Adjustments to the indicators of the heating and cooling degree-days for regions of the Republic of Uzbekistan

This paper identifies the indicators of the calculated heating and cooling degree-days for the territory of Uzbekistan. The revealed values of the maximum and average daily outside air temperature were taken into account based on the collection, processing and analysis of the latest archives of climatic data. These data was obtained from open sources of weather stations, suitable for servicing scientific data, in order to enter adjustments to forecasts in the design of heat and cold supply systems in buildings and structures, which, in turn, mitigate the effects of climate change.

Large uncertainties in trends of energy demand for heating and cooling under climate change

The energy demand for heating and cooling buildings is changing with global warming. Using proxies of climate-driven energy demand based on the heating and cooling Degree-Days methodology applied to thirty global climate model simulations, we show that, over all continental areas, the climate-driven energy demand trends for heating and cooling were weak, changing by less than 10% from 1950 to 1990, but become stronger from 1990 to 2030, changing by more than 10%. With the multi-model mean, the increasing trends in cooling energy demand are more pronounced than the decreasing trends in heating. The changes in cooling, however, are highly variable depending on individual simulations, ranging from a few to several hundred percent in most of the densely populated mid-latitude areas. This work presents an example of the challenges that accompany future energy demand quantification as a result of the uncertainty in the projected climate.

Heating and Cooling Degree-Days Climate Change Projections for Portugal

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II

Waterfront Hotels’ Chillers: Energy Benchmarking and ESG Reporting

Chillers consumes the largest amount power in subtropical hotels. To monitor chillers’ power usage is of critical importance in energy control. This study attempted to establish the benchmark of electricity usage of hotel chillers and elucidate how the benchmarking results can be integrated with the various types reports for monitoring purposes. A survey of 20 waterfront hotels in the city of Greater Bay Area was conducted and 13 complete samples were used in the analysis. Multiple regression with selected 12 parameters—outdoor temperature, solar radiation, wind speed, cooling degree days, room occupancy, number of employees, service types, and unequally sized chillers were employed. The investigation found that the mean electricity usage of a chiller is 118 kWh/m2 on an annual basis for a deluxe waterfront hotel. The analysis excluded air-conditioned floor area, an exploratory variable, as the valid factor in the chiller’s electricity usage. While the overall R2 of the modeling equation for the whole year was limited to 0.76, the explanatory power of equations for humid spring and deep summer reached 80%. Hoteliers may harness this exercise as a reference to monitor and report the performance of key energy production facility per the Environment, Social, and Governance (ESG) guide.

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

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.

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

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.

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

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.

Heating and Cooling Degree-Days Climate Change Projections for Portugal

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating degree-day (HDD), the cooling degree-day (CDD) and the HDD+CDD were computed from an ensemble of 7 high-resolution bias-corrected simulations attained from EURO-CORDEX under RCP4.5 and RCP8.5. These three indicators were analyzed for 1971-2000 (from E-OBS) and 2011-2040 and 2041-2070, under both RCPs. Results show that the overall spatial distribution of HDD trends for the 3 time-periods points out an increase of energy demand to heat internal environments in Portugal's northern-eastern regions, most significant under RCP8.5. It is projected an increase of CDD values for both scenarios; however, statistically significant linear trends were only found for 2041-2070 under RCP4.5. The need for cooling is almost negligible for the remaining periods, though linear trend values are still considerably higher for 2041-2070 under RCP8.5. By the end of 2070, higher amplitudes for all indicators are depicted for southern Algarve and Alentejo regions, mainly under RCP8.5. For 2041-2070 the Centre and Alentejo (North and Centre) regions present major positive differences for HDD(CDD) under RCP4.5(RCP8.5), within the 5 NUTS II regions predicting higher heating(cooling) requirements for some locations.