Residential Electricity Use Research Articles

Optimizing energy consumption in smart buildings: A model for efficient energy management and renewable integration

In the current landscape of sustainable energy, integrating photovoltaic (PV) generation and electric vehicles (EVs) into household energy management systems (EMSs) has become a pivotal strategy to enhance grid sustainability in residential areas and provide economic benefits to homeowners. This article introduces an innovative approach to an energy administration framework designed for intelligent households, to seamlessly integrate EVs, both with and without PV generation. The proposed plan meticulously optimizes residential electricity expenses. It standardizes the load gradient using Time-of-Use (TOU) cost, residential electricity use fluctuations, PV generation patterns, and specific variables of EVs, including entry and exit times and charging statuses. The management method is divided into two distinct phases based on charging constraints and initial charge status. Stage A comprises three operational states contingent upon the availability of PV generation, while Stage B involves five operational states predicted based on anticipated PV generation. Through this research, the advanced control strategy facilitates precise adjustment of energy absorption by EVs from the grid and/or PV generation, along with injected energy derived from EVs to the grid. It ensures minimal residential electricity expenses and synchronizes the electrical load profiles. The findings indicate a significant reduction in residential electricity expenses and a substantial normalization of power load characteristics. Furthermore, simulation results emphasize the superior performance of the proposed plan for intelligent households fitted with both EVs and PV generation, compared to households with EVs alone, in terms of lowering expenses and normalizing load scenarios.

IoT-based smart net energy meter with advanced billing feature for residential buildings including solar PV system

Electricity consumption is rising across all industries. Residential electricity use dominates the sector. Solar photovoltaic (PV) systems on residential roofs are increasing quickly, notably in Dhaka, Bangladesh. PV power generation is high at peak sun irradiance. Due to light loads, residential structures use less electricity. PV system surplus electricity may be transmitted to the national grid. Residential customers may sell power to the government, lowering their electricity expense. Traditional energy meters make it difficult to calculate PV system consumption by load and grid injection. This is possible with net metering. Thus, this study presents an internet of things (IoT)-based smart net energy meter for home users to provide surplus solar PV power and consume grid electricity when needed. With the government's new power tariff rate, the net bill will be calculated automatically. A dedicated mobile application is used to monitor all the activities. The billing statement will be generated automatically, and the payment of that bill will be payable using a redirect link with the same mobile application. The suggested smart net energy meter will inform SMS/mobile app users of gas, smoke, and tempering. The suggested meter's performance and efficacy were evaluated using software simulation and hardware analysis.

Estimating the direct rebound effect for residential electricity use in seventeen European countries: Short and long-run perspectives

The energy saved by improving the building efficiency of European households may not be as much as expected due to a rebound effect. Based on Eurostat and World Bank annual panel data covering the period 1996–2020, this article develops dynamic panel approaches, a generalized method of moments, and first-difference specifications, to investigate the direct rebound effect of residential electricity consumption in selected European countries. Instrumental variable techniques are used to tackle the reverse causality of the electricity price in a demand model. Estimates of the direct rebound effect in residential electricity use are 18% in the short-run and 43% in the long-run. Our findings reject the hypothesis of a backfire effect in residential electricity demand. They have important implications for policy makers, suggesting the need for smart policies that consider energy consumption behaviors and decision-making processes among various households.

Planning for Heat Resilience and the Future of Residential Electricity Usage

Community resilience refers to the ability for a geographic area to respond and adapt to acute shocks and long-term stresses. Geography research is well positioned to examine how communities can adapt to the compounding effects of climate change. Our work aims to analyze the factors that influence residential electricity in the context of increasing urban temperatures in Maricopa County, Arizona, coupled with the COVID-19 pandemic. Using census tracts as our basis for analysis, we quantified factors that influence electricity use related to neighborhood characteristics, home structures, social situations, pricing policies, and work-from-home estimates. Our findings suggest that the structure of the home (e.g., number of rooms and house size) influences the variation in residential electricity use, whereas trees and small-area temperatures were not factors. We then compared above-median-income census tracts to those that were below the median income. We found fewer factors influenced electricity use in the lower income census tracts and that they were also related mostly to the home structure. Our analysis did not reveal that working from home was significant, but we did find that the average household size was significant and that the amount of influence increased from 2019 to 2020, suggesting that the stay-at-home policies from the pandemic did affect electricity use. As we consider and implement work-from-home strategies, families need to recognize that the home structure plays a crucial role in determining electricity usage.

