Heating Degree Days Research Articles

Recommending a thermal energy benchmark based on CIBSE TM46 for typical college buildings and creating monthly energy models

According to Chartered Institution of Building Services Engineers, CIBSE TM46 benchmarks, a typical college building needs 240 kWh/m2 thermal energy annually. This paper firstly analysed the accuracy of the CIBSE TM46 ‘University Campus’ benchmark against the thermal consumption values displaying on Display Energy Certificates (DECs). The DECs of 52 typical college buildings in Dublin were assessed and based on the 46% discrepancy between the median of samples and the CIBSE benchmark a new benchmark of 130 kWh/m2/yr was recommended. Secondly, monthly thermal energy models (MTEMs) which take into account the variations of heat demand during a year were generated. MTEMs were created using five key factors, including the mixed use method, CIBSE UC recommended benchmark, activities area, heating degree days, and typical operational hours of heating systems. The high level of accuracy of MTEMs was assessed against the actual consumption. The developed methodology predicts an accurate and detailed estimation of monthly thermal energy consumption in typical college buildings. In addition, a new definition for typical college buildings which is a mixed use building including seven major activities is presented.

Effects of climate and potential policy changes on heating degree days in current heating areas of China

Based on climate simulations over East Asia from a high-resolution regional climate model under RCP4.5 and 8.5 scenarios, we examine the impact of future climate change and heating policy changes on energy demand in current central heating areas over China using the heating degree days (HDD) and the number of the heating days (NHD) with different base temperature as the indices. Based on current heating policy in China, significant decreases of NHDs are projected, with larger decreases under RCP8.5 than RCP4.5. This decrease of NHDs would cause a northward shift of the decadal heating boundary line, with significant implications for infrastructure planning and development. Changing the heating policy currently in practice to one used in Europe and USA would cause an immediate jump in NHDs and in HDDs; as warming progresses in the future, these effects attenuate with time in an approximately linear trend under the two scenarios. Under RCP8.5, by 2050, the effects of warming climate would dominate over the heating policy change, and heating demand would be lower than the present day HDD and continue to decrease until the end of the century. Energy demand and the number of the heating days during peak winter shows no dependence on heating policy, as the policy-induced increase of energy demand would occur primarily during warmer months of the year. In addition, the indices are further weighted by population, and results show that increases in both HDDs and NHDs can be found in parts of northern China due to the increased population there by the end of the 21st century.

Analysis of heating degree day requirments changes under climate change in South Khorasan

Analysis of heating degree day requirments changes under climate change in South Khorasan

FARKLI İKLİM ŞARTLARI İÇİN HAVA BOŞLUKLU OPTİMUM BORU YALITIM KALINLIĞININ BELİRLENMESİNDE YAŞAM DÖNGÜSÜ MALİYET ANALİZİ

This study is about determining air gap, insulation material in pipes between 50 mm and 1000 mm in mechanical installation, and determining optimum insulation thickness, energy saving and payback period in cases where both are being used. For this calculation, life cycle cost analysis containing heating degree day has been used. Even though Afyon province climate conditions have been used as the case study, the study has been expanded for cold, temperate and warm climate conditions. This made it possible to make comparative assessments for insulation thickness, air gap, pipe diameter and heating degree day values. In 50 mm and 1000 mm pipes using air gap, the optimum insulation thickness was reduced by 81% and 39% respectively. It is recommended to use air gap in mild climates and to use insulation in cold climates. When insulation with air gap is applied, optimum insulation thickness is reduced, and in pipes with greater diameter energy cost saving is increased while in pipes with smaller diameter the payback period is reduced.

Changes of heating and cooling degree days over China in response to global warming of 1.5 °C, 2 °C, 3 °C and 4 °C

Future changes of heating degree days (HDD) and cooling degree days (CDD) in the 21st century with and without considering population factor are investigated based on four sets of climate change simulations over East Asia using the regional climate model version 4.4 (RegCM4.4) driven by the global models of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES, and MPI-ESM-MR. Under global warming of 1.5 °C, 2 °C, 3 °C, and 4 °C, significant decrease of HDD can be found over China without considering population factor, with greater decrease over high elevation and high latitude regions, including the Tibetan Plateau, the northern part of Northeast China, and Northwest China; while population-weighted HDD increased in areas where population will increase in the future, such as Beijing, Tianjin, parts of southern Hebei, northern Shandong and Henan provinces. Similarly, the CDD projections with and without considering population factor are largely different. Specifically, without considering population, increase of CDD were observed over most parts of China except the Tibetan Plateau where the CDD remained zero because of the cold climate even under global warming; while considering population factor, the future CDD decreases in South China and increases in North China, the Sichuan Basin, and the southeastern coastal areas, which is directly related to the population changes. The different future changes of HDD and CDD when considering and disregarding the effects of population show that population distribution plays an important role in energy consumption, which should be considered in future research.

