Electric Home Research Articles

Day-Ahead Scheduling of Electric Vehicles and Electrical Storage Systems in Smart Homes Using a Novel Decision Vector and AHP Method

The two-way communication of electricity and information in smart homes facilitates the optimal management of devices with the ability to charge and discharge, such as electric vehicles and electrical storage systems. These devices can be scheduled considering domestic renewable energy units, the energy consumption of householders, the electricity tariff of the grid, and other predetermined parameters in order to improve their efficiency and also the technical and economic indices of the smart home. In this paper, a novel framework based on decision vectors and the analytical hierarchy process method is investigated to find the optimal operation schedule of these devices for the day-ahead performance of smart homes. The initial data of the electric vehicle and the electrical storage system are modeled stochastically. The aim of this work is to minimize the electricity cost and the peak demand of the smart home by optimal operation of the electric vehicle and the electrical storage system. Firstly, the different decision vectors for charging and discharging these devices are introduced based on the market price, the produce power of the domestic photovoltaic panel, and the electricity demand of the smart home. Secondly, the analytical hierarchy process method is utilized to implement the various priorities of decision criteria and calculate the ultimate decision vectors. Finally, the operation schedule of the electric vehicle and the electrical storage system is selected based on the ultimate decision vectors considering the operational constraints of these devices and the constraints of charging and discharging priorities. The proposed method is applied to a sample smart home considering different priorities of decision criteria. Numerical results present that although the combination of decision criteria with a high rank of electricity demand has the highest improvement of technical and economic indices of the smart home by about 12 and 26%, the proposed method has appropriate performance in all scenarios for selecting the optimal operation schedule of the electric vehicles and the electrical storage system.

The New Renewable Energy Hybrid Systems for Simple Home Electricity Purposes

The New Renewable Energy Hybrid Systems for Simple Home Electricity Purposes

Optimal scheduling of electrical and thermal resources and appliances in a smart home under uncertainty

The development of renewable energy sources, using the Combined Heat and Power (CHP), along with controllable appliances, has provided new opportunities for scheduling resources and consumption in smart homes. This paper proposes a framework for the optimal scheduling of electrical appliances and sources of electricity and heat in a smart home. The smart home is able to purchase electricity through bilateral contracts and spot market. Real-Time Pricing (RTP) and Inclining Block Rate (IBR) tariffs are considered in the spot market. Uncertainties related to production of renewable resources, spot market prices and usage time of inelastic non-shiftable appliances are modeled by scenarios. The presented framework is modeled as a two-stage stochastic optimization problem, with the aim of minimizing the expected cost of the smart home. Then, the problem is formulated in the form of MILP problem. The simulation results showed that the cogeneration of electricity and heat significantly reduced the expected cost of the smart home by 125% compared to the base case study. Meanwhile, the Peak to Average Ratio index (PAR) due to the distribution of consumption along the scheduling horizon has decreased by 35% compared to the base case study.

The electric home health care routing and scheduling problem with time windows and fast chargers

This paper introduces the electric home health care routing and scheduling problem with time windows and fast chargers. The problem aims to construct the daily routes of health care nurses so as to provide a series of services to the patients located at a scattered area. The problem minimizes the total cost, which comprises of total traveling cost of electric vehicles, total cost of uncovered jobs, and total costs of recharged energy. We develop an adaptive large neighborhood search heuristic, which contains a number of advanced efficient procedures tailored to handle specific features of the problem. The paper conducts extensive computational experiments on generated benchmark instances and assesses the competitiveness of the heuristic. Results show that the heuristic is highly effective on the problem. Our analyses quantify the advantages of considering all charger technologies, i.e., normal, fast- and super-fast. We show that the downgrading of competence levels of jobs yields an improvement in total cost.