Changes in energy use profiles derived from electricity smart meter readings of residential buildings in Milan before, during and after the COVID-19 main lockdown

The COVID-19 pandemic had a profound impact on society, causing changes in various aspects of people's lives, including their energy use habits. This has prompted a need for checking and updating standard energy use profiles, particularly for residential electricity use. To address this topic, a study was conducted on 24 multifamily buildings in Milan, using clustering to extract patterns from a database of quarter-hourly electricity use data from 2019 to 2020. This study found an increase in electricity usage during the COVID-19 lockdown period for residential buildings, likely associated with the imposed restrictions. The research also highlighted a shift in energy usage from the morning peak to the central hours of the day during the working days of the lockdown period, while a gradual increase in electricity usage throughout the day and no morning peak was observed during the Autumn (post-COVID) period. The findings can assist regulators and businesses in weighing the benefits and drawbacks of remote working and provide modellers with a complete set of daily load profiles for an Italian residential case study.

Electromagnetic Performance Investigation of Rectangular-Structured Linear Actuator with End Ferromagnetic Poles

Saving energy from domestic appliances is a focus in the effort to combat energy challenges. Linear compressors are a more efficient alternative to the traditional compressors used in refrigerators, which account for 20–40% of all residential electricity use. This article investigates the new topology of the moving magnet (MM), dual-stator single-mover linear oscillating actuator (DSSM-LOA) for linear compressor application. Both the stators were C-shaped, with coils looped across their end sides. Two permanent magnets (PMs) that were axially magnetized were housed on the mover. The PM structural shape significantly affected its fabrication cost and magnitude of magnetic flux density (B). The DSSM-LOA makes use of axially magnetized rectangular-shaped PMs because they are inexpensive and generate high electromagnetic (EM) force density. End ferromagnetic core materials were used to improve the magnetic flux, linking from the stator to the mover. All the design parameters were optimized through parametric analysis using the finite parametric sweep method. Parameters present within the three primary parameters (length, height, and depth) that were assumed constants were optimized, and the optimal dimensions were selected based on the EM force. The investigated DSSM-LOA was contrasted with traditional LOA designs, and they showed significant improvement in EM force per ampere, generally named motor constant (MC), MC per PM mass, MC density, cogging force, and stroke. Additionally, the proposed DSSM-LOA had a simple structure and low cost, and it operated in a feasible range of strokes for linear compressor application.

Wintertime patterns of residential electricity use and indoor temperature in the composite climate of India

Wintertime electricity use in India has received little attention due to the growth of residential air conditioning (AC) in the summer and monsoon seasons. This paper combines monitoring (time-series) and survey (contextual) data to examine the wintertime pattern of daily electricity current, indoor temperature, and relative humidity profiles across a sample of 64 dwellings in the city of Hyderabad representing the composite climate of India. Monitoring data were recorded for 31 days (December 2021 with a mean daily outdoor temperature of 25°C) using a CT clamp meter and Bluetooth enabled sensors. Contextual data covered dwelling and household characteristics, and use of appliances. The winter peak period of electricity use was found to occur from 6:30-10:30 in the morning, likely to be for hot water (geysers) and cooking. This is different to the late evening/night-time peak observed in the summer due to use of air conditioning (AC). Only one dwelling showed potential signs of using space heating. Higher electricity use aligned with lower peak temperatures in some homes particularly in the high-income group, indicating the potential use of AC during winter. The wintertime morning electricity peak in India could be managed using thermal stores in geysers through pre-heating which could also offer demand response opportunities.