A novel approach for estimating residential space heating demand

Energy system models on country level usually contain multiple energy carriers at different granularity. While data is comparably rich in terms of temporal and spatial resolution for the electricity part, much less is known for heat. Especially the true demand for heat as a function of usage and time is difficult to obtain. In many cases, energy consumption data (fuel oil, natural gas, district heating etc.) is taken as approximation for the final energy end-use of heat. Different heat distribution technologies bring their own bias on temperature levels and heating hours, like with ground floor heating vs. radiator. Therefore, historic consumption data is not an appropriate base for modelling of energy systems with long prospect. The present research work proposes a novel top-down methodology for generating aggregated load curves on heat demand, with a focus on residential space heating. Maps of population density distribution combined with norm temperature profiles and the definition of heating degree days provides a tempo-spatial map of heating demand. The knowledge of total residential space heating demand is used to identify the aggregated demand curve, suitable for energy system modelling.

The demand for natural gas in the Northeastern United States

This paper examines the demand for natural gas in the residential, commercial, and industrial sectors of the Northeastern United States, comprising nine states and using annual state-level panel data over the period between 1997 and 2016. It applies panel unit root and cointegration tests, and then estimates the parameters using five alternative estimators: dynamic fixed effects (DFE), mean group (MG), pooled mean group (PMG), common correlated effect mean group (CCEMG), and augmented mean group (AMG). The panel unit root and cointegration tests show that the series are I (1), and cointegrated. The estimated results show that the long run own price elasticities for natural gas in residential, commercial, and industrial sectors are −0.14, −0.29, and −0.28, respectively. The cross price elasticities of fuel oil for natural gas demand in residential, commercial, and industrial sectors are 0.19, 0.52, and 0.24, respectively. The long run natural gas demand is not affected by income in all three sectors. The heating degree days (HDD) have significant positive effects on demand for natural gas in all three sectors.

Developing a GIS of Hazards for Canadian Cultural Institutions

The Canadian Conservation Institute (CCI) has developed a Geographic Information System (GIS) of hazards for Canadian cultural heritage institutions. The greatly increased access to open data is changing how advisory bodies like the CCI and the public can access and share information. For the purpose of investigating how a GIS approach can assist the CCI with its mandate to improve the preservation of collections, a map layer of cultural heritage institutions across Canada has been assembled and continues to be upgraded for accuracy, inclusion and detail (Fig. 1). This was combined with a collation of hazard layers; a partial list includes: seismic risk, notably expectations of earthquake severity tied to improvements in the national building code, tsunami exposure, wildfire data, hurricane, tornado, lightning density, pest distribution, and energy use indicators such as heating degree days and climate norm data. The platform allows examination of expectations around climate change driven risks such as sea-level rise, storm-incursions, permafrost melt. The GIS approach will also allow reassessments around expected changes to flood risk maps issued by jurisdictions, as well as Statistics Canada layers on population related factors such as changes in numbers of local populations, income and demographic shifts which can be stressors or opportunities. Sources have been drawn from federal, provincial, municipal, and academic evaluations of hazards, which now are more commonly published as GIS products. Mapping Canadian heritage institution's within a GIS improves our ability to: visualise and interpret to clients the relative magnitude of their local hazards, make ties to more refined local analyses, and show adjacencies to mapped historical events. From a national perspective the GIS can generate profiles of aggregated institutional exposure to the hazards, and more readily identify sub-populations of institutions for which particular risks would rank higher or lower among their concerns. This improves CCI's preventive conservation advisory service's perspective on mappable risks for any institution we deal with as clients. Ultimately, through federal initiatives in open data, it is our intention that client groups can look at the GIS for the purpose of educating themselves on hazards they would want to prepare for.