Home Energy Upgrades as a Pathway to Home Decarbonization in the US: A Literature Review

This work aims to characterize how home energy upgrade projects and programs in the US have evolved over the past decade. It also identifies what changes are needed to drive expansion of the US energy retrofit market in such a way that addresses carbon emissions from buildings, improves resilience and upgrades the housing stock. This review focuses on whole-home energy upgrades, targeting deep energy retrofit savings of >30%. The topics we cover include trends in home electrification, US and European home energy upgrade programs, energy upgrade measure costs, business economics, and health effects. Key changes in project design noted in this review include: (1) the electrification of dwellings with rapidly improving heat pump systems and low-cost solar photovoltaic technology; and (2) a shift away from high-cost building envelope strategies and towards more traditional home performance/weatherization envelope upgrades. Promising program design strategies covered include: (1) end-use electrification programs; (2) novel financing approaches; (3) the use of carbon-based program and project metrics; and (4) “one-stop shop” programs. Based on the existing market barriers, we suggest that the industry should adopt new project performance metrics. Additionally, market drivers are needed to spur widespread energy upgrades in the US housing stock. Costs must be reduced, and projects designed to appeal to homeowners and contractors.

Platform of Intelligent Control of Indoor Lighting integrated into LVDC Distribution System: A Case Study in the Technical University of Ambato

Currently, inefficient use of electricity in homes, businesses, schools, and industries requires the implementation of policies, mechanisms, and technological innovations of rational use of energy. In this sense, the implementation of new distribution systems, low-voltage direct current, LVDC, is presented as a technological solution for energy saving as well as for the efficiency for end users and for energy distribution companies’ power. The emergent of new distribution systems such as LVDC has encouraged the development of innovative methods and components for power to low voltage DC, which are applied to lighting systems, datacenters, and interior spaces. Existing experience about LVDC distribution systems have shown that reducing energy loss is proportional to increased levels of DC voltage. In addition, conversion AC/DC systems have higher losses than conversion DC/DC ones. Therefore, the implementation of LVDC systems is comparatively more efficient than traditional distribution methods of alternating current. The massive integration of LVDC distribution systems will significantly reduce energy losses and increase the efficiency of energy end users. In this article, the implementation of a cloud platform control and management of an isolated distribution system that feeds LVDC lighting loads is described. Also, the conceptual development of integration of LVDC system with a renewable generation, which supplies current to the lighting system is presented.

Engaging Hard-to-Reach Audiences through Internal Interdisciplinary and External Diverse Collaborations

Through a combination of internal and external collaborations, consumer-based energy education designed for hard-to-reach audiences was successfully delivered statewide by an interdisciplinary Extension team. Program participants representing rural residents, senior citizens, and low-income audiences demonstrated improvements in knowledge and increased intention to change their home electricity usage behaviors. This outreach work can serve as a model for other Extension services to combine interdisciplinary teams with community partnerships to reach underserved audiences statewide.

Mobile Phone Based Home Surveillance System

This paper presents an application of the GSM technology. Using the public GSM networks, a mobile phone based home surveillance system has been designed. The system automatically sends sms messages to specified phone / phones in case any door or window is opened by some intruder. The system also allows the homeowner monitoring and controlling the electrical home appliances via the mobile phone by sending commands in the form of SMS messages and receiving the appliances status. Virtual control panel is realized using VB on windows 98. Electronic circuit to control security and electrical appliances is interfaced to PC using PCL-812 Lab card. This home surveillance system has been tested and found to very effective in security control as well as controlling and monitoring electrical home appliances virtually from any place.

Development of new renewable energy hybrid system for simple home electricity purposes

The need for energy has now become a major problem that is increasingly complex in all countries in the world to support their economic growth. These various conditions require the need for new renewable energy that can answer these challenges. Wind energy and solar cells have become one of the solutions to reduce dependence on fossil energy. Wind energy and solar energy are actually the most promising sources of energy considering their sustainable nature and very large amounts to be used as electrical energy for lighting in simple people's homes. A wind turbine is a prime mover that utilizes wind energy to drive the turbine blades which are then transformed in the form of mechanical energy to rotate the turbine shaft. Solar energy is energy in the form of light and heat from the sun, which technology can be applied to a variety of energies, including solar thermal electrical energy. New and renewable energy with hybrid or combined systems for home-scale power plants is very much needed to ensure the continuity of the existence of electrical energy and efficiency. The combined and hybrid system models that have been developed and applied are hybrid solar cells and wind turbines.

