomalous TLC and cooling energy consumption data, as well as whether these abnormalities were due to inefficient thermal management or sensor malfunctioning.

A methodology for estimating office building energy use baselines by means of land use legislation and reference buildings

Understanding the energy demand of cities is a challenge especially in countries such as Brazil where the lack of building energy consumption benchmarks makes it hard to decide upon interventions in the building stock, as neither the existing nor the attainable energy performance are known. Aiming to overcome these difficulties this study develops a framework to estimate the Energy Use Intensity (EUI) baseline of an existing building stock category based on the investigation of land use regulations, a land tax database and field surveys. These offer a starting point to estimate current energy consumption and promising interventions without having to study specific buildings in depth. A case study of the high-rise commercial building stock took place in the city of Belo Horizonte, Brazil. Three representative typologies were identified. For each of these, archetype energy models were created in order to assess EUI. The analysis of the EUI baselines highlights differences between archetypes, explaining the impact of technical choices on the overall electricity consumption and indicating a growing tendency of energy consumption for forthcoming buildings. The archetype analysis also provides knowledge to identify the most promising energy savings potential and thus to support further energy policies in the city.

Resource and Energy Efficiency in Small and Medium Breweries

Resource and energy efficiency in industrial production is promoted within the European Union. For small and medium size companies, resource and energy efficiency is significant for improving both the economic and environmental performance of a company. For benchmarking and the identification of potential improvements, relevant data must be collected and comparative analysis is necessary. Since the business world is driven by competitiveness, the comparison of resource and energy efficiency in companies can motivate investments in economically and environmentally beneficial improvements. Current data and benchmarks on both energy and resource efficiency should be constantly updated. The aim of this study is to analyze and compare with benchmarks the energy and resource efficiency in the brewery sector in Latvia. To promote the approach to apply national reference data, the resource and energy consumption data is collected from four Latvian small and medium size breweries. The data were acquired on-site during personal meetings with representatives of all four breweries. Based on empirical data from breweries, specific energy, resource and water consumption indicators were calculated and normalized by production amount to compare the performance of breweries. A linear regression analysis was performed to assess how the specific factors impact the overall energy consumption. The results show that all case breweries exceed the available energy consumption benchmarks, but some of them can achieve the malt and water consumption benchmarks. The comparison of these companies, although they are of quite similar in size, shows that many more factors, other than production capacity, influence their specific resource and energy consumption. The developed linear regression models of the company's energy consumption can further be used as tools for predicting energy consumption based on those individual factors that are more significant for each of the companies.

An Optimization Study on Energy Consumption Benchmarks for Boilers and Their Auxiliary Systems

An Optimization Study on Energy Consumption Benchmarks for Boilers and Their Auxiliary Systems

Daily energy consumption signatures and control charts for air-conditioned buildings

Energy signatures for air conditioning systems can have characteristics which are not seen with heating systems. This paper explains and illustrates some of the characteristics that are specific to air conditioning systems and describes how energy signatures that take account of them can be applied to produce benchmarks, control charts and diagnostic information. It focusses on the use of energy signatures derived from measured daily system energy consumption.Daily energy signatures can generate more robust energy consumption benchmarks and provide additional insight into unusual energy demand patterns compared to monthly or weekly signatures, albeit requiring slightly more data. In particular, they distinguish between weekday and weekend consumptions. They can be used to generate benchmarks based on standardised annual consumption or standardised annual load factor. In addition they can be used to generate control charts to identify days of unusual consumption for individual systems. More sets of daily energy consumption data are needed to evaluate their diagnostic power.

Shorter hash-based signatures

We describe an efficient hash-based signature scheme that yields shorter signatures than the state of the art. Signing and verification are faster as well, and the overall scheme is suitable for constrained platforms typical of the Internet of Things. We describe an efficient implementation of our improved scheme and show memory, time, and energy consumption benchmarks over a real device, i.e. the ATmega128l 8-bit AVR microcontroller embedded in MICAz, a typical sensor node used in wireless sensor networks.