Analysis of energy data of existing buildings in a University Campus

The constant increase in the requirement for electric energy on the part of the service sector has driven the development of tools for the analysis of energy data regarding the management of buildings. Particularly university campuses are made up of buildings for different purposes and uses. Therefore, this work proposes to develop a method capable of providing clear and easy-to-understand information to track electricity end-use by means of two-dimensional graphs. The aim of the method is to analyse the data of the electricity consumption of one or several buildings and compare them with regard to their surface areas and uses, as well as to obtain a correlation with the outdoor temperature. The visual analysis of the building electricity consumption in the campus ‘Sciences et Technologies’ of the University of Bordeaux in France is based on graphs which include electricity use intensity, time series of daily electricity consumption, scatter diagrams of consumption versus heating degree-days, and boxplots for daily consumption profiles. This analysis permits characterising the electricity consumption of the different types of buildings and determining a trends of energy end-use in the short as well as in the long term.

Impact of Climate Change on Energy Production, Distribution, and Consumption in Russia

An assessment of the overall impact of the observed and expected climatic changes on energy production, distribution, and consumption in Russia is presented. Climate model results of various complexity and evaluation data on the vulnerability of various energy production sectors to climate change are presented. It is shown that, due to the increase of air temperature, the efficiency of electricity production at thermal and nuclear power plants declines. According to the climate model results, the production of electricity at TPPs and NPPs by 2050 could be reduced by 6 billion kW h due to the temperature increase. At the same time, as a result of simulation, the expected increase in the rainfall amount and river runoff in Russia by 2050 could lead to an increase in the output of HPP by 4–6% as compared with the current level, i.e., by 8 billion kW h. For energy transmission and distribution, the climate warming will mean an increase in transmission losses, which, according to estimates, may amount to approximately 1 billion kW h by 2050. The increase of air temperature in summer will require higher energy consumption for air conditioning, which will increase by approximately 6 billion kW h by 2050. However, in total, the optimal energy consumption in Russia, corresponding to the postindustrial level, will decrease by 2050 by approximately 150 billion kW h as a result of climate- induced changes. The maximum global warming impact is focused on the heat demand sector. As a result of a decrease in the heating degree-days by 2050, the need for space heating is expected to fall by 10–15%, which will cause a fuel conservation sufficient for generating approximately 140 billion kW h of electricity. Hence, a conclusion about the positive direct impact of climate change on the Russia’s energy sector follows, which is constituted in the additional available energy resource of approximately 300 billion kW h per year.

Variations and trends of heating and cooling degree-days in Georgia for 1961–1990 year period

Abstract Indoor air heating and cooling is responsible for a large fraction of energy use in Georgia. Heating and cooling degree days are measures that reflect the amount of energy needed to heat or cool a building to a comfortable temperature, considering how cold or hot it is outside. The purpose of the presented research is to estimate and study variations and trends of heating and cooling degree days for different locations in Georgia for the base period defined by the World Meteorological Organization (1961–1990). To achieve this goal, air temperature daily values were used for fourteen different locations within Georgia, covering 1961–1990 year period. The daily, monthly and annual numbers of cooling and heating degree days have been estimated for various locations and also their spatial distribution have been studied. Heating degree days were calculated at a base temperature of 18 °C and cooling degree days at a base temperature of 26 °C. The obtained results are significant to study energy demand and resolve environmental issues associated with energy consumption in Georgia.

Climatic zoning for building construction in a temperate climate of Chile

In Chile, the official document that defines energy efficiency for building construction is the General Ordinance of Urban Planning and Construction which defines seven thermal zones based on the annual average values of heating degree-days (base temperature of 15 °C) calculated in 1999. In the context of climate change, the obsolete meteorological data must be updated. In the present study, we assessed three regions in the south of Chile (La Araucanía, Los Ríos, and Los Lagos); updated annual average values of the heating degree-days using data from the meteorological observations for the past decade and updated the thermal zones. The results obtained shows that the 20% of the municipalities were different from the thermal zones of the General Ordinance of Urban Planning and Construction.In addition, we considered the possibility of the climate severity index method application for climatic zoning in the study area. Due to this method, we identified the relative differences of energy demand for heating and cooling for the same building in different climatic conditions. The climatic zones were identifying based on the Technical Building Code of Spain. As a result, we detect three climatic zones for this regions in Chile and it was found that they were similar to the regions of northwest Spain. And finally, there was an analysis of the spatial distribution of the thermal and climatic zones and a comparison of the construction recommendations for each one of them.