Security Based Home Automation Using IoT Devices

The Internet of things, or IOT, is an arrangement of interrelated figuring gadgets, mechanical and advanced machines, items, creatures or individuals that are given remarkable identifiers and the capacity to move information over an organization without expecting human-to-human or human-to-PC association. One of these applications is home robotization which is utilized to control all electrical home machines naturally of by means of advanced mobile phones. This controls gadgets through a Boolean orders of valid and bogus to control to gadgets. These dampness levels for wet and dry conditions (cases) can be changed relying upon the plant necessities for plant development. This can be utilized to identify soil dampness when the dirt dampness shortage module plant watering gadget, so the plants in our nursery without individuals to make due. This aides in numerous ways like while are getting back to home and you need the AC to be on and be cooled before you happen to assuming that you neglect to turn of light or fan you want not again come to home and turn off them, rather than it you can handle with your advanced mobile phone when any place you are. This undertaking incorporates IFTTT, Blynk and Node MCU(ESP32) . At first the gadgets are associated with the Node MCU(ESP32) to the regarded ports then the sign from the Blynk application will give signs to the Node MCU(ESP32) then, at that point, the regarded port will give power supply to the gadget through Relay board and the gadget will turn on. The Blynk application is associated with google aide, through IFTTT. In IFTTT the google right hand and web hook is associated together to make this project achievement. Assuming the form in laud is given as a contribution to research aide then the gadget will turn on.

Ensuring power quality and demand-side management through IoT-based smart meters in a developing country

Population increase and the adoption of new power appliances have significantly increased electrical demands. As a result, the utility (electricity supplier) faces difficulties in maintaining the balance between supply and demand. Further, such supply and demand imbalance leads to frequent load-shedding and a drop in power quality (PQ), predominantly in the developing world. Increasing consumer awareness of energy consumption and implementing efficient demand-side management (DSM) algorithms in a metering instrument can be utilized to avoid such issues. Nowadays, access to the internet in developing nations is increasing rapidly. Hence to solve the existing limitations, the internet of things (IoT)-based smart meter (SM) is proposed and its practical application demonstrated in households in Bangladesh as a case study. The proposed SM primarily serves local and online monitoring, bidirectional data transmission, and DSM at the consumer side by maintaining PQ and peak-clipping. The MySql cloud database is used here for data storage and bidirectional data transmission between consumers and the utility. Web applications are developed for real-time data visualization, enabling consumers to track their hourly, daily, and monthly energy consumption by accessing the web page. The SM data shows that the over-voltage varied (from a nominal 220 V) within 15.45–16.36%, and the under-voltage varied between 10.45% and 11.82% from 220 V. The frequency fluctuations are found to be 2.2% under and 2.4% over the nominal value of 50 Hz (standard is nominal value ± 1%). The experimental result showed that the proposed IoT-based SM could ensure the smooth operation of electrical home appliances by maintaining PQ-related parameters (voltage and frequency) within a standard limit. Additionally, the proposed SM also helps to maintain the maximum pre-defined demand of a household during peak times through an appropriate load-clipping algorithm. The utility company can remotely define peak time hours and maximum peak demands when necessary. The real-life demonstration of the SM's operation advocated that this type of IoT-based SM could be easily adapted to maintain the balance between supply and demand through DSM application, and increase consumers' awareness of energy consumption in developing countries.

A Bidirectional Grid-Connected DC–AC Converter for Autonomous and Intelligent Electricity Storage in the Residential Sector

Controlling the cost of electricity consumption remains a major concern, particularly in the residential sector. Smart home electricity management systems (HEMS) are becoming increasingly popular for providing uninterrupted power and improved power quality, as well as for reducing the cost of electricity consumption. When power transfer is required between a storage system and the AC grid, and vice versa, these HEMS require the use of a bidirectional DC–AC converter. This paper emphasizes the potential value of an almost unexplored topology, the design of which was based on the generation of sinusoidal signals from sinusoidal half waves. A DC–DC stage, which behaved as a configurable voltage source, was in series with a DC–AC stage, i.e., an H-bridge, to achieve an architecture that could operate in both grid and off-grid configurations. Wide bandgap power switches (silicon carbide metal-oxide-semiconductor field-effect transistors [MOSFETs]), combined with appropriate control strategies, were the keys to increasing compactness of the converter while ensuring good performance, especially in terms of efficiency. The converter was configured to automatically change the operating mode, i.e., inverter or rectifier in power factor correction mode, according to an instruction issued by the HEMS; the latter being integrated in the control circuit with automatic duty cycle management. Therefore, the HEMS set the amount of energy to be injected into the grid or to be stored. The experimental results validate the operating modes of the proposed converter and demonstrate the relevance of such a topology when combined with an HEMS, especially in the case of an AC grid connection. The efficiency measurements of the bidirectional DC–AC converter, performed in grid-connected inverter mode, show that we exceeded the efficiency target of 95% over the entire output power range studied, i.e., from 100 W to 1.5 kW.

