Household Electricity Energy Research Articles

Building an Energy Efficiency System for Residential Households in the Context of Quantitative Feedback

The way in which households consumed electricity largely influences the total amount of energy used. This paper uses questionnaires to obtain information on the daily electricity consumption behavior of 1,140 households. A comprehensive analysis was used to determine the residential electricity consumption pattern. The study showed that, the traditional residential household electricity consumption patten has some effect on the energy saving strategies, however, it did not provide any scientific or rational information loop system overall. The quantitative feedback platform can be used to improve the level of communication among the residents regarding the electric consumption pattern, and to continuously strengthen residents’ awareness of energy saving. In addition, by combining traditional energy saving strategies with the scientific, and systematic residential household electricity energy saving system as a new idea for reducing end-use energy consumption will be useful and may also help in achieving the goal of energy saving subsequently emission reduction.

IOT BASED HOUSEHOLD ELECTRICITY ENERGY MONITORING AND CONTROL

Internet of Things (loT) has opened up a myriad of applications in many areas, including medical and healthcare networks, smart home control, and environmental surveillance. IoT is supposed to bring about a large amount of progress in the ubiquitous computing sector. IoT-based energy management programs may allow a significant contribution to energy conservation. Therefore, this paper focuses on the design and implementation of an IoT based household electricity energy monitoring and electric bulb remote control for the reduction of electrical wastage using ESP 32-bit microcontroller. The ESP 32 microcontroller was used as the brain of the entire system which processes the energy consumption, temperature reading. Temperature monitoring can assist tremendously in the explosion and burning incidence avoidance, thereby saving lives and properties. The ESP32 microcontroller also handles the internet connectivity via its inbuilt WIFI module in order to transmit the real-time energy consumption, temperature reading, and electric bulb remote control over the internet. A MATLAB app was designed to serve as user interface for monitoring the household electricity energy consumption, temperature reading and electric bulb remote control via Thingspeak cloud server from MathWorks (makers of MATLAB) and also monitors the temperature and electricity consumed by the pressing iron and the hair dryer. Whenever, the electricity consumption or temperature reading exceeds the set threshold on the MATLAB app, a notification is sent to the user’s Email. The system could be used for reducing the wastage of electrical energy in the house by proper scheduling and monitoring of the appliances

The Influence of Urban Sprawl on Household Power Intensity——Evidence from China's Urban Panel Data

The paper measures the yearly urban sprawl index and household power intensity of 285 prefecture-level and Municipality cities in China from 2004 to 2017. Through the establishment of a fixed effect model, random effect model and systematic GMM model, this paper empirically analyze the impact of urban sprawl on household power intensity, and found that there is a significant and positive effect of urban sprawl on household power intensity, that is, the higher the urban sprawl, the lower the efficiency of household electricity energy utilization will be, and this effect has a cogent robustness. On this basis, the establishment of a mediating effect model found that population agglomeration playes a significant role of the partial mediating effect in the process of urban sprawl affecting household power intensity. The conclusion of this paper provides some policy implications for the scientific and reasonable urban planning in the process of urbanization in China from the perspective of optimizing household power intensity.

Power Load Disaggregation of Households with Solar Panels Based on an Improved Long Short-term Memory Network

With the increasing application of small distributed renewable energy systems in household power supplies, when a large number of distributed renewable energy power generation systems are connected to the power grid, the time-varying output power of small solar energy, wind turbines, etc. Disaggregation and analysis of regional household electricity and renewable energy power supply systems connected to household electricity will help grid companies to conduct power dispatch management. This paper employed a two-way two-layer Long Short-term Memory deep learning network with improved input form to perform non-intrusive load disaggregation on household power with solar panels, which can monitor the load status of household electrical appliances and the output power of solar power generation system in real time. The power situation provides a decision basis for optimizing the response value of household energy demand and improving the demand of the power system from the response management level. The combined dataset from UK-DALE and kaggle’solar panel power generation data is adopted to train and test the proposed improved Long Short-term Memory network. The test results show that the proposed algorithm is applied to the household electric load disaggregation with solar panels, with high accuracy and reliability.

