Summer Electricity Consumption Research Articles

Projection of Non-Industrial Electricity Consumption in China’s Pearl River Delta under Global Warming Scenarios

Global warming is a global issue closely linked to sustainability, and power systems around the world are facing immense pressure due to global warming. The purpose of this study is to investigate the impact of global warming on non-industrial electricity consumption in China’s Pearl River Delta. The Weather Research and Forecasting (WRF) model is employed to dynamically downscale and simulate summer climate change characteristics during historical periods and future warming scenarios of 1.5/2 °C. Then, in order to dynamically investigate the changes in non-industrial electricity consumption in cities after warming, we developed a non-industrial electricity consumption estimation model based on degree days and GDP. The regression model can well reproduce non-industrial electricity consumption in summer. Under future warming scenarios of 1.5/2 °C, the results indicate an annual growth trend in non-industrial electricity consumption due to global warming. Under a 1.5 °C warming scenario, non-industrial electricity consumption in both Guangzhou and Zhuhai increases, with Guangzhou experiencing a larger increase of about 10 terawatt-hours (TWh) compared to the historical period. However, under a 2 °C warming scenario, non-industrial electricity consumption in both cities slightly decreases compared to the 1.5 °C warming scenario, with a maximum decrease of 874 million kilowatt-hours.

Summer electricity consumption and its drivers in urban areas

The issue of energy consumption is receiving increasing attention due to the growth of the global population and urbanization rate. This study comprehensively analyzed the independent effects, spatial varying effects, and interactive effects of potential factors on summer electricity consumption (EC) by using the geographical detector and geographically weighted regression model. Finally, the study area was partitioned into clusters based on the GWR local coefficients to provide zonal customized policy implications. Results found that floor area ratio (FAR) was the key factor that influenced EC. As for independent effects, FAR independently explained 36.3% of the variance of the EC. As for spatial varying effects, the association between FAR and EC was found to be spatially non-stationary. This association was positive in high FAR regions and vice versa in low FAR regions. As for interaction effects, FAR ∩ land surface temperature was identified as the factor pair with the highest interactive explanatory power. Finally, the study area was divided into four clusters, and customized policy implications were proposed based on the local relationship between EC and factors. This study provides a new perspective for understanding urban energy consumption, which will contribute to sustainable development and energy consumption management.

Development of city-scale air pollutants and greenhouse gases emission inventory and mitigation strategies assessment: A case in Zhengzhou, Central China

The development of anthropogenic air pollutants and greenhouse gases (GHGs) emission inventory is important for air pollution and climate change. This study developed a high-resolution emission inventory of consistent sources of air pollutants and GHGs in Zhengzhou. Designed scenarios with 2030 as the target year to estimate future emissions from power plants and on-road mobile. The 2019-based total emissions of SO2, NOx, CO, PM10, PM2.5, VOCs, NH3, CO2, CH4, and N2O were 39.2, 174.6, 586.9, 134.1, 59.2, 176.8, 19.3, 83,014.8, 239.3, and 4.3 kt, respectively. Stationary combustion and mobile source were the top contributors to SO2, NOx, CO, and CO2 emissions. PM10 emissions were mainly from fugitive dust, while CH4 emissions were other sources. Most PM2.5 and VOCs emissions came from industrial process. Agriculture was the primary source of NH3 and N2O emissions. Most air pollutants and GHGs were mainly concentrated in the main urban area, which were closely related to population density, traffic flow, and industrial activities, while winter heating and higher electricity consumption in summer were the main reasons for higher emissions during these seasons. Air pollutants and GHGs from power plants and on-road mobile are reduced by 16.0%–84.7% in the best reduction scenario.

