To see the other types of publications on this topic, follow the link: Electricity appliances.
Journal articles on the topic 'Electricity appliances'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Electricity appliances.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Morvai, Peter, Miroslav Žitňák, and Stanislav Paulovič. "Rationalization of Electricity Consumption in Househ Olds." Acta Technologica Agriculturae 21, no. 2 (June 1, 2018): 69–74. http://dx.doi.org/10.2478/ata-2018-0013.
Full textAbstract:
Abstract With rationalization of electricity consumption, it is possible to obtain savings of electric energy in households, as well as financing and capital input for the electricity production. Rational use of appliances in the best operating modes can reduce the final consumption of electricity, representing a positive impact on improving the environment quality. The main objective of this paper was to measure the electricity consumption of appliances in various operating modes. The measured values from two energy suppliers were recorded and processed in tables and figures, from which we created a table of the financial costs necessary for operation of appliances in different modes. For the calculation of annual electricity consumption and electricity prices, an application allowing selection of individual products from suppliers with current electricity prices was designed. According to the tables of electricity prices, various modes of appliance operation allow the selection of the most preferred mode for appliance operation based on the lowest price, rational consumption and energy costs. The aim of the paper is to demonstrate the consumption and costs of operating appliances in certain operating modes, standby modes and their efficient use or functionally similar appliances for reduction of electricity consumption in households.
2
Aqilah, Naja, Sheikh Ahmad Zaki Shaikh Salim, Aya Hagishima, Nelidya Md Yusoff, and Fitri Yakub. "Time series data measurement on electricity consumption for selected domestic appliances in typical terrace house of Malaysia." Bulletin of Electrical Engineering and Informatics 8, no. 3 (September 1, 2019): 1144–53. http://dx.doi.org/10.11591/eei.v8i3.1601.
Full textAbstract:
This paper describes the pattern of electricity consumption from total and selected domestic appliances at a typical terrace house in Malaysia. The measured appliances can be classified into four groups on the basis of pattern of use which are ‘standby’ (TV), ‘active’ (massage chair, charger of hand phone, laptop and power bank, washing machine, air-conditioners, iron, standing fan, shower heaters, rice cooker, toaster, microwave), ‘cold’ (refrigerator) and ‘cold and hot’ (water dispenser). The major contribution of monthly electricity consumption comes from ‘cold’ appliances that consume 118.8 kWh/month followed by ‘active’ appliances that consume 87.8 kWh/month and ‘cold and hot’ appliance with 52.5 kWh/month. ‘Standby’ appliances shown a small contribution to the total electricity with 0.9 kWh/month. The amount of energy consumed depends on time-of-use, power characteristics of particular appliances as well as occupancy period.
3
Dzobo, O., and Y. Sun. "Optimal Power Control Strategy of a Hybrid Energy System Considering Demand Response Strategy and Customer Interruption Cost." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 1 (January 10, 2019): 20–29. http://dx.doi.org/10.2174/2352096511666180312142859.
Full textAbstract:
Background: The integration of distributed renewable energy sources into the conventional power system network has created opportunities for electricity customers to reduce their electricity cost. This paper investigates the optimal power scheduling of a hybrid energy system connected to the grid in the presence of demand response strategy and inconvenience cost. Methods: A new proposed method of calculating the inconvenience cost which is dependent on total home appliance load, Customer Interruption Cost (CIC) and delay time operation of home appliances is proposed. The hybrid energy system consists of solar photovoltaic (PV) module and battery bank storage system. The home appliance scheduling is formulated as a non-convex mixed integer programming with a binary decision variable to switch ON/OFF the home appliances. The optimization objective is to minimize both the total daily electricity cost and inconvenience cost of a residential customer with different time-shiftable, power shiftable home appliances and customer time preference constraints. Results: The results show that it is important to schedule home appliances and include their inconvenience cost so that home appliances are not only shifted to the lower electricity tariff periods but can also start at their customer preferred operation times. Conclusion: The results also show that the hybrid energy system is able to cater for all the energy requirements of home appliances during the day, reducing power demand from the grid by a significant percentage and thus, relieve the power system network and afford electricity consumers significant monetary savings.
4
Apaydin-Özkan, Hanife. "An Appliance Scheduling System for Residential Energy Management." Sensors 21, no. 9 (May 10, 2021): 3287. http://dx.doi.org/10.3390/s21093287.