Simulation and rapid control prototyping of DC powered universal motors speed control: Towards an efficient operation in future DC homes

Universal motors are widely used in household appliances. When traditionally powered by AC, current harmonics are created which cause overheating of the windings and electromagnetic compatibility problems affecting the lifespan of the motor. Considering the remarkable comeback of DC power and its prospects in the electrification of homes, this paper proposes a control strategy for universal motors powered by DC using the rapid control prototyping feature offered by the dSPACE MicroAutoBox. A PI controller is designed using dominant-pole compensation method. The control strategy is simulated in Matlab/Simulink, then implemented in the MicroAutoBox via the Real-Time Interface. The simulation results are compared with those acquired by implementation through a laboratory test bench built around the MicroAutoBox and a dual full-bridge driver. The experimental results show that the designed PI controller managed to eliminate the static error and increased significantly the system dynamic performance by 26.5% in simulation and by 23.5% in practice. The robustness of the proposed control strategy against randomized load disturbances is proved by experimental tests. Furthermore, a significant improvement in power quality is reported.

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

A Smart Home Energy Management System Utilizing Neurocomputing-Based Time-Series Load Modeling and Forecasting Facilitated by Energy Decomposition for Smart Home Automation

The key advantage of using power-utility-owned smart meters is the ability to transmit electrical energy consumption data to power utilities’ remote data centers for various purposes, such as billing. Several useful consumer-centric use cases can also be identified for the collection and further analysis of consumers’ electrical energy consumption data from smart meters. One of the use cases is home automation. Recent related solutions for home automation involving home security and healthcare depend on the installation of sensors and/or other devices such as video cameras, which have high costs for installation and annual maintenance. Because the electrical energy consumption patterns mined from smart meter data are indicative of residents’ daily life, it is possible to develop a new home automation approach based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">energy decomposition</i> for smart home automation. Accordingly, in this work, a smart home energy management system (SHEMS) utilizing a parallel-processing-implemented, GPU-accelerated neurocomputing-based time-series load modeling and forecasting mechanism is proposed for smart home automation. Energy decomposition is used to facilitate the time-series load modeling and forecasting mechanism, which tracks appliance-level electrical energy consumption to be quantitatively modeled from circuit-level consumption, with no intrusive deployment of networked plug-level power meters for individual electrical home appliances. For the neurocomputing approach applied in this mechanism, an autoregressive multilayer perceptron methodology is compared against a stacked long short-term memory methodology. The presented neurocomputing-based time-series load modeling and forecasting mechanism facilitated by energy decomposition is capable of predicting residents’ daily behavioral patterns by nonintrusively analyzing and modeling relevant electrical home appliances based on their past trends for smart home automation.

Customer perceptions of value, satisfaction, and loyalty in the social media era: insights from electrical home appliances in an emerging economy

Customer loyalty (CS) is an outcome of all brands, which is hard to come by in the era of social media because customers are very volatile and tend to switch. Thus, this study investigated the influence of quality (product quality, delivery and installation service quality), customer perceived value, and customer satisfaction on loyalty (attitudinal and behavioural) among customers in the marketplace of electronic home appliances, as well as the equivalent moderating influence of brand trust and social media usage in those relationships. This study was conducted in Dhaka and collected data from 486 customers using a structured questionnaire and analysed in partial least squares structural equation modelling (PLS-SEM). The findings revealed that all hypotheses were accepted except delivery service quality on customer satisfaction. These findings contributed to stimulus-organism-response theory and provided several insights to practicing managers in their developing marketing strategies to maintain customer loyalty in electronic home appliances.