Indoor temperatures affected by phase-change materials

Energy costs are rapidly rising around the world and it is important to find a way to reduce energy consumption. Energy consumption in buildings can account for up to 40% of total energy consumption in developed European countries due to an increase in living space per person, an increase in the need for air conditioning, an increase in the number of appliances used in households, and other factors. Due to the increasingly frequent high temperatures during the summer and the increase in electricity consumption, it is very important to find a way to decrease indoor temperatures in urban residential buildings without using more energy, given the severe energy crisis that has engulfed Europe and the high percentage of energy and electricity consumption in the residential sector. Installation of phase changeable materials is one method for improving the thermal envelope of a building by increasing the thermal capacity of the envelope and thus affecting the reduction of indoor temperature oscillations and, consequently, reduction of summer electricity consumption. In this study, the TRNSYS software package was used to simulate and compare the indoor air temperature in typical detached houses built in period 1946 and 1970 in the Belgrade area, for both, the case without and the case with installed phase change (PCM). It was shown that incorporating a PCM with a melting temperature of 25?C into the inter-floor construction of the house could significantly improve comfort conditions by reduce indoor temperature fluctuations during the warm period without consuming additional energy. When the temperature outside is around 30?C, the maximum air temperature in the house drops by about 2?C.

Coupled hydro-mechanical analysis of seasonal underground hydrogen storage in a saline aquifer

Hydrogen is promising an efficient and viable solution for low-carbon fuel for different purposes, such as transportation, manufacturing, and electricity. Fluctuating renewable energy production, however, can lead to a temporary imbalance between demand and supply. Nonetheless, it is feasible to mitigate this mismatch by converting the surplus wind power to hydrogen and storing it in geological (subsurface) systems. This work investigates the applicability of underground hydrogen storage in a saline aquifer at the Powder River Basin of Wyoming State. Thus, a 3D coupled hydro-mechanical simulation is presented to evaluate the hydraulic and geomechanical effects during three annual injection-reproduction cycles. A fully calibrated one-dimensional mechanical model has been constructed to characterize the 3D geomechanical model. The simulated results show that the designed storage scenario can be operated with reasonable recovery efficiency such that 78% of injected hydrogen can be extracted to meet 16.7% of household summer electricity consumption for the considered scenario in this study. The surface uplift is highly correlated with the cumulative amount of hydrogen injection and production, and a maximum magnitude of 1.6 cm has been estimated. Integrity analysis of subsurface rock and caprock based on the Mohr-Coulomb criterion demonstrates the safety of underground hydrogen storage at the selected site.

Combination Forecasting Model of Daily Electricity Consumption in Summer Based on Daily Characteristic Meteorological Factors

Daily electricity consumption in summer is affected by numerous meteorological factors. In order to improve the accuracy of daily electricity consumption forecasting, a summer daily electricity consumption combination forecasting model based on daily characteristic meteorological factors is proposed in this paper. Firstly, the relationship between various meteorological indexes and daily electricity consumption is analysed considering the coupling effect and accumulative effect of meteorological factors on daily electricity consumption, and a single forecast model of daily electricity consumption is established. Then the meteorological mapping function is designed to evaluate the impact of each meteorological index on daily electricity consumption, and the weight of each single forecasting model is calculated. Finally, a combination forecasting model of daily electricity consumption in summer is established. The parameters of meteorological mapping function are optimized by adaptive training and virtual forecasting, and solved by genetic algorithm. Taking the daily electricity consumption in Chongqing in the summer of 2018 as an example, the results have shown that the proposed combination forecasting model can effectively improve the accuracy of daily electricity consumption forecasting.

Energy Saving Can Kill: Evidence from the Fukushima Nuclear Accident

Following the Fukushima nuclear accident, Japan gradually shut down all its nuclear power plants, causing a country-wide power shortage. In response, the government launched large-scale campaigns that aimed to reduce summer electricity consumption by as much as 15% in some regions. Because electricity use plays a key role in mitigating climate impacts, such policies could potentially damage the population’s health. Exploiting the different electricity-saving targets set by different regions, we show that the reduction in electricity consumption indeed increased heat-related mortality, particularly during extremely hot days. This unintended consequence suggests that there exists a trade-off between climate adaptation and energy saving.