Domestic hot water technology transition for solar thermal systems: An assessment for the urban areas of Maputo city, Mozambique

Solar thermal systems have been widely used to increase energy efficiency in residential sector, since it became one of the top priorities in many countries to mitigate the electricity shortage. Thus, for better deployment of solar thermal systems in the residential sector it is important to understand the household electricity consumption and energy usage for domestic hot water, though developing countries lack this type of accurate data.This work assesses a domestic hot water technology transition to solar thermal systems in the urban areas of developing countries, taking as case study Maputo city, in Mozambique.First, a survey was made to the domestic hot water needs, demand and usage, in 700 households, 28 neighbourhoods of Maputo, having identified the sources and technologies used to heat water and quantified the domestic hot water needs. Then, the impact on energy demand, cost and CO2 emissions of domestic hot water technology change to solar thermal systems was modelled as well as the impact on electricity grid.The survey results point that the predominant energy sources used for domestic hot water in urban areas are electricity and biomass with nearly 46% and 41% shares, respectively. Further, results show that the domestic hot water technology used depends on household income, being the electric water heaters mostly used in households with relatively high-income.The technology transition to solar thermal systems results in a positive impact on the grid by reducing up to 65.7% the domestic hot water electricity demand and 78.7% of the CO2 emissions, while the economic savings are up to 244 USD/household/year. However, peak load is expected to increase by 11%, suggesting the need for load management policy implementation.

Effect of population age structure on capacity for biomass cogeneration: A case study of a rural area in China

To improve the overall efficiency of biomass cogeneration, a case study was conducted in a rural area to investigate the effect of the age structure of the local population on the total capacity of the biomass cogeneration system. The age-structure-based energy consumption data of 150 households were obtained through a questionnaire survey. The data treatment and function fitting yielded functional relationships between the average family age and the annual household electricity, heat, total energy consumptions and the heat–electricity ratio of biomass cogeneration. Conclusions can be summarized as follows: (1) The annual household electricity, heat and total energy consumptions peak at average family ages of approximately 40, 60 and 55, respectively. The heat–electricity ratio of biomass cogeneration peaks at an average family age of approximately 68. (2) During the heating period, the heat–electricity ratio of biomass cogeneration is positively related to the difference between indoor and outdoor temperatures, while during the non-heating period, the ratio is stable. (3) The total capacity of biomass cogeneration estimated based on the age structure of the local population (Method A) may not be consistent with that estimated based on the per-capita energy consumption (Method B). As the total energy consumption varies in a parabolic pattern with the average family age, the estimate yielded by Method A is smaller than that yielded by Method B if the average family age is smaller than 35 or larger than 73; the two methods yield similar estimates if the average family age falls in the range of 35–73.

Performances and economic analysis of small photovoltaic–electricity energy storage system for residential applications

Currently, the need to address the issues arising from the uncontrolled growth of photovoltaic installations, such as intermittence and unpredictability of the generation that cause loss of balance in the grid, becomes unavoidable. Promising solutions for minimizing grid injection are the combination of photovoltaic generation with electricity energy storage and load management, the latter commonly known as Demand Side Management. These strategies together with incentives for self-consumption or energy independence from the network will allow facilitating the integration of the always-increasing generation of renewable energy. In Europe, the usage of residential energy grid-interactive energy storage systems for buffering of surplus photovoltaic generation is becoming a field of growing interest and market activity, as a consequence of the less attractive photovoltaic feed-in-tariffs in the near future and incentives to promote self-consumption. This study aims to evaluate the energy exchange with the grid and the rate of self-consumption of combined photovoltaic–electricity energy storage systems dedicated to residential and small commercial prosumers. More specifically, several combinations of sizes of photovoltaic plant, annual household consumptions and electricity energy storage capacity were evaluated. This analysis aims to identify which arrangement among photovoltaic power, electricity consumption and battery capacity allows reaching the highest ratio of self-sufficiency and consequently minimizing the energy exchanged with the grid. Moreover, the financial analysis of the photovoltaic–electricity energy storage system has been performed for verifying the economic viability of the photovoltaic–electricity energy storage systems under the Italian current market and economic circumstances.

