Characteristics of Heating Degree Days and Cooling Degree Days in Beijing During Last 50 Years

2011 ◽  
Author(s):  
Zuofang Zheng ◽  
Xiuli Zhang
Keyword(s):  
Degree Days ◽  
Cooling Degree Days ◽  
Heating Degree Days

Climate Change as a Driving Force on Urban Energy Consumption Patterns

2018 ◽  
pp. 7815-7830
Author(s):  
Mostafa Jafari ◽  
Pete Smith
Keyword(s):  
Energy Consumption ◽  
Pearson Correlation ◽  
Consumption Patterns ◽  
Time Slice ◽  
Degree Days ◽  
Urban Energy ◽  
Cooling Degree Days ◽  
Energy Consumption Patterns ◽  
Annual Total ◽  
Heating Degree Days

Heating Degree Days (HDD), in cases where temperatures are below 18°C, and Cooling Degree Days (CDD), in cases where temperatures are above 21°C, were used as energy consumption indices. During the last half century, mean annual temperatures have increased and as a consequence, CDD in the warm season have increased sharply. In the same time slice, HDD, even in the cool and cold season have declined steadily. The number of monthly and annual total HDD (mean= 1556) are much higher than CDD (mean=400) in the case study area and annual total HDD and CDD have a negative correlation (Pearson correlation = - 0.493; p = 0.001). The deceasing rate of HDD is limited and steady (R2= 0.062, p=0.099), but the increasing rate of CDD in the same time slice is sharp (R2=0.427, p=0.813). This shows that energy consumption patterns have increased sharply, and with available projection scenarios, is projected to increase more rapidly, leading to higher energy costs.

scholarly journals Influence of Climate Conditions on Deficiencies of Building Roofs

2019 ◽  
Vol 9 (7) ◽  
pp. 1389 ◽  
Author(s):  
Manuel Carretero-Ayuso ◽  
Alberto Moreno-Cansado ◽  
Justo García-Sanz-Calcedo
Keyword(s):  
Wind Speed ◽  
Maintenance Phase ◽  
Point Of View ◽  
Degree Days ◽  
Average Wind Speed ◽  
Climate Conditions ◽  
Average Wind ◽  
Building Process ◽  
Cooling Degree Days ◽  
Heating Degree Days

Climate conditions affect buildings’ performance and durability. The purpose of this paper is to examine the influence of climate conditions on roof deficiencies. 763 cases of such deficiencies were analyzed in this regard. Once the construction deficiencies were quantified, they were characterized from a climatological point of view and their ‘climate location segments’ were studied to obtain ‘ranges of concentration of anomalies’ according to the obtained percentage. A direct relation is shown to exist between the location of the building (latitude, situation, type of climate, precipitation, thermal demands, and average wind speed) and a greater or smaller concentration of deficiencies found in both flat and pitched buildings. It was also found that an annual average wind speed greater than 3 m/s increases the appearance of deficiencies in roofs. A higher prevalence of deficiencies was also found in those geographical zones with a thermal demand of 1800–2800 heating degree days or 450–700 cooling degree days. It was found that a higher percentage of construction deficiencies are concentrated in buildings located in the northern coastal climate segments of Spain. With these results, technicians will be able to take more appropriate precautions during both the building process and the use and maintenance phase.

scholarly journals Spatio-Temporal Analysis of Heating and Cooling Degree-Days Over Iran

2021 ◽  
Author(s):  
Amin Sadeqi ◽  
Hossein Tabari ◽  
Yagob Dinpashoh
Keyword(s):  
Time Series ◽  
Energy Demand ◽  
Temporal Trends ◽  
Temporal Analysis ◽  
Degree Days ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Spatio Temporal ◽  
Heating Degree Days ◽  
Cooling Energy Demand

Abstract Climate change affects the energy demand in different sectors of the society. To investigate this possible impact, in this research, temporal trends and change points in heating degree-days (HDD), cooling degree-days (CDD), and their simultaneous combination (HDD+CDD) were analysed for a 60-year period (1960-2019) in Iran. The results show that less than 20% of the study stations had significant trends (either upward or downward) in HDD time series, while more than 80% of the stations had significant increasing trends in CDD and HDD+CDD time series. Abrupt changes in HDD time series mostly occurred in the early 1980s, but those in CDD time series were mostly observed in the 1990s. The cooling energy demand in Iran has dramatically increased as CDD values have raised up from 690 ºC-days to 1010 ºC-days in the last 60 years. HDD, however, almost remained constant in the same period. The results suggest that if global warming continues with the current pace, cooling energy demand in the residential sector will considerably increase in the future, calling for a change in residential energy consumption policies.