Energy Saving Can Kill: Evidence from the Fukushima Nuclear Accident

Following the Fukushima nuclear accident, Japan gradually shut down all its nuclear power plants, causing a country-wide power shortage. In response, the government launched large-scale campaigns that aimed to reduce summer electricity consumption by as much as 15% in some regions. Because electricity use plays a key role in mitigating climate impacts, such policies could potentially damage the population’s health. Exploiting the different electricity- saving targets set by different regions, we show that the reduction in electricity consumption indeed increased heat-related mortality, particularly during extremely hot days. This unintended consequence suggests that there exists a trade-off between climate adaptation and energy saving.

Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the earthquake.

Research on Relation between El Nino Climate and Summer Electricity Consumption

El Nino is a typical climate phenomena. Such phenomena would have influence on climate in China and furthermore impact the electricity condition. This paper is purposed to explore how El Nino phenomena affecting electricity and make prediction on summer electricity consumption. Since meteorological characteristics are complex and multiplex, a variety of meteorological factors should be considered and the paper used Body Feeling Temperature to measure it. Furthermore, to make prediction on summer electricity, the paper used the Pearson Analysis to measure the correlation between weather and electricity and then extracted the weather-used electricity from the whole society electricity using least square method. Finally, the paper built the model on relation between weather-used electricity and body feeling temperature, and took Beijing as an example to make electricity prediction. The prediction idea and model the paper put forward is reliable and practicable.

Impacts of Climate Change on Seasonal Residential Electricity Consumption by 2050 and Potential Adaptation Options in Alexandria Egypt

Climate change and associated more frequent, hot or cold, extreme/weather events, as well as increasing temperature may increase future residential demand for electricity for heating and cooling purposes. The paper in hand intends to assess potential impacts of increasing temperature attributed to climate change on seasonal residential electricity consumption in Alexandria city, Egypt. Additionally, it aims to identify and discuss potential soft and hard adaptation options to such impacts. For this purpose, seasonal changes in electricity consumption were investigated. For this purpose, data on monthly residential electricity consumption, population size and income levels at district level as well as maximum monthly temperature in Alexandria city, Egypt over the period 2007-2016 were collected. This is followed by developing a panel-data model to simulate influence of temperature on residential electricity consumption. It was found that there is a significant growth trend over the study period as well as considerable seasonal variation with summer season experienced significant increase in consumption. It was found that increasing temperature, under RCP 2.6 and RCP 8.5, may contribute to significant increase in residential summer electricity consumption by 2050. Different adaptation options to such an increase in consumption, both soft and hard, have been identified and assessed.

Urban form and household electricity consumption: A multilevel study

While urban form affects building energy consumption, the pathways, direction and magnitude of the effect are disputed in the literature. This paper uses a unique dataset to examine the effect of urban form on residential electricity consumption in Ningbo, China. Using survey and utility bill data of 534 households in 46 neighborhoods in the city, we model the electricity use of households using a multi-level regression model. We find that neighborhood street configuration and tree shade are important in controlling residential electricity consumption and, consequently, greenhouse gas emissions. Our results suggest that seasonality and dwelling type condition the effect of neighborhood densities on electricity consumption. Neighborhood density is associated with household electricity consumption in summer months, while there is no such association in winter months. As neighborhood density increases, households in slab and tower apartments in dense urban neighborhoods consume more electricity in summer months, which can be partly explained by exacerbated heat island effect. Interestingly, the neighborhood density is negatively associated with summer electricity consumption for single-family houses, suggesting that the effect of neighborhood density is different for different types of dwelling units.

Heat-Related Mortality in Japan after the 2011 Fukushima Disaster: An Analysis of Potential Influence of Reduced Electricity Consumption.