Full textAbstract:
In this work, an Appliance Scheduling-based Residential Energy Management System (AS-REMS) for reducing electricity cost and avoiding peak demand while keeping user comfort is presented. In AS-REMS, based on the effects of starting times of appliances on user comfort and the user attendance during their operations, appliances are divided into two classes in terms of controllability: MC-controllable (allowed to be scheduled by the Main Controller) and user-controllable (allowed to be scheduled only by a user). Use of all appliances are monitored in the considered home for a while for recording users’ appliance usage preferences and habits on each day of the week. Then, for each MC-controllable appliance, preferred starting times are determined and prioritized according to the recorded user preferences on similar days. When scheduling, assigned priorities of starting times of these appliances are considered for maintaining user comfort, while the tariff rate is considered for reducing electricity cost. Moreover, expected power consumptions of user-controllable appliances corresponding to the recorded user habits and power consumptions of MC-controllable appliances corresponding to the assigned starting times are considered for avoiding peak demand. The corresponding scheduling problem is solved by Brute-Force Closest Pair method. AS-REMS reduces the peak demand levels by 45% and the electricity costs by 39.6%, while provides the highest level of user comfort by 88%. Thus, users’ appliance usage preferences are sustained at a lower cost while their comfort is kept impressively.
5
Vardhan, Pola Adithya. "Automated Electricity Control." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1408–15. http://dx.doi.org/10.22214/ijraset.2021.35264.
Full textAbstract:
Automated Electricity control with Arduino is a circuit used to achieve three tasks I.e., 1) to accurately count the number of students in a room, 2) to display The total number of people in the room on the LCD 16X2 module, And 3) to automatically turn off the electric appliances in some regions in the room where no people are there, we divide the the room in to n number of regions ,when a person enters into region 1, then the appliances in those area only turned on , when he moves from this region to another region the appliances in the first region will turned off automatically, thus the regions in which people are present only uses the electricity the unnecessary wastage of electricity would be drastically decreased, this could be implemented in big shopping malls and function halls, seminar halls etc.. when everyone leaves the room all the electric appliances will be turned off automatically. The microcontroller performs the task and receives signals from sensors, and these sensors are controlled by software stored on the EEPROM of the Arduino. this project will help reduce energy losses. This project can be implemented in a wide range of applications , where the area of rooms are very big and the electric appliance are arranged every corner of the room which is contributing of lot of electricity wastage.for Example At my university, I discovered that the lights and fans turn on even when no one is in the room. To avoid all these situations, this project was developed. When everyone leaves the room, the counter is reset to zero, turning off all lights and fans. You can avoid proxy attendance by cross-checking with the counter.
6
Shewale, Amit, Anil Mokhade, Nitesh Funde, and Neeraj Dhanraj Bokde. "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem." Energies 13, no. 16 (August 18, 2020): 4266. http://dx.doi.org/10.3390/en13164266.
Full textAbstract:
Smart grid (SG) is a next-generation grid which is responsible for changing the lifestyle of modern society. It avoids the shortcomings of traditional grids by incorporating new technologies in the existing grids. In this paper, we have presented SG in detail with its features, advantages, and architecture. The demand side management techniques used in smart grid are also presented. With the wide usage of domestic appliances in homes, the residential users need to optimize the appliance scheduling strategies. These strategies require the consumer’s flexibility and awareness. Optimization of the power demand for home appliances is a challenge faced by both utility and consumers, particularly during peak hours when the consumption of electricity is on the higher side. Therefore, utility companies have introduced various time-varying incentives and dynamic pricing schemes that provides different rates of electricity at different times depending on consumption. The residential appliance scheduling problem (RASP) is the problem of scheduling appliances at appropriate periods considering the pricing schemes. The objectives of RASP are to minimize electricity cost (EC) of users, minimize the peak-to-average ratio (PAR), and improve the user satisfaction (US) level by minimizing waiting times for the appliances. Various methods have been studied for energy management in residential sectors which encourage the users to schedule their appliances efficiently. This paper aims to give an overview of optimization techniques for residential appliance scheduling. The reviewed studies are classified into classical techniques, heuristic approaches, and meta-heuristic algorithms. Based on this overview, the future research directions are proposed.