A method to estimate the heating and cooling degree-days for different climatic zones of Saudi Arabia

2016 ◽  
Vol 38 (3) ◽  
pp. 327-350 ◽  
Author(s):  
Madhavi Indraganti ◽  
Djamel Boussaa
Keyword(s):  
Saudi Arabia ◽  
Energy Consumption ◽  
Regression Models ◽  
Outdoor Environment ◽  
Base Temperature ◽  
Degree Days ◽  
Climatic Zones ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Heating Degree Days

Saudi Arabia’s energy consumption is increasing astronomically. Saudi Building Code prescribes a fixed base temperature of 18.3℃ to estimate the heating degree-days and cooling degree-days. Using historical meteorological data (2005–2014), this article presents the heating degree-days and cooling degree-days estimated for the representative cities in all the five inhabited climatic zones of Saudi Arabia. We used the base temperatures of 14℃, 16℃ and 18℃ for heating degree-days, and 18℃, 20℃, 22℃, 24℃ and 28℃ for cooling degree-days for Dhahran, Guriat, Jeddah, Khamis Mushait and Riyadh cities. We developed multiple regression models for heating degree-days and cooling degree-days at various base temperatures for these zones. Degree-days for other cities in similar climates with limited input data can be computed with these. Lowering of base temperature by 2 K from 18℃ reduced the heating degree-days by 33–65%. At 14℃ of base temperature, the heating requirement reduced by 60–95%. Elevating the base temperature by 2 K from 18℃ lowered the cooling degree-days by 16–38%. At 28℃ of base temperature cooling can be completely eliminated in Khamis Mushait, and reduced by 65–92% in other cities. This observation merits rethinking about use of appropriate base temperatures that properly link the outdoor environment to reduce the energy consumption. Practical application: Using historical data, we developed regression models for predicting heating and cooling degree-days for five cities of Saudi Arabia in various climate zones without the historic data. Using these, we can estimate the changes in heating/cooling load due to the variation in base temperatures. For example, lowering base temperature by 2–4 K from 18℃ reduces the HDDs by 33–95% and elevating the base temperature by 2–4 K from 18℃ lowered the CDDs by 16–68%.

Climate Change as a Driving Force on Urban Energy Consumption Patterns

2019 ◽  
pp. 547-563
Author(s):  
Mostafa Jafari ◽  
Pete Smith
Keyword(s):  
Energy Consumption ◽  
Pearson Correlation ◽  
Consumption Patterns ◽  
Time Slice ◽  
Degree Days ◽  
Urban Energy ◽  
Cooling Degree Days ◽  
Energy Consumption Patterns ◽  
Annual Total ◽  
Heating Degree Days

Heating degree days (HDD), in cases where temperatures are below 18°C, and cooling degree days (CDD), in cases where temperatures are above 21°C, were used as energy consumption indices. During the last half century, mean annual temperatures have increased, and as a consequence, CDD in the warm season have increased sharply. In the same time slice, HDD even in the cool and cold season have declined steadily. The number of monthly and annual total HDD (mean= 1556) are much higher than CDD (mean=400) in the case study area, and annual total HDD and CDD have a negative correlation (Pearson correlation = - 0.493; p = 0.001). The deceasing rate of HDD is limited and steady (R2= 0.062, p=0.099), but the increasing rate of CDD in the same time slice is sharp (R2=0.427, p=0.813). This shows that energy consumption patterns have increased sharply, and with available projection scenarios, it is projected to increase more rapidly, leading to higher energy costs.

scholarly journals An Assessment of Six Dissimilarity Metrics for Climate Analogs