Climate change mitigation potential of contaminated land redevelopment: A city-level assessment method

Under the Paris Agreement, nations and cities are under increasing pressure to reduce greenhouse gas (GHG) emission. Brownfield land redevelopment promises climate change mitigation benefits; however, no studies have attempted to quantify the mitigation potential on a city level. Here we propose a method for this purpose. The method is based on life cycle assessment of GHG emission as compared to greenfield land development, in three categories: (1) primary impact (associated with physical state of brownfield sites and greenfield sites), (2) secondary impact (associated with remediation activities at brownfield sites), and (3) tertiary impact (associated with post-remediation usage of the brownfield sites and avoided usage of greenfield land). A quantitative assessment was conducted for the city of San Francisco in the US, a growing city with ambitious carbon reduction plans. City wide contaminated land remediation activities were found to render a significant secondary impact, resulting in increased GHG emission of 3.54 Mt CO2 eq. However, by averting the development of greenfield land, this negative impact was partially off-set by a primary impact reduction of 1.22 Mt CO2 eq. Moreover, the redevelopment of brownfield land offers large tertiary impact reductions due to higher housing density, less utility and road construction needs, shorter commute distances, and smaller household energy consumption. Overall, the results show that brownfield land redevelopment led to a net GHG reduction of 51.9 Mt CO2 eq. over a 70-year period, or 0.74 Mt CO2 yr−1, the equivalent of 14% of San Francisco's 5.3 Mt CO2 eq. GHG emission in 2010. It was found that reduced household electricity and space heating energy consumption and shorter commute distances were the main contributors, accounting for 41.2% and 34.0% of the tertiary impact reduction, respectively. While it is not expected that all cities can fully capture these climate change mitigation benefits, the present study demonstrates a quantification method and emphasizes the large climate change mitigation potential associated with brownfield land redevelopment. Progression of this premise will require regulators and policy makers to better align cities' climate change mitigation strategies with urban planning and development actions.

Household electricity demand forecast and energy savings potential for Vientiane, Lao PDR

This paper uses the survey data on household electricity demand from five districts of Vientiane, Lao PDR, for the demand projection up to 2030 using the end-use model. The scenario analysis is used to verify the potential of an energy-saving program by alternating selected appliances with more energy-efficient ones following the labelling standard of Thailand. The demographic structure of electrified households and the energy efficiency of electric appliances are considered as the dominant factors affecting electricity demand. Under the base-case scenario, the total electricity demand of Vientiane increased from 593 GWh in 2013 to 965 GWh in 2030. In the energy efficiency scenario, it is revealed that the appliance standard enhancement program can save total electricity demand in 2030 by 147 GWh (−15.2%), where 117 GWh (−12.1%) of which is contributed by the air conditioner and 30 GWh (−3.1%) by the lighting equipment.

Techno-economic Simulation of a Grid-connected PV System Design as Specifically Applied to Residential in Surabaya, Indonesia

Abstract This paper simulates the feasibility of installing a grid-connected photovoltaic (PV) system in a typical residential in Surabaya, Indonesia. The study was conducted to evaluate the technical, economic and environmental aspects of PV system for supplying of household electricity energy needs. A 1 kWp grid-connected PV system simulation is carried out with PVsyt and RETScreen software. The simulation expected to help in demonstrating the advantages and challenges of installing of a grid-connected PV system for residential in Surabaya.

The Demand of Household Electricity Energy (The Study Case on Household Customers of PT. PLN (Persero) Electricity in Medan)

The Demand of Household Electricity Energy (The Study Case on Household Customers of PT. PLN (Persero) Electricity in Medan)

The Analysis of Household Electricity Demand for Small Scaled Household in Medan

The research aimed to analyze the variables affecting the household electricity energy demand for strata of tariff structure 450 VA, 900 VA, and 1300 VA, as classified by PT. PLN (Persero). The research was carried out in Medan City, North Sumatra. The model was specified in single equation with endogeneous variables : the household electricity energy demand, and the exogeneous variables: consumer’s income, price of electricity with the proxy of willingness to pay per KWh (kilowatt-hours), home appliances index, number of household members, number of rooms, price of other goods (fuel and gas) as a substitution goods for electricity, and etnic.The result of the research showed that generally for strata : 450 VA, 900VA, and 1300 VA, the variables significantly influencing the household electricity energy demand were consumer’s income and WTP per KWh. Meanwhile, other variables had the various significance for every stratum. The variable of home appliances index positively and significantly influenced the household electricity energy demand for strata 900 VA and 1300 VA, but it was not significant for stratum 450 VA. This was caused by the limitation of using the home appliances. The variables of number of household members and number of rooms were positively and significantly influenced the household electricity energy demand for strata 450 VA and 900 VA. The variable of price of fuel was only significant for stratum 1300 VA.The research indicated that consumers of household in Medan City can improved the utility of electricity usage through the usage of more appliances but it was constrained by the power of electricity supplied by PT. PLN. Thus, PT. PLN should improve its management especially in electric power station.