A user-centric space heating energy management framework for multi-family residential facilities based on occupant pattern prediction modeling

Space heating is the highest energy consumer in the operation of residential facilities in cold regions. Energy saving measures for efficient space heating operation are thus of paramount importance in efforts to reduce energy consumption in buildings. For effective functioning of space heating systems, efficient facility management coupled with relevant occupant behaviour information is necessary. However, current practice in space heating control is event-driven rather than user-centric, and in most cases relevant occupant information is not incorporated into space heating energy management strategies. This causes system inefficiency during the occupancy phase. For multi-family residential facilities, integrating occupant information within space heating energy management strategies poses several challenges; unlike with commercial facilities, in multi-family facilities occupant behavior does not follow any fixed activity-schedule pattern. In this study, a framework is developed for extracting relevant information about the uncertainties pertaining to occupant patterns (i.e., demand load) in multi-family residential facilities by identifying the factors affecting space heating energy consumption. This is achieved using sensor-based data monitoring during the occupancy phase. Based on the analysis of the monitoring data, a structure is defined for developing an occupant pattern prediction model that can be integrated with energy management strategies to reduce energy usage in multi-family residential facilities. To demonstrate the developed framework, a multi-family residential building in Fort McMurray, Canada, is chosen as a case study. This paper shows that integrating the developed occupant pattern prediction model within space heating energy management strategies can assist facility managers to achieve space heating energy savings in multi-family residential facilities.     

Alternative scenarios analysis concerning different types of fuels used for the coverage of the energy requirements of a typical apartment building in Thessaloniki,Greece. Part I: Fuel consumption and emissions

This paper focuses on the analysis (concerning energy and environmental performance) and comparison of different types of fuel intended either for direct use (e.g. domestic boiler combustion) or indirect use (production of electricity that will be consumed) in order to satisfy the energy requirements of a typical apartment building in Thessaloniki, Greece. The energy requirements that are being examined are: space heating, water heating, kitchen and cooking appliances, lighting and other various electrical appliances. For the purposes of this analysis an apartment building model has been designed that simulates combinations of these operations sorted in five scenarios in proportion with the fuel being used and the way electricity is generated. The analysis’ obtained results concern: pollutant emissions per kg, kWh or m³ of the fuel being used, daily total emissions that correspond to the estimated fuel required to satisfy the energy needs of the apartment building and the financial comparison of all scenarios.     

Heat consumption for preparing domestic hot water in hospitals

This study analyses heat consumption for heating domestic water in large hospital facilities with over 600 hospital beds. The tests were carried out in 2 hospitals: the 715-bed University Hospital in Bydgoszcz and the 690-bed Provincial Hospital. The tests were performed over a period of 4 years: 2005-2008 for the first hospital and 2003-2006 for the second.The aim of this study is to analyse the variations and seasonal changes in the heat consumed to produce domestic hot water during the specified time periods. The results of this study show the yearly, monthly, daily, and hourly consumption of heat for domestic hot water. Particular emphasis is placed on the daily and hourly heat-consumption irregularity coefficients for domestic hot water.The results of this study may be used, for example, to predict heat consumption when designing new hospital facilities with 500-800 beds, to determine the heating power of the heat source and individual centres. Data on the constant and low-temperature heat consumption for domestic hot water throughout the whole year are particularly useful, as these data may be used to analyse existing large hospitals that are seeking alternative solutions (such as renewable energy or energy recycling) to reduce fossil fuel consumption.     

Estimation models for heating energy and electricity costs

Heating energy and electricity represent a significant proportion of the overall financial expenditures over the life cycle of buildings and play a decisive role in the assessment of ecological quality. To ensure ecological and economical sustainability, the planning and construction of energy efficient buildings have become increasingly important. The present study introduces statistical models for the estimation of energy costs during the planning process as well as for the purpose of monitoring and controlling costs during operation including a wide range of facility types. Based on a data sample of 206 occupied facilities located in Germany, regression models are presented in detail including significant predictor variables. The provision of correctly specified models as well as a consistent and unbiased estimation beyond the employed data is verified by validation tests. The practical significance of the determined variables is presented by the calculation of various scenarios. The best estimation accuracy is indicated for regression models with transformed response and predictor variables achieving mean absolute percentage errors of 20.5% (heating energy) and 20.7% (electricity), respectively. An extension of the data sample, a consideration of further facility types, and an implementation of additional statistical methods may be considered by future approaches to improve the estimation accuracy.     