2013 ◽  
Vol 52 (4) ◽  
pp. 733-752 ◽  
Author(s):  
Patrick Grenier ◽  
Annie-Claude Parent ◽  
David Huard ◽  
François Anctil ◽  
Diane Chaumont
Keyword(s):  
Large Scale ◽  
Nearest Neighbor ◽  
Climate Model ◽  
Regional Climate ◽  
A Priori ◽  
Degree Days ◽  
Leibler Divergence ◽  
Cooling Degree Days ◽  
Kolmogorov Smirnov ◽  
Heating Degree Days

AbstractSpatial analog techniques consist in identifying locations whose historical climate is similar to the anticipated future climate at a reference location. In the process of identifying analogs, one key step is the quantification of the dissimilarity between two climates separated in time and space, which involves the choice of a metric. In this study, six a priori suitable metrics are described (the standardized Euclidean distance, the Kolmogorov–Smirnov statistic, the nearest-neighbor distance, the Zech–Aslan energy statistic, the Friedman–Rafsky runs statistic, and the Kullback–Leibler divergence) and criteria are proposed and investigated in an attempt to identify the best metric for selecting spatial analogs. The case study involves the use of numerical simulations performed with the Canadian Regional Climate Model (CRCM, version 4.2.3), from which three annual indicators (total precipitation, heating degree-days, and cooling degree-days) are calculated over 30-yr periods (1971–2000 and 2041–70). It is found that the six metrics identify comparable analog regions at a relatively large scale but that best analogs may differ substantially. For best analogs, it is shown that the uncertainty stemming from the metric choice does not generally exceed that stemming from the simulation or model choice. On the basis of the set of criteria considered in this study, the Zech–Aslan energy statistic stands out as the most recommended metric for analog studies, whereas the Friedman–Rafsky runs statistic is the least recommended.

scholarly journals The valuation of a natural gas-fired power plant with multiple turbines using clean spark spread and weather options

2021 ◽  
Author(s):  
M. Reaz-us Salam Elias
Keyword(s):  
Power Plant ◽  
Natural Gas ◽  
Regime Switching ◽  
Gas Turbines ◽  
Emission Rates ◽  
Degree Days ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Spread Option ◽  
Heating Degree Days

Assessing the value of a power plant is an important issue for plant owners and prospective buyers. In a deregulated market, an owner has the option to operate the plant when the revenue from selling the electricity is higher than the cost of operating the plant. This option is known as the spark spread option. Under emission restrictions, when the carbon cost is deducted from the spark spread, the option is named as the clean spark spread option. This thesis presents an analysis on the spark spread and clean spark spread option based valuation methods for a power plant with multiple gas turbines having different input–output characteristics, emission rates, and capacities. Electricity, natural gas and carbon allowance prices are assumed to follow mean–reverting processes. Results demonstrate that CO2 allowance cost reduces the expected plant value, while the flexibility of switching among turbines adds value to the power plant. Weather also affects the power plant operation. This thesis also presents a valuation model for a power plant integrating spark spread and weather options. A cooler winter drawing more electricity could generate a higher payoff for the plant owner. A warmer winter, however, could lead to a lower payoff. An owner holding a long position in a temperature–based put option could exercise the option when the winter is milder. The exercise is triggered by the drop of heating degree days below a strike degree day. The number of weather contracts to buy is determined by minimizing the variance of the total payoff. Pricing of the weather option is calculated based on the mean–reverting behavior of temperature. Results demonstrate that the integrating weather option along with spark spread option adds value to the downward spark spread option based valuation of the plant in a warmer winter. A comparison of temperature modeling approaches with an aim to pricing weather option is also investigated. Regime–switching models generated from a combination of different underlying processes are utilized to determine the expected heating and cooling degree days. Weather option prices are then calculated based on a range of strike heating degree days.

scholarly journals Climate Extreme Indices Derived from Observed Daily Temperature Data Over Three Cities of Thrace Region, Turkey

2021 ◽  
Author(s):  
Sertaç Oruç ◽  
Keyword(s):  
Climatic Factors ◽  
Daily Minimum Temperature ◽  
Historical Period ◽  
Daily Maximum ◽  
Climate Extreme ◽  
Degree Days ◽  
Cooling Degree Days ◽  
Temperature Indices ◽  
Heating Degree Days ◽  
Thrace Region