Developing energy consumption benchmarks for buildings: Bank branches in Brazil

The energy consumption of buildings is an area of increasing importance, and developing economies like Brazil must start to consider the energy performance of existing buildings. The publication of national energy benchmarks is a fundamental step for understanding energy consumption in commercial buildings and developing energy efficiency programmes. A voluntary data gathering initiative by the Brazilian Sustainable Construction Council (CBCS) is producing the data necessary to develop national benchmarks. A methodology for benchmark development is proposed, using both statistical data and energy audit data to benchmark end-use energy consumption, with the use of wet-bulb cooling degree hours for climate correction. Benchmarks and climate corrections are developed for the energy consumption of bank branches in Brazil. A simple linear regression analysis of data from 1890 bank branches in 57 different climates provides the energy consumption benchmark, while thermal simulation of building performance is used to validate the results and provide an end-use breakdown in the different climates studied. This work provides the foundation for further work to develop and publish national benchmarks in other typologies.

Method for rating energy performance of public buildings

This paper discussed a comparative study of several state-of-art methods for determining building energy consumption benchmark. A new approach, which combined the idea of “building benchmark” and “operational benchmark” in its rating system, was proposed. A case study was conducted which applied the proposed approach to benchmarking an existing office building in Tianjin. Besides, the calculation of benchmarks of the reference building model and real building model using the rating method in eQUEST was also considered. Furthermore, the simulation results of the reference building model were taken as the baseline to divide real office buildings into different energy performance grades.

Knowledge is Power: Benchmarking and prediction of building energy consumption

Knowledge is Power: Benchmarking and prediction of building energy consumption

Benchmarking Energy Efficiency by ′Space Type′: An Energy Management Tool for Individual Departments Within Universities

′Energy management′ is a challenging task for individual departments within universities, especially when several departments occupy the same facility. To assist individual departments in dealing with the complex energy management topics, this study aims to establish the Benchmarking Energy Efficiency by Space Type (BEEST) method. The BEEST is developed around the core concept of ′space type′. It is proposed that the spaces within a department be categorized into several ′space types′; and for each space type, its ′standard operation settings′ be defined to further estimate the ′standard energy consumption′ for the department, with energy prediction module such as eQuest, as its energy consumption benchmark. The energy efficiency index of a department and its facility can then be assessed by comparing its ′actual energy consumption′ against the estimated ′standard energy consumption. The problem areas can be identified and energy saving action plans recommended by conducting further analyses, such as energy analyses by space types, floors, and equipment types as well as sensitivity analyses of the energy reduction effects of various ′standard settings′. The Department of Architecture of the national university NTUST in Taiwan is used as a case to demonstrate how the BEEST functions as an effective energy management tool.

Benchmarking small power energy consumption in office buildings in the United Kingdom: A review of data published in CIBSE Guide F

CIBSE’s Guide F is a widely recognised guidance document on energy efficiency in buildings, which includes energy consumption benchmarks for small power equipment in offices. In its recently published 3rd edition, existing power demand benchmarks for office equipment were revised to better represent appliances found in contemporary office buildings. Other key sources of data such as typical operating hours for equipment, however, have been omitted. This paper compares the benchmarks published in both the 2nd and 3rd editions of Guide F against a set of measurements of small power loads in a real UK office building. Load profiles for the monitored equipment are also presented to supplement the information included in the new Guide F. Practical application: With the increasing demand for more realistic predictions of operational energy use in buildings, small power should not be disregarded since it typically accounts for more than 20% of total energy used in offices. Furthermore, small power loads can have a significant impact on the cooling loads of a building. This paper reviews existing benchmarks, focusing on the new update to CIBSE Guide F, comparing available benchmarks against newly gathered monitored data. Detailed load profiles for individual office equipment are also provided, which can be used by designers to inform better predictions of small power consumption in office buildings.