Kvalitet brenda, potrošačke emocije i odluke o kupovini mašina za pranje veša

The largest number of studies on the determinants of the consumer's decision to purchase washing machines have explored the influence of the price, the product quality, the perceived value and related constructs without the effects made by consumption emotions. Therefore, the purpose of this study is to determine the impact of brand quality, consumption emotions and socioeconomic factors on the consumer's decision to purchase washing machines in Nigeria's Delta State. The data used in the study were obtained from a cross-section of 385 consumers drawn from Asaba, Sapele and Warri, the three most populous towns in Delta State. The results show that brand quality, consumption emotions and socioeconomic variables, such as the household size, the education level and income are the significant determinants of a decision to purchase washing machines in the study area. The significance of emotions as predictors of a purchase decision underscores the need for manufacturers of electrical home appliances to ensure that the design and functionality of their products elicit the positive emotions that will foster customers' attachment and loyalty to a brand in order for the manufacturers to maximize their revenue and sustain a profit.

Smart Meter Development for Cloud-Based Home Electricity Monitor System

Α cloud-based home electricity data-monitoring system, which is based on an Arduino Mega controller, is proposed for monitoring the electricity consumption (electrical power) and power quality (PQ) in home. This system is also capable of monitoring the fundamental frequency and supply-voltage transients to ensure that the appliances operate in a safe operation range. The measured data (voltage and current) are transmitted through a WiFi device between the Arduino controller and server. The transmission control protocol (TCP) server is set up to acquire the high-data transmission rate. The server system immediately displays the calculated parameters and the waveform of the acquired signal. A comparison with a standard measurement device shows that the proposed system, which can be built at a low cost, exhibits the same functions as a factory product.

Solar photovoltaic technology in isolated rural communities in Latin America and the Caribbean

The main characteristics of photovoltaic (PV) energy and its current development in Latin American and Caribbean countries (LAC); its impact on the electrification of homes, health institutions, and schools in isolated or difficult-to-access communities; and, the advantages thereof are presented and discussed by replacing the use of traditional fuels such as firewood and kerosene in order to improve inhabitants ’health as well as reducing CO2 emissions. Countries like Nicaragua, Peru, Brazil, Argentina, and Chile stand out for their growing PV energy development in the region. A case study of the electrification process by PV systems shows very positive changes are manifested in terms of improving the quality of life of the inhabitants, and especially their physical and mental health state. In addition, CO2 emission reductions from electrifying 216 houses in the nine communities reach an annual amount of 2,164.19 t/yr, reducing firewood consumption by 2,123.39 t/yr and kerosene consumption by 40.80 t/yr However, LAC countries must adopt laws and regulations that regulate the use of PV energy, with an emphasis on recycling systems at the end of their life cycle.

Economical Electricity Home System using Solar

Economical home system can be defined as one realization of home that have a cost-effective ideal by using specific set of technologies combined with the renewable energy as a power supply. This system has a highly advance for lighting, temperature control, socket and own power supply by using solar panel. This system is developed in this project and focused on B40 community that represents the bottom 40% of income earners and also this project becomes suitable for this community for getting an energy efficiency system. Due to the COVID-19, B40 households were reported to have lost their jobs causing financial hardship and had to face the issue of high electricity bills which are very burdensome for them at all in order to pay the cost electricity for monthly. The aim of the article is to design and simulate the solar power system including battery storage in suitable software for a residential house especially in B40 community home and also to analyze the potential of battery storage in order to store the energy from solar panel. Therefore, the economical electricity home system using solar energy for B40 community is proposed in this project for producing an energy efficient system at home. In addition, an electrical floor plan and floor plan of B40 community home is designed in the SketchUp software that using basic electrical equipment such as lighting, ceiling fan and socket. The system is developed by using the MATLAB software in order to produce the result of energy efficiency by using the renewable energy which is solar system and also battery storage. According to the data produced from the calculation of old bills and new bills, the energy consumptions are calculated and also be compared before and after using the renewable energy which is using solar system. The data obtained through calculation of maximum demand in new bill is used in the simulation of solar system in MATLAB software. The results obtained show that after using an energy-efficient load, the monthly new bill is around RM 27.79 which is around RM 10.75 less than the monthly old bill before using an energy-efficient load. It can be concluded that the use of renewable energy in B40 community home can save the energy and also money.