Sensitivity of the total heat loss coefficient determined by the energy signature approach to different time periods and gained energy

In order to identify buildings that have energy saving potential there is a need for further development of robust methods for evaluation of energy performance as well as reliable key energy indicators. To be able to evaluate a large database of buildings, the evaluation has to be founded on available data, since an in-depth analysis of each building would require large measurement efforts in terms of both parameters and time. In practice, data are usually available for consumed energy, water, and so on, namely consumption that the tenants or property holder has to pay for. In order to evaluate the energy saving potential and energy management, interesting key energy indicators are the total heat loss coefficient K_tot (W/K), the indoor temperature (T_i), and the utilisation of the available heat (solar radiation and electricity primarily used for purposes other than heating). The total heat loss coefficient, K_tot, is a measure of the heat lost through the building's envelope, whereas T_i and the gained energy reflect the user's behaviour and efficiency of the control system.In this study, a linear regression approach (energy signature) has been used to analyse data for 2003-2006 for nine fairly new multifamily buildings located in the Stockholm area, Sweden. The buildings are heated by district heating and the electricity used is for household equipment and the buildings’ technical systems. The data consist of monthly energy used for heating and outdoor temperature together with annual water use, and for some buildings data for household electricity are also available. For domestic hot water and electricity, monthly distributions have been assumed based on data from previous studies and energy companies. The impact on K_tot and T_i of the time period and assumed values for the utilised energy are investigated.The results show that the obtained value of K_tot is rather insensitive to the time period and utilised energy if the analysis is limited to October-March, the period of the year when the solar radiation in Sweden yields a minor contribution to heating. The results for the total heat loss coefficient were also compared to the calculations performed in the design stage; it was found that K_tot was on average 20% larger and that the contribution to heating from solar radiation was substantially lower than predicted. For the indoor temperature, however, the utilised energy had a large impact.With access to an estimate of K_tot and T_i, an improved evaluation of the energy performance may be achieved in the Swedish real estate market. At present the measure commonly used, despite the fact that monthly data is available, is the annual use of energy for space heating per square metre of area to let.     

Trial application of ASHRAE 1051-RP: calibration method for building energy simulation

ASHRAE research project 1051-RP generated a method to improve the process of calibrating whole building energy simulation models based on monthly utility data. The approach, using manual generation of simulation model variations, was applied to a 12,000 m² high-performance, dual energy, cold climate building. This led to 27 models that met the ASHRAE Guideline 14 monthly goodness-of-fit criteria for electricity, but had fit values for gas that were about 5–7 times the normalized mean bias error (NMBE) acceptance threshold. Five models met the criteria for natural gas and had acceptable coefficient of variation of the root-mean-square error for electricity, but NMBE was about 100% too high. Use of finer interval monitored data yielded a model with electrical NMBE about 60% above the acceptance threshold, and gas use about 200% above. Hourly analysis of the thermal energy demand on the plant showed wide discrepancies with the estimates on an hourly and half daily basis.     

Economic and environmental evaluation of micro CHP systems with different operating modes for residential buildings in Japan

The growing worldwide demand for less polluting forms of energy has led to a renewed interest in the use of micro combined heat and power (CHP) technologies in the residential sector. The operation of micro CHP system results in simultaneous production of heat and power in a single household based on small energy conversion units. The heat produced may be used for space and water heating and possibly for cooling load if combined with an absorption chiller, the electricity is used within the house.In this paper, two typical micro CHP alternatives, namely, gas engine and fuel cell for residential buildings, are analyzed. For each facility, two different operating modes including minimum-cost operation and minimum-emission operation are taken into consideration by employing a plan and evaluation model for residential micro CHP systems. The analysis results show that the fuel cell system is recognized as a better option for the examined residential building from both economic and environmental points of view. With the operation considering optimal economic benefits, annual energy cost is reduced by about 26%. On the other hand, while maximizing the environmental merits, annual CO₂ emissions are reduced by about 9%.     