On the relation between urban climate and energy performance of buildings. A three-years experience in Rome, Italy

Climatic conditions strongly affect the energy performance of buildings, and due to the synergy between global climate change and the Urban Heat Island (UHI) effect, the climatic conditions inside and outside the city are highly different. However, weather data collected at airports are commonly used for building energy simulations and these data do not take into account real temperature distribution in cities. Many studies in the literature address the topic but mostly considering only a couple of urban and non-urban stations. In this paper, the urban climate in Rome, Italy, is analysed after monitoring of the air temperature and relative humidity in four selected neighbourhoods and one reference station from October 2014 until September 2017. Rome is characterised by a composite urban pattern and high variability of building types, of which the four selected areas are representative. The heating degree days decrease up to 18% and cooling degree days increase up to 157% in the urban area with respect to the rural reference and the area most affected by the UHI is the city centre. The UHI is more intense in summer than in winter (average increase between 0.7 °C and 1 °C); while the diurnal and nocturnal UHI depends on the season and the neighbourhood. Then, the energy performance of a representative apartment block and a typical office building was computed using the measured data. Regarding the predicted energy performance, comparing the four urban sites and the reference site, the UHI causes a reduction of heating consumption up to 21% in residential building and 18% in the office building. An increase of cooling consumption up to 74% is instead computed for the residential building and up to 53% for the office building.

Determining base temperature for heating and cooling degree-days for India

Internationally, the cooling degree-days (CDD) and heating degree-days (HDD) have been commonly used as indicators of cooling and heating load occurring due to outdoor temperature. These indicators have also applied for classification of climate zones as referred in ASHRAE Standard 169-2013. As of now various base temperatures has been used in the different part of the world. Additionally, the analysis for base temperature had been done in 1980 by ASHRAE. This study aims to determine the base temperature for cities in India. The simulation approach has been used to identify base temperature using Energy Signature and Performance line method for 60 cities of India. The US-DOE developed 16 reference buildings which have been used for eight climate zones of India. These eight climate zones have been classified using the methodology of ASHRAE Standard 169–2013 on weather data of Indian cities. It was observed that the cooling base temperature is varying from 6.8 °C to 28.6 °C for the large hotel and 8.7–28.1 °C for office buildings while the heating base temperature is ranging from 13.8 °C to 21.4 °C for the large hotel and 10.4–18.7 °C respectively for different cities. The estimated base temperature for cooling and heating is 18 °C for India.

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.

Study of Hygrothermal Processes in External Walls with Internal Insulation

Abstract Being an important contributor to the final energy consumption, historic buildings built before 1945 have high specific heating energy consumption compared to current energy standards and norms. However, they often cannot be insulated from the outside due to their heritage and culture value. Internal insulation is an alternative. However internal insulation faces challenges related to hygrothermal behaviour leading to mold growth, freezing, deterioration and other risks. The goal of this research is to link hygrothermal simulation results with experimental results for internally insulated historic brick masonry to assess correlation between simulated and measured data as well as the most influential parameters. The study is carried out by both a mathematical simulation tool and laboratory tests of historic masonry with internal insulation with four insulation materials (mineral wool, EPS, wood fiber and granulated aerogel) in a cold climate (average 4000 heating degree days). We found disparity between measured and simulated hygrothermal performance of studied constructions due to differences in material parameters and initial conditions of materials. The latter plays a more important role than material parameters. Under a steady state of conditions, the condensate tolerating system varies between 72.7 % and 80.5 % relative humidity, but in condensate limiting systems relative humidity variates between 73.3 % and 82.3 %. The temperature between the masonry wall and all insulation materials has stabilized on average at +10 °C. Mold corresponding to Mold index 3 was discovered on wood fiber mat.