Did new electricity progressive tariff system change energy usage pattern in Seoul apartments? Evidence from integrated multisource dataset and combined analytical models

A new electricity progressive tariff (PT) system was introduced to cities in South Korea at the end of 2016 to replace the previous one as a policy response to increased energy demand and costs in hotter summers. Public concerns have been raised over its effects on annual energy use and energy poverty. However, studies on this topic are very few due to the lack of relevant data. In the broader literature on the effect of the PT system, studies are limited in that they mostly focus on household characteristics. This study contributes to the literature and practical discussions by examining how the new PT system influences residential electricity use in 243 sample apartments in Seoul, considering a wide range of factors that impact energy use decisions. An integrated urban dataset was developed based on urban big data from multiple sources, and a combination of two models was used for analysis. The interrupted time series analysis was adopted to find whether the change in household electricity use was significant for each apartment using the dataset. A logistic regression model was then used to examine the relationships between the significance of change and influential factors in energy use and billing, household, apartment, and neighborhood. Results suggest that nearly half of the sample apartments significantly increased electricity usage, and energy and built environment factors significantly influenced the change. Furthermore, higher-income groups were found to benefit more from the new PT system. The findings provide a reference for policymakers to evaluate the new policy and develop strategies toward broad sustainability goals. Given the wicked nature of urban energy policy, suggestions were made on policy implementation design and urban data integration for more rigorous evaluation.

Urban domestic electricity consumption in relation to households’ lifestyles and energy behaviours in Burkina Faso: Findings from a large-scale, city-wide household survey

Information on actual domestic electricity use in Burkina Faso, where the urban zones and residential sector account for 74% and 33% respectively of the total electricity use, remains very challenging to find, as little research currently exists. This study aimed therefore, to provide the first ever insights into the actual urban residential electricity use. A survey with 387 households, the first large-scale, city-wide household electricity study undertaken in Burkina Faso to the authors’ knowledge, was conducted in the city of Ouagadougou. Information on the households' characteristics and behaviours were collected to yield a first comprehensive analysis on the actual city-scale domestic electricity use. Findings demonstrated an average electricity use of 2395 kWh/year by households. Cooling accounts for almost 40% of the total domestic electricity use, followed mainly by cooking and food preserving (23%) and information-communication-entertainment (19%) activities. Three groups of consumers were then formed based on their electricity use level, to investigate interactions between electricity use and households’ lifestyles. The study’s findings lay therefore, the foundations for a better understanding of actual urban domestic electricity use patterns and could help to develop more suitable policies and actions targeting energy conservation in the residential sector.

Adaptive responses: the effects of temperature levels on residential electricity use in China

Adaptive responses: the effects of temperature levels on residential electricity use in China

Impact of Urban Form on Residential Electricity Use in South Korea

Impact of Urban Form on Residential Electricity Use in South Korea

Impact of Urban Form on Residential Electricity Use in South Korea

Impact of Urban Form on Residential Electricity Use in South Korea

Electricity consumption changes following solar adoption: Testing for a solar rebound

AbstractWe use household‐level data to explore residential electricity use patterns following installation of solar panels. Solar adoption leads to an increase in total electricity consumption relative to a matched non‐adopting control group. Our point estimate translates to a rebound effect of 28.5%, suggesting that nearly a third of the electricity produced by a customer's solar panels is used for increased energy services, rather than reduced grid electricity consumption. We explore several potential drivers of an increase in electricity consumption. These results have important implications for electricity planning and policy, suggesting that rooftop solar stimulates additional demand for electricity.

A compositional kernel based gaussian process approach to day-ahead residential load forecasting

Load forecasting is an expected ability of electric power networks to enable effective capacity planning. This paper proposes a probabilistic approach to short-term load forecasting (STLF) of residential power consumption. The proposed method is based on Bayesian regression modeling. It utilizes an additive Gaussian Process (GP) to estimate climate-sensitive and calendar factors of power demand. The GP model is constructed by using a set of compositional kernels that represent the most significant interactions between input variables. Such collection is built up through a sampling method, capable of selecting the n-upmost order-based interactions. Moreover, a technique is performed to deal with challenges related to multivariate input and large dataset training complexity. The forecasting model is applied to actual power consumption data of a set of houses, located in Quebec, during winter. The results demonstrate that the suggested scheme is highly efficient to model and predict residential electricity use. Furthermore, it is competitive with other forecasting algorithms, as manifested by a comparative analysis.

Impact of tiered pricing reform on China's residential electricity use

Based on a county-level monthly panel data from four provinces and a province-level monthly panel data from 21 provinces from 2009 to 2015, we use the regression discontinuity method to examine the impacts of the tired pricing reform implemented in July 2012 on residential electricity use in China. The county-level (province-level) estimation shows that the tiered pricing reform has reduced the monthly electricity use per household by 6.5 ​kWh (8.9 ​kWh), accounting for 6.1% (7.1%) of the monthly electricity use per household. Moreover, counties and provinces with a more drastic policy shift have shown a larger decrease in residential electricity use.