Construction industry can be affected by climate change in particular temperature and temperature extremes not only for the design phase but also for production or end-use/operation phases. In this regard the major climatic factors that are dominant for the building lifecycle must be evaluated. This study determined the 13-sector specific ET-SCI temperature indices annually and investigated their trend characteristics at Edirne, Kırklareli and Tekirdağ of Thrace Region for the historical period. The results showed a dominant increasing temperature trend over the region. Edirne, Kırklareli, and Tekirdağ stations showed significantly increasing trends for the hottest night, average daily maximum, and average daily minimum temperature indices in this study. Furthermore, the hottest day index also showed an increasing trend for all the stations with a significant trend for Edirne and Tekirdağ. Moreover, significant decreasing trends were observed in the heating degree days and increasing significant trends were observed for the SU (summer days), CDDCOLD18 (cooling degree days) and TR (tropical nights) values at all the stations.

scholarly journals The valuation of a natural gas-fired power plant with multiple turbines using clean spark spread and weather options

2021 ◽  
Author(s):  
M. Reaz-us Salam Elias
Keyword(s):  
Power Plant ◽  
Natural Gas ◽  
Regime Switching ◽  
Gas Turbines ◽  
Emission Rates ◽  
Degree Days ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Spread Option ◽  
Heating Degree Days

Assessing the value of a power plant is an important issue for plant owners and prospective buyers. In a deregulated market, an owner has the option to operate the plant when the revenue from selling the electricity is higher than the cost of operating the plant. This option is known as the spark spread option. Under emission restrictions, when the carbon cost is deducted from the spark spread, the option is named as the clean spark spread option. This thesis presents an analysis on the spark spread and clean spark spread option based valuation methods for a power plant with multiple gas turbines having different input–output characteristics, emission rates, and capacities. Electricity, natural gas and carbon allowance prices are assumed to follow mean–reverting processes. Results demonstrate that CO2 allowance cost reduces the expected plant value, while the flexibility of switching among turbines adds value to the power plant. Weather also affects the power plant operation. This thesis also presents a valuation model for a power plant integrating spark spread and weather options. A cooler winter drawing more electricity could generate a higher payoff for the plant owner. A warmer winter, however, could lead to a lower payoff. An owner holding a long position in a temperature–based put option could exercise the option when the winter is milder. The exercise is triggered by the drop of heating degree days below a strike degree day. The number of weather contracts to buy is determined by minimizing the variance of the total payoff. Pricing of the weather option is calculated based on the mean–reverting behavior of temperature. Results demonstrate that the integrating weather option along with spark spread option adds value to the downward spark spread option based valuation of the plant in a warmer winter. A comparison of temperature modeling approaches with an aim to pricing weather option is also investigated. Regime–switching models generated from a combination of different underlying processes are utilized to determine the expected heating and cooling degree days. Weather option prices are then calculated based on a range of strike heating degree days.

scholarly journals Weather indexes, index insurance and weather index futures

2018 ◽  
Vol 9 (1) ◽  
pp. 32-40 ◽  
Author(s):  
Chengyi Pu ◽  
Yueyun (Bill) Chen ◽  
Xiaojun Pan
Keyword(s):  
Financial Markets ◽  
Index Insurance ◽  
Degree Days ◽  
Weather Index ◽  
Index Futures ◽  
Weather Index Insurance ◽  
Cooling Degree Days ◽  
Chicago Mercantile Exchange ◽  
Heating Degree Days ◽  
Weather Insurance

This paper compares the weather insurance, weather index insurance and index futures and focuses on why China needs to develop weather indexes and adopt and trade weather index futures. It further discusses how to construct the indexes and futures and how to price them. Different from the Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) used at Chicago Mercantile Exchange (CME), it develops the Extremely Heating Days (EHDs) and Extremely Cooling Days (ECDs) to derive relevant temperature-based weather index futures. Recently China has started using weather index insurance to cover farmers’ risk. Through comparisons of weather index futures with index insurance, this study shows the necessity and importance of using the weather index futures to better protect farmers and better develop China’s financial markets.

Sign in / Sign up

Export Citation Format

Share Document