Leveraging the analysis of parametric uncertainty for building energy model calibration

Calibrated energy models are used for measurement and verification of building retrofit projects, predictions of savings from energy conservation measures, and commissioning building systems (both prior to occupancy and during real-time model based performance monitoring, controls and diagnostics). This paper presents a systematic and automated way to calibrate a building energy model. Efficient parameter sampling is used to analyze more than two thousand model parameters and identify which of these are critical (most important) for model tuning. The parameters that most affect the building’s energy end-use are selected and automatically refined to calibrate the model by applying an analytic meta-model based optimization. Real-time data from an office building, including weather and energy meter data in 2010, was used for the model calibration, while 2011 data was used for the model verification. The modeling process, calibration and verification results, as well as implementation issues encountered throughout the model calibration process from a user’s perspective are discussed. The total facility and plug electricity consumption predictions from the calibrated model match the actual measured monthly data within ±5%. The calibrated model gives 2.80% of Coefficient of Variation of Root Mean Squared Error (CV (RMSE)) and ?2.31% of Normalized Mean Bias Error (NMBE) for the whole building monthly electricity use, which is acceptable based on the ASHRAE Guideline 14–2002. In this work we use EnergyPlus as a modeling tool, while the method can be used with other modeling tools equally as well.     

Zur Genauigkeit von Heizwärme‐Bilanzverfahren. Einführung eines Heizperiodenbilanzverfahrens mit analytischen Klimafunktionen

Precision of heating energy balance methods. Introduction of annual heating energy balance with analytical climate function. By smoothing the outdoor temperature and global radiation intensities to cosine functions it is possible to obtain the length of the heating period, the mean outdoor temperature and the radiation during the heating period as functions of the base temperatures. Neglecting the time difference between radiation intensities and outdoor temperature it is also possible to represent the mean base temperature as a simple function of building parameters and outdoor climate values. With these functions the accuracy of the monthly heating energy balance method and of the annual heating energy balance method according to the European Standard EN 832 can be tested for very low heat gains. Comparisons show, that the monthly heating energy balance method and even more the annual heating energy balance method according to EN 832 tend to underestimate the annual heating energy demand. With short heating periods, this tendency is stronger. At heating periods shorter than 4 months the qualification of the monthly heating energy balance method as reference method seems to be questionable. The analytic heating energy balance method, a simple completely analytical method using energy balance over the heating period for different energetic standards is introduced. The accuracy in the calculation of annual heating energy demand is checked in comparisons with the monthly heating energy balance method. For heating periods longer than 5 months the annual heating energy demand calculated with this method differs less than 2 percent from the equivalent value of the monthly heating energy balance method in most cases. The annual method of energy balance over the heating period introduced by Loga for buildings with different energetic standards is analysed and compared with the analytic balance method.     

Effects of common fuel and heating system options on the energy usage,pollutant emissions and economy

Annual fuel and energy consumptions and CO₂ and SO₂ emissions of various fuel (natural gas, fuel oil, coal, lignite, electricity) and system alternatives (individual, central, district) for hot water and space heating are compared. Further, detailed economical analyses illustrate the dependency of the life cycle costs on fuel and system types, building size and location, inflation and interest rates. It is found that natural gas systems lead in all respects, but fuel oil systems follow closely in many cases. Coal and lignite cannot compete at all, except possibly lower SO₂ emissions of imported low-S coal in comparison to typical fuel oils. Direct electrical heating and even electrical heat pumps should be discouraged because of their markedly inferior performance. Also, district and central systems could provide savings (about 20% and 5%, respectively) in comparison to individual systems using identical energy resources.     