Background:In March 2011, the Great East Japan Earthquake devastated several power stations and caused severe electricity shortages. This accident was followed by the implementation of policies to reduce summer electricity consumption in the affected areas, for example, by limiting air-conditioning (AC) use. This provided a natural experimental scenario to investigate if these policies were associated with an increase in heat-related mortality.Objectives:We examined whether the reduced electricity consumption in warm season modified heat-related mortality from 2008 to 2012.Methods:We conducted prefecture-specific interrupted time-series (ITS) analyses to compare temperature–mortality associations before and after the earthquake, and used meta-analysis to generate combined effect estimates for the most affected and less affected areas (prefectures with or reductions in electricity consumption, respectively). We then examined whether the temperature–mortality association in Tokyo, one of the most affected areas, was modified by the percent reduction in electricity consumption relative to expected consumption for comparable days before the earthquake.Results:Contrary to expectations, we estimated a 5–9% reduction in all-cause heat-related mortality after the earthquake in the 15 prefectures with the greatest reduction in electricity consumption, and little change in the other prefectures. However, the percent reduction in observed vs. expected daily electricity consumption after the earthquake did not significantly modify daily heat-related mortality in Tokyo.Conclusions:In the prefectures with the greatest reductions in electricity consumption, heat-related mortality decreased rather than increased following the Great East Japan Earthquake. Additional research is needed to determine whether this finding holds for other populations and regions, and to clarify its implications for policies to reduce the consequences of climate change on health. https://doi.org/10.1289/EHP493

Experimental Evaluation of Simple Thermal Storage Control Strategies in Low-Energy Solar Houses to Reduce Electricity Consumption during Grid On-Peak Periods

There is growing interest in zero-energy and low-energy buildings, which have a net energy consumption (on an annual basis) of almost zero. Because they can generate both electricity and thermal energy through the use of solar photovoltaic (PV) and solar thermal collectors, and with the help of reduced building thermal demand, low-energy buildings can not only make a significant contribution to energy conservation on an annual basis, but also reduce energy consumption and peak demand. This study focused on electricity consumption during the on-peak period in a low-energy residential solar building and considers the use of a building’s thermal mass and thermal storage to reduce electricity consumption in summer and winter by modulation of temperature setpoints for heat pump and indoor thermostats in summer and additional use of a solar heating loop in winter. Experiments were performed at a low-energy solar demonstration house that has solar collectors, hot water storage, a ground-coupled heat pump, and a thermal storage tank. It was assumed that the on-peak periods were from 2 pm to 5 pm on hot summer days and from 5 pm to 8 pm on cold winter days. To evaluate the potential for utilizing the building’s thermal storage capacity in space cooling and heating, the use of simple control strategies on three test days in summer and two test days in the early spring were compared in terms of net electricity consumption and peak demand, which also considered the electricity generation from solar PV modules on the roof of the house.

Statistical analysis of residential building energy consumption in Tianjin

To analyze the effect of energy conservation policies on energy consumption of residential buildings, the characteristics of energy consumption and indoor thermal comfort were investigated in detail in Tianjin, China, based on official statistical yearbook and field survey data. A comprehensive survey of 305 households indicates that the mean electricity consumption per household is 3215 kWh/a, in which annual cooling electricity consumption is 344 kWh/a, and the mean natural gas consumption for cooking is 103.2 m3/a. Analysis of 3966 households data shows that space heating average intensity of residential buildings designed before 1996 is 133.7 kWh/(m2·a), that of buildings designed between 1996 and 2004 is 117.2 kWh/(m2·a), and that of buildings designed after 2004 is 105.0 kWh/(m2·a). Apparently, enhancing the performance of envelops is effective in reducing space heating intensity. Furthermore, the results of questionnaires show that 18% of the residents feel slightly warm and hot respectively, while 3% feel slightly cold in winter. Therefore, the electricity consumption in summer will rise for meeting indoor thermal comfort.