Impacts of climate change on hydropower generation in China

Analyzing the impact of climate change on China’s hydropower system can make great contribution to understanding the feedback mechanism of the climate change on energy system. In this work, an econometric model for regional hydropower generation is constructed to explore the impact of climate factors on hydropower generation in different regions of China by using the monthly panel data of 28 provinces in China. Further, we also make a prediction for the changes of hydropower generation in China caused by the changes of climatic factors under the three climate change scenarios (RCP2.6, RCP4.5 and RCP8.5) proposed in the Intergovernmental Panel on Climate Change’s (IPCC) fifth assessment report. The results show that: (1) At the national level, the influences of climatic factors on hydropower generation are significant, the elasticity coefficients of rainfall, heating degree day (HDD), cooling degree day (CDD) and sunshine duration are 0.081, −0.016, 0.089 and −0.043 respectively. (2) The impacts of climatic factors on the hydropower generation in the northern and southern regions of China are different. The effect of rainfall on the hydropower generation is significant in the southern regions, but not in the northern region. The CDD has a significant effect on both the northern and southern regions, and the latter is greater (0.136%). The impact of HDD on the northern area is significant, while its influence on the southern area is not significant. The influence of sunshine duration is not significant in any region in China. (3) Compared with the year of 2011, the total changes of hydropower output caused by climate factors by 2100 under the RCP8.5, RCP4.5 and RCP2.6 scenarios are 153.29 billion kWh, 67.49 billion kWh and 22.10 billion kWh, respectively. The results imply that the hydropower is sensitive and vulnerable to climate fluctuation, leading to many uncertainties for its development in the future. Finally, some policy implications are proposed for the planning of hydropower in China.

Natural gas consumption forecast with MARS and CMARS models for residential users

Prediction natural gas consumption is indispensable for efficient system operation and required for planning decisions at natural gas Local Distribution Companies (LDCs). Residential users are major consumers that usually demand a significant amount of total gas supplied in distribution systems, especially, in the winter season. Natural gas is primarily used for space heating, and for cooking of food by residential users therefore, they should naturally be non-interruptible. Due to the fact that distribution systems have a limited capacity for the gas supply, proper planning and forecasting in high seasons and during the whole year have become critical and essential. This study is conducted for the responsibility area of Başkentgaz which is the LDC of Ankara. Predictive models MARS (Multivariate Adaptive Regression Splines) and CMARS (Conic Multivariate Adaptive Regression Splines) are formed for one-day ahead consumption of residential users. The models not only permit to compare both approaches, but they also analyze the effect of actual daily minimum and maximum temperatures versus the Heating Degree Day (HDD) equivalent of their average. Using the obtained one-day ahead models with daily data during 2009–2012, the daily consumption of each day in 2013 has been predicted and the results are compared with the existing methods Neural Network (NN) and Linear Regression (LR). The outcomes of this study present MARS and CMARS methods for the natural gas industry as two new competitive approaches.

Weather derivatives pricing using regime switching model

Abstract In this study we discuss the pricing of weather derivatives whose underlying weather variable is temperature. The dynamics of temperature in this study follows a two state regime switching model with a heteroskedastic mean reverting process as the base regime and a shifted regime defined by Brownian motion with nonzero drift. We develop mathematical formulas for pricing futures and option contracts on heating degree days (HDDs), cooling degree days (CDDs) and cumulative average temperature (CAT) indices. The local volatility nature of the model in the base regime captures very well the dynamics of the underlying process, thus leading to a better pricing processes for temperature derivatives contracts written on various index variables. We use the Monte Carlo simulation method for pricing weather derivatives call option contracts.

Projected changes in future climate over the Midwest and Great Lakes region using downscaled CMIP5 ensembles

ABSTRACTDespite an increasing body of evidence from observed data that climate change is having a significant impact on different types of biogeophysical systems in the Midwest and Great Lakes region, there still remain critical questions of how quickly and how much climate will be altered over this region in the future. For this evaluation, we make use of 31 global climate model (GCM) projections from the Coupled Model Intercomparison Project, Phase 5 (CMIP5). Based on changes in temperature (T) and precipitation (P) over the Midwest, we selected ten GCM scenarios which (1) simulate historical climate well and (2) successfully capture the range of future climate from the entire CMIP5 ensemble. We then downscaled T and P projections to 1/16° gridded data sets for two different emission scenarios (RCP4.5 and RCP8.5) for three 30‐year future periods using the Hybrid Delta (HD) statistical downscaling approach which was proven to be applicable for daily‐scale application by a validation work using historical data. T is projected to increase across all seasons, with ensemble mean changes up to 6.5 °C by 2100 for the RCP8.5 scenarios. P increases up to 30% in spring and winter with decreasing snowfall to precipitation ratio, while summer P decreases moderately (−15%) by the 2080s. Changes in daily extreme events show similar seasonal patterns including increasing daily extreme P events in winter and decreasing P in summer. Growing season P may actually increase, however, despite projected P reductions in the warmest summer months. Regional warming results in decreased heating degree days (−1639 °C days, −32%) and increasing cooling degree days (+318 °C days, +957%) by 2080s, with overall net reductions in energy demand.