Electrical analysis of a hybrid photovoltaic-hydrogen/fuel cell energy system in Denizli, Turkey

In recent years, hybrid photovoltaic-hydrogen/fuel cell energy systems have been popular as energy production systems that are clean, environmental-friendly, modular, and independent from fossil fuels. In February 2007, a clean energy research facility consisting of a 5 kWp photovoltaic system and a 2.4 kWp hydrogen-fuel cell system was built to investigate these energy production technologies at Pamukkale University in Denizli, Turkey. In this hybrid energy system, electricity is generated by photovoltaic panels. Generated electrical energy is stored chemically in batteries and metal hydride hydrogen canisters. Hydrogen electrolyzed from water is transformed to DC electrical energy by two fuel cells in the case of its necessity. DC electricity produced by photovoltaic panels and fuel cells is converted to AC by two inverters for the requirements of the building. In this study, an electrical energy analysis of the building, in terms of energy efficiency, harmonics, voltage changes, voltage and current sags, voltage and current swells, transients, power outage, frequency changes etc., is performed to evaluate the power quality of the hybrid energy system. In addition, some measurements such as insulation resistance, loop impedance, line impedance, grounding resistance, and specific resistance of the ground are measured to obtain the electrical characteristics of the system.     

Rapid analysis of time series data to identify changes in electricity consumption patterns in UK secondary schools

This paper presents a methodology for energy professionals to identify potential electricity saving opportunities in buildings from the analysis of half-hourly electricity consumption data. The technique recommended in UK government good practice guidance for use with monthly gas data has been applied to half-hourly electricity data from 37 secondary schools. The technique monitors consumption over time, identifying any changes in patterns and quantifying their effects. It has the advantage of being both high resolution and quick to employ. The analysis produces results that allow energy professionals to rapidly detect changes in electricity consumption.     

Fuzzy and feedforward control of an hybrid thermal energy storage system

A control model for operating a system that stores simultaneously sensible heat from solar and electric energy is proposed. The hybrid thermal energy storage system accumulates solar energy during sunny days and releases it later at night or during cloudy days. It also stores heat from an electric heater during off-peak periods so as to release it later during peak periods. The control model, which makes use of 24-h weather forecasts, comprises two types of controllers: a fuzzy logic controller for estimating the daily amount of thermal electric energy to be stored and a feedforward controller for determining the electricity consumption profile of the heating element during off-peak hours. Results indicate that the proposed control system is far superior to traditional control systems. It maintains a comfortable thermal environment at all times, i.e. the temperature fluctuations are kept within the imposed margins and overheating of the room never occurs. Furthermore, compared to a traditional electric base board heating system, it reduces the electricity consumption for the winter season by 24% and 94% of this electricity is consumed during off-peak hours.     

Analyse der Genauigkeit des Monatsbilanzverfahrens zur Ermittlung des Kühlbedarfs von Nichtwohngebäuden

Analysis of the monthly method for cooling energy demand calculation in office buildings. On 16^th December of 2002 the European Union passed the directive 2002/91/EU regarding the “Energy Performance of Buildings”. The individual member states had to implement this directive until 4^th January 2006. For new and for existing buildings energy certifications must be issued. To calculate energy ratios of buildings the monthly method is often used. The monthly method is analysed in this paper. Therefore the cooling demand for an office zone model was calculated by the monthly method and by a simulation. The comparison of the calculated value of the cooling demand by the monthly method and the simulation shows that the balanced value is sometimes smaller than the simulated value. To get realistic values for the cooling demand it is imperative to use correction‐factors for the balanced cooling demand. Coupled zones are accounted incorrect by calculation of cooling demand with the monthly method.     

Alternative scenarios analysis concerning different types of fuels used for the coverage of the energy requirements of a typical apartment building in Thessaloniki, Greece. Part II: life cycle analysis

This paper constitutes a continuation of “Alternative scenarios analysis concerning different types of fuels used for the coverage of the energy requirements of a typical apartment building in Thessaloniki, Greece. Part I: fuel consumption and emissions”. It is concerned with the application of life cycle analysis (LCA) methodology to the model of the apartment building determined in Part I. The examination here includes emissions of light heating oil EL refining, transportation and combustion, of natural gas transportation and combustion and of electricity generation and use (lignite, natural gas, diesel oil and kerosene originated). All data used were collected from a typical power station in Greece.     