Roberts

This paper presents Roberts, a Reconfigurable platfOrm for BEnchmarking Real-Time Systems. Roberts is the first platform which can be customised for a given system-under-test to support benchmarking of real-time properties and energy consumption. The benchmarking takes into account system workload and environmental events, with facilities for generating test vectors conforming to the specification of systemunder- test, and with support for on-line monitoring of the response time, output values and energy consumption. The proposed benchmarking platform has been implemented in the DE4 development system to provide cycle-accurate timing measurement at nano-second precision to analyse high performance applications. An evaluation of our approach shows that the platform can be used in analysing the performance of target applications and overheads of other timing facilities, such as the interval timer on processors.

Energy consumption, indoor environmental quality, and benchmark for office buildings in Hainan Province of China

With rapid economy growth, building energy consumption in China has been gradually increased. The energy consumption and indoor environmental quality of 51 office buildings in Hainan Province, a hot and humid area, were studied through collection of verified data in site visits and field tests. The result revealed that, electricity accounted for 99.79% of the total energy consumption, natural gas 0.17%, and diesel 0.04%. The air conditioning dominated the energy use with a share of 43.18%, equipment in the particular areas 26.90%, equipment in the office rooms 11.95%, lighting system 8.67%, general service system 7.57%, and miscellaneous items 1.73%. Statistical method including six indicators obtained the energy consumption benchmark with upper limit of 98.31 kW·h/m2 and lower limit of 55.26 kW·h/m2. According to ASHRAE standard (comfortable standard) and GB/T 18883-2002 (acceptable standard), the indoor environmental quality of 51 sampled office buildings was classified into three ranks: good, normal and bad. With benchmark of building energy consumption combined with indoor environmental quality, it was found that only 3.92% of sampled buildings can be identified as the best performance buildings with low energy consumption and advanced indoor environmental quality, and the buildings classified into normal level accounted for the maximum ratio.

Energy performance and indoor environmental quality in Hellenic schools

School buildings constitute a major part of the non-residential building stock, though due to their operational characteristics, they represent a low percentage of the overall energy balance of the building sector. Although health and productivity of pupils and teachers is strongly affected by the indoor environmental quality of their school, poor indoor air quality has been reported in published literature, even so for recently constructed school buildings. The same applies for the energy consumption, with large amounts of energy being wasted because no energy saving measures are applied for the operation of schools. This paper presents the outcome of a study on the energy performance of Hellenic school buildings. The general features of the contemporary building stock are presented along with the results from an energy survey in 135 Hellenic schools. The derived energy consumption benchmarks are compared with published literature. Finally, the energy performance and indoor environmental quality of a representative sample of schools in metropolitan Athens are assessed in a holistic approach to the “energy efficiency – thermal comfort – indoor air quality” dilemma. The IEQ assessment was based on an objective evaluation by monitoring crucial indoor conditions and a subjective occupant evaluation using standardized questionnaires. The potential of several energy conservation measures is evaluated in terms of energy savings and reduction of greenhouse gas emissions along with the related payback periods.

ENERGY EFFICIENCY IN EU UNIVERSITIES – RESULTS OF THE 1ST LEVEL AUDIT

The paper presents the main ideas of the project considering the programme “Intelligent Energy – Europe (IEE) / Use Efficiency: Universities and Students for Energy Efficiency”. The article focuses on project goals, outputs, results and work programme. The methods of energy performance analysis and consumption benchmarks are described. Operational Rating method for 1st level analysis is preferred as the most reasonable. The principles of critical buildings, including some examples are identified. The obtained results of the 1st level audit of 9 EU universities are given.

Simulation of a building and its HVAC system with an equation solver: Application to audit

A series of building energy simulation tools are being developed to help the building energy auditor in establishing his diagnosis (including benchmarking and detailed analysis of actual energy consumption) and in evaluating the selected energy conservation opportunities (ECOs). A first simulation tool, dedicated to benchmarking, has been presented in a previous paper. The present paper focuses on the second simulation tool, dedicated to inspection and evaluation of ECOs. This Building-HVAC System global model includes simplified models of building zones and of HVAC (heating, ventilation, and air conditioning) equipment. Only a limited number of easily identifiable parameters are required. The simplicity of the models and the use of an equation solver to run the simulation ensure good robustness and full transparency. The development, the implementation and the application of these models are discussed. Focus is also given to the calibration of the tools to monthly utility bills.