IMPROVE THE INCREMENTAL BLOCK TARIFFS OF ELECTRICITY: TO HARMONIZE PRICING POLICY TARGETS IN THE NEW CONTEXT OF POWER SUPPLY AND DEMAND IN VIETNAM

The existing retail electricity tariff for households in Vietnam is the incremental block structure. However, the most recent revision of the electricity tariff structure was in 2014 which it was 7 years - a long period of change in conditions of electricity supply and consumption leading to the need to adjust this structural price appropriately. This article provides an in-depth analysis of the current residential block tariff of residential electricity use to identify shortcomings, thereby, for building options to improve this incremental block tariff structure to ensure the harmonization of different pricing targets especially the equity, efficiency and promote the electricity saving, in the new context of electricity supply and demand in Vietnam.Keywords: Electricity pricing policy, incremental block tariff, Electricity of VietnamJEL Classifications : D4, Q31, Q41, Q43. Q48DOI: https://doi.org/10.32479/ijeep.11534

Impacts of COVID-19 related stay-at-home restrictions on residential electricity use and implications for future grid stability

“Stay-at-home” orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. We conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apartment’s consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a possible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is predicted to be 15% – 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% – 53% higher than that under pre-pandemic conditions. We conclude that the projected increase in peak demand - which might arise if stay-at-home guidelines coincided with hot weather conditions - could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted.

Residential Electricity Consumers and Increasing Block Pricing Policy in Pakistan: Evidence Based on Household Level Primary Data

The purpose of this paper is to explore the efficacy of increasing block electricity pricing (IBEP) which was imposed in 2013 by the Pakistani government. The main objective of this policy is rational resource allocation and to lower the cross-subsidization to the residential sector by two other major sectors such as commerce and industry. The study is based on primary data which is collected through questionnaires from four tehsils of district Sargodha in rural as well as the urban regions. About 54.6% of households understand the electricity price scheme (IBEP) while urban users are more aware as compared to rural but urban electricity consumption is higher due to high use of home appliances. By using the regression model the elasticity of residential electricity consumption is estimated for heterogeneous consumers. The upper blocks of electricity consumption are more sensitive to price increases (e.g., the elasticity of the first to fourth block is -0.391, -0.988, -1.229, -0.955 respectively) except in the fifth block (-0.489) which indicates that higher income group pays more attention to the standard of living. The increase in the number of trees also affects the price elasticity of residential electricity use and positively influences saving behaviour. The policy which was implemented from a welfare point of view has achieved its target to a certain extent. Future guidelines for the up-gradation of electricity pricing reform in the residential sector are thus proposed.

How would real-time electricity pricing affect the Saudi power sector in the long-run?

This paper shows the effects of real-time electricity pricing (RTP) on the long-run marginal costs of power generation in Saudi Arabia. To do this, it links a multi-sector energy system model with a residential electricity use model. The energy system model contains an economic power dispatch optimization component. The residential framework embeds households, whose decisions are governed by microeconomic principles, in a physical building energy model. The analysis entails liberalizing fuel prices for the power utilities and setting the dynamic prices of electricity equal to the long-run marginal electricity supply costs. The electricity prices are solely offered to households. The key takeaways from this analysis are:•RTP, a form of dynamic electricity pricing, reduces the variability of the marginal costs for Saudi power utilities throughout the day.•Lowered capital spending by the Saudi power sector results from RTP and consequently lower power loads. Moreover, the curtailed investment in power plants would more than cover the costs of residential smart meter replacements.

Hysteresis and the Welfare Effect of Corrective Policies: Theory and Evidence from an Energy-Saving Program

This paper provides stark evidence of hysteresis—the failure of an effect to reverse itself as its underlying cause is reversed—in energy demand. We estimate that half of the 23% reduction in residential electricity use caused by a 9-month-long policy that was imposed on millions of Brazilians has persisted for at least 12 years. We examine the implications of our finding by extending the traditional welfare analysis of corrective policies to allow for hysteresis. Our estimate highlights that failing to take hysteresis into account could severely bias the welfare evaluation of policies aimed at reducing (long-run) energy demand.