Interaction between urban microclimate and electric air-conditioning energy consumption during high temperature season

With global climate changing, urban microclimate is deteriorating at a faster rate than before in many cities. In this paper, the significant effect of the deterioration of urban microclimate on air-conditioning energy consumption (ACEC) is studied. Cumulative effect (CE) has enormous influence on ACEC and it can also strengthen the influence of urban heat island effect (UHIE), which has not been recognized by previous literatures. UHIE, temperature and humidity effect (THE) and CE are taken into consideration via revising perceived temperature to precisely estimate ACEC caused by urban microclimate. The result shows the ACEC estimated in this paper is much larger than that reported in previous literatures. Our study shows electric ACEC resulting from the comprehensive influence of microclimate accounted for 11.28% of total summer electricity consumption and this percentage reached 20.4% during the peak load period in Beijing in 2005. In turn, the increased ACEC contributes to the increase of urban heat island intensity. Based on the study, it’s discovered that the interaction between urban microclimate and ACEC, which is a positive feedback with saturation and time-lag.

Susceptibility of the European electricity sector to climate change

The electricity system is particularly susceptible to climate change due to the close interconnectedness between electricity production, consumption and climate. This study provides a country based relative analysis of 21 European countries' electricity system susceptibility to climate change. Taking into account 14 quantitative influencing factors, the susceptibility of each country is examined both for the current and projected system with the result being a relative ranked index. Luxembourg and Greece are the most susceptible relatively due in part to their inability to meet their own electricity consumption demand with inland production, and the fact that the majority of their production is from more susceptible sources, primarily combustible fuels. Greece experiences relatively warm mean temperatures, which are expected to increase in the future leading to greater summer electricity consumption, increasing susceptibility. Norway was found to be the least susceptible, relatively, due to its consistent production surplus, which is primarily from hydro (a less susceptible source) and a likely decrease of winter electricity consumption as temperatures rise due to climate change. The findings of this study enable countries to identify the main factors that increase their electricity system susceptibility and proceed with adaptation measures that are the most effective in decreasing susceptibility.

HOUSEHOLD ATTRIBUTES AND ELECTRICITY CONSUMPTION OF PHOTOVOLTAIC SYSTEM OWNERS

Household attributes and electricity consumption of photo-voltaic-system owners and non-owners are investigated by using an internet questionnaire.It was found that the photo-voltaic-system owners have higher income and try to conserve energy more positively than the non-owners. The photo-voltaic-system owners positively invest in solar water heaters, insulated walls, double windows, and LED bulbs. Installed capacity of the majority of the photo-voltaic-systems ranges 3 to 4 kW. Most of the owners introduce the photovoltaic systems for the purpose of saving money on electricity when they build or rebuild their house.The electricity consumption in summer shows a statistically significant difference between the photo-voltaic-system owners and non-owners while the electricity consumptionin winter doesn't.

Proposed Modifications for Models of Heat Transfer Problems Involving Partially Melted Phase Change Processes

Abstract Air conditioning electricity consumption in summer represents a challenge in many areas with hot and humid climates. When incorporated into lightweight residential building walls, phase change materials (PCMs) can increase the effective thermal mass of the wall, which in turn will shift part of the cooling load to off-peak times and lower the peak space cooling load of the building. From analyses of experimental data, it was found that it was very likely that the PCMs, once integrated into the walls, would “start” the phase change process from partially melted states. Currently used simulation models, including the most widely accepted models, such as the effective heat capacity method and the enthalpy method, come short when handling phase change processes that start from partially melted states. The characteristics of how the heat is absorbed or released during the phase change process were studied through experimental and theoretical analyses. A differential scanning calorimeter (DSC) method and its detailed steps, used to obtain latent heat of fusion distribution along the phase change temperature range, are presented. Based on the DSC test data, a modified PCM model for a paraffin-based PCM was developed.

Modelling the impact of temperature on summer electricity consumption in Kuwait

Monthly electricity consumption data for Kuwait (1975–1982) were investigated to model the impact of ambient temperature, expressed in terms of cooling degree days (CDDs), on consumption. Linear and quadratic models were used in the analysis. It is shown that quadratic models make reasonable predictions of base monthly consumption and account for the two-fold effect of ambient temperature on consumption for cooling, i.e. its impact on the magnitude of the cooling demand and the rate of power consumption per unit of cooling output.