Temperatures and heating energy in New Zealand houses from a nationally representative study—HEEP

The household energy end-use project (HEEP) has collected energy and temperature data from a randomly selected, nationally representative sample of about 400 houses throughout New Zealand. This database has been used to explore the drivers of indoor temperatures and heating energy. Initial analysis of the winter living room temperatures shows that heating type, climate and house age are the key drivers. On average, houses heated by solid fuel are the warmest, with houses heated by portable LPG and electric heaters the coldest. Over the three winter months, living rooms are below 20 °C for 83% of the time—and the living room is typically the warmest room. Central heating is in only 5% of houses. Solid fuel is the dominant heating fuel in houses. The lack of air conditioning means that summer temperatures are affected by passive influences (e.g. house design, construction). Summer temperatures are strongly influenced by the house age and the local climate—together these variables explain 69% of the variation in daytime (9 a.m. to 5 p.m.) living room temperatures. In both summer and winter newer (post-1978) houses are warmer—this is beneficial in winter, but the high temperatures in summer are potentially uncomfortable.     

LCC analysis for energy-saving in residential buildings with different types of construction masonry blocks

Space heating in cold climates requires large quantities of heat energy to be spent. Therefore, considerable energy-savings can be obtained using construction wall materials with low thermal conductivity in the buildings. In this study, an economic analysis (LCC analysis) was performed in order to estimate the optimum thickness, saving and pay-back period which minimizes the total cost including the masonry material and the energy consumption costs. The LCC analysis was carried out for external walls of buildings in Afyonkarahisar, Turkey. Considering long term and current outdoor air temperature records, degree-days (DD) values were used, and the variation of annual energy requirement of the building was investigated for various masonry (product) types for per unit area. Masonry products were block elements with one, two, three and four row-hollows, hollow-brick and aerated concrete. As the fuel types, fuel-oil, natural gas, coal and electricity were considered in the analysis. The functional unit of the LCC was the use of 1 m² of the building's living area over 50 year's period. As a conclusion, the highest energy-saving was obtained by the use of hollow blocks with 4 rows. Moreover, the most suitable fuels for all climate zones appear to be electricity and fuel-oil. But, the natural gas is a better choice when the atmospheric pollution is an important consideration.     

住宅供热采暖节能有关问题的探讨

据最新媒体报道数据显示,当前我国城市总耗能中,建筑供热采暖耗能占到32%以上,节能现状问题表现突出。研究供热采暖节能,开发城市住宅供热采暖节能潜力,在当前形势下对有效利用资源,提高资源利用率有着十分重要的现实意义。     

Economic optimization of a cogeneration system for apartment houses in Korea

A cogeneration system which can be used as a distributed generation source produces electricity and heat energy simultaneously from a single source of fuel. For industrial and domestic applications, where both kinds of energy are required, the cogeneration system can return fossil fuel energy savings up to 30%, and can reduce CO₂ emissions correspondingly as compared with a conventional system. In this study, eight apartments with residential areas in the range of 57200 m² to 182760 m² were chosen to study how much energy savings can be achieved by adoption of the cogeneration system in those apartments. Based on the energy demand data for heat and electricity, an optimum configuration of the cogeneration system for each apartment was determined by a developed computer program. The economic gain achieved by introducing the cogeneration system in those apartments was estimated and the monitored values compared with the estimated ones. By adoption of the cogeneration system, the natural gas saved was more than 30% and an average economic gain of US$ 3.6 m⁻²/year in the overall energy cost was obtained.     

A method for fully automatic operation of domestic heating

Complex, inconvenient and badly arranged push buttons and menus on domestic heating controls often cause users to enter unsuitable settings that result in impaired comfort and poor operating efficiency. This paper proposes a novel approach to the human interface of home heating systems that greatly simplifies the input required from the user. Time settings are derived automatically from electricity consumption and hot water use, also a temperature set point is provided that adapts to user activity levels and external temperature. Practical results from a prototype control system incorporating these methods are reported, showing useful energy savings. It is argued that this increased automation of control allows the benefits of low carbon technologies such as micro-combined heat and power, and solar hot water heating, to be fully exploited.