Survey of Residential Air Conditioning Electricity Consumption in Shanghai

With proliferation of electric appliances, residential electricity consumption, in particular the air conditioning load becomes more and more important and shares higher and higher percentage in total consumption in large cities like Shanghai. The paper reports in detail the survey on characteristics of residential electric consumption, in particular the air conditioning consumption. To optimize power system operation and expand power market, the paper concludes that power industry must learn to investigate, open up and adapt itself to power market economy.

IMPACT OF CLIMATE ON SUMMER RESIDENTIAL ELECTRICITY CONSUMPTION IN HONG KONG

The influence of climatic variables and cooling degree days (CDD) on summer residential electricity consumption for the period 1980 through 1994 in Hong Kong was investigated. The association between Clo, a measure of amount of Clothing insulation to maintain comfort, and residential electricity consumption was also examined. Utilizing monthly data and multiple regression analyses, it is discovered vapor pressure was not significantly related to electricity consumption while Cloud cover was negatively associated with electricity use. Climatic variables, CDD and Clo provided highly comparable results in modeling summer residential electricity consumption. Mean temperature and Cloud gave the best result. Clo yielded a slightly higher R2 value (0.867) than that of CDD (0.865) in the models. These results indicated that Clo could replace the weather variables and CDD to model electricity consumption.

Calculation and decomposition of regional household energy consumption in China:based on perspectives of urbanization and residents' consumption

Demographic urbanization caused great changes in scale of residents' consumption and residents' lifestyle and then impacted changes of regional household energy consumption. This paper expanded Logarithmic Mean Decomposition Index method through introducing variables of urbanization and residential consumption into the model. It also analyzed the influences of six factors as energy structure, energy intensity, population scale, urbanization, residential consumption, and consumption inhibit on regional household energy consumption. Results showed that in 2003-2012, impact of urbanization on regional household energy consumption of Chinese three areas was significantly higher than population size. The "population gathered in eastern region" phenomenon caused eastern region getting the largest population scale effect. Driving force of residential consumption on regional household energy consumption was much higher than the other five effects. Due to the comparative advantage of residential consumption compared with government consumption, investment, and net export, the decrease of consumption ratio promoted the growth of regional household energy consumption. Energy intensity in Chinese three regions kept reducing in 2003-2012. The progress of energy utilization technology slowed the growth of regional household energy consumption, and energy intensity effect was most significant in the central region.

Poisson rectangular pulse(PRP)model establishment based on uncertainty analysis of urban residential water consumption patterns

The commonly used Poisson rectangular pulse(PRP)model,employed for simulating high-resolution residential water consumption patterns(RWCPs),relies on calibration via medium-resolution RWCPs obtained from practical measurements.This introduces inevitable uncertainty stemming from the measured RWCPs,which consequently impacts the precision of model simulations.Here we enhance the accuracy of the PRP model by addressing the uncertainty of RWCPs.We established a critical sampling size of 2000 household water consumption patterns(HWCPs)with a data logging interval(DLI)of 15 min to attain dependable RWCPs.Through Genetic Algorithm calibration,the optimal values of the PRP model's parameters were determined:pulse frequency lλ=91 d^(-1),mean of pulse intensity E(I)=0.346 m^(3) h^(-1),standard deviation of pulse intensity STD(I)=0.292 m^(3) h^(-1),mean of pulse duration E(D)=40 s,and standard deviation of pulse duration STD(D)=55 s.Furthermore,validation was conducted at both HWCP and RWCP levels.We recommend a sampling size of2000 HWCPs and a DLI of30 min for PRP model calibration to balance simulation precision and practical implementation.This study significantly advances the theoretical foundation and real-world application of the PRP model,enhancing its role in urban water supply system management.

Impact of Low-Impact Development Technologies from an Ecological Perspective in Different Residential Zones of the City of Atlanta, Georgia

Low-impact development （LID） technologies have a great potential to reduce water usage and stormwa- ter runoff and are therefore seen as sustainable improvements that can be made to traditional water infrastructure, These technologies include bioretention areas, rainwater capturing, and xeriscaping, all of which can be used in residential zones, Within the City of Atlanta, residential water usage accounts for 53% of the total water consumption; therefore, residential zones offer significant impact potential for the implementation of LID, This study analyzes the use of LID strategies within the different residen- tial zones of the City of Atlanta from an ecological perspective by drawing analogies to natural ecosys- tems, The analysis shows that these technologies, especially with the addition of a graywater system, work to improve the conventional residential water network based upon these ecological metrics, The higher metric values suggest greater parity with healthy, natural ecosystems.

A Data Analytics Study on Building Characteristics Impacting Energy Consumption in Single-Family Attached Homes

San Antonio, Texas is the seventh largest city in the United States with a population of 1.4 million people, and ranked among the fastest growing cities. To assess the implications of past and present building practices within the residential sector on future energy consumption, the energy utilization of single-family attached homes (SFAH) in Bexar County, Texas is studied. The available dataset includes 3932 SFAH records representing about 33% of the total number of SFAHs within the county. The study is based on pairing and analyzing data at the individual building level from a variety of sources including the buildings’ physical characteristics, access to fuels, and monthly energy consumption. The results indicate that the area of conditioned space, presence of swimming pools, number of stories, presence of fireplaces, fuel-type, and number of shared walls are a significant factor on the energy consumption of single-family attached homes. In terms of energy consumption, all-electric two-story homes sharing two walls are the most energy efficient among SFAHs. This study can aid comprehensive master planning efforts for developing sustainable communities by highlighting key features of SFAHs and making the case for higher density housing as a viable and more energy efficient alternative to single-family detached homes (SFDH).