7
Ryu, Do-Hyeon, Ryu-Hee Kim, Seung-Hyun Choi, Kwang-Jae Kim, Young Myoung Ko, Young-Jin Kim, Minseok Song, and Dong Gu Choi. "Utilizing Electricity Consumption Data to Assess the Noise Discomfort Caused by Electrical Appliances between Neighbors: A Case Study of a Campus Apartment Building." Sustainability 12, no. 20 (October 20, 2020): 8704. http://dx.doi.org/10.3390/su12208704.
Full textAbstract:
Real-time collection of household electricity consumption data has been facilitated by an advanced metering infrastructure. In recent studies, collected data have been processed to provide information on household appliance usage. The noise caused by electrical appliances from neighboring households constitutes a major issue, which is related to discomfort and even mental diseases. The assessment of noise discomfort using electricity consumption data has not been dealt with in the literature up to this day. In this study, a method that utilizes electricity consumption data for the assessment of noise discomfort levels caused by electrical appliances between neighboring households is proposed. This method is based on the differences in the usage time of electrical appliances in a collective residential building. The proposed method includes the following four steps: data collection and preprocessing, residential units clustering, noise discomfort modeling, and evaluation of noise discomfort. This method is demonstrated through a case study of a campus apartment building. Variations in the noise discomfort assessment model and measures for alleviating noise discomfort are also discussed. The proposed method can guide the application of electricity consumption data to the assessment and alleviation of noise discomfort from home appliances at an apartment building.
8
Sena, Boni, Sheikh Ahmad Zaki, Hom Bahadur Rijal, Jorge Alfredo Ardila-Rey, Nelidya Md Yusoff, Fitri Yakub, Mohammad Kholid Ridwan, and Firdaus Muhammad-Sukki. "Determinant Factors of Electricity Consumption for a Malaysian Household Based on a Field Survey." Sustainability 13, no. 2 (January 15, 2021): 818. http://dx.doi.org/10.3390/su13020818.
Full textAbstract:
Electricity-saving strategies are an essential solution to overcoming increasing global CO2 emission and electricity consumption problems; therefore, the determinant factors of electricity consumption in households need to be assessed. Most previous studies were conducted in developed countries of subtropical regions that had different household characteristic factors from those in developing countries of tropical regions. A field survey was conducted on electricity consumption for Malaysian households to investigate the factors affecting electricity consumption that focused on technology perspective (building and appliance characteristics) and socio-economic perspective (socio-demographics and occupant behaviour). To analyse the determinant factors of electricity consumption, direct and indirect questionnaire surveys were conducted from November 2017 to January 2018 among 214 university students. Direct questionnaire surveys were performed in order to obtain general information that is easily answered by respondents. On the other hand, some questions such as electricity consumption and detailed information of appliances must be confirmed by the respondents’ parents or other household members through an indirect questionnaire survey. The results from multiple linear regression analyses of the survey responses showed that appliance characteristic factors were the main variables influencing electricity consumption and house characteristics were the least significant. Specifically, air conditioners, fluorescent lamps, and flat-screen TVs emerged as appliances with the most significant effect on electricity consumption. Occupant behaviour factors had a more significant influence than socio-demographic factors. The findings in this study can be used by policymakers to develop electricity-saving strategies in Malaysia.
9
Gopi Krishna, P., K. Sreenivasa Ravi, R. Trinadh, K. Chandra Sekhar, and V. Ranjit Kumar. "Design and development of smart energy meter for effective use of electricity in IoT applications." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 115. http://dx.doi.org/10.14419/ijet.v7i2.8.10342.
Full textAbstract:
IoT (Internet of things) has delivered a venerable progression and advancements in the automation of home environments. The home automation has changed the manual frame work into robotization by making the household appliances smart which plays vital role now and more in the coming future. By connecting the household appliances to the internet for remote supervision and controlling. For better results home automation is employed with energy management strategy for better fallouts. Many energy management systems are available which are having expensive cost but are not efficient. By equipping the energy meters to home appliances, the amount of energy consumed can be calculated by each appliance. Enhanced facilities are provided to the user in this system. The remote user can monitor the electrical appliances, can turn ON and OFF through the web page. Webcam is employed in the proposed system for better functionality and to enhance the security so that remote user can observe the living home environment. A specific threshold values are specified to electrical appliances which reduces the power consumption in an effective way. The appliances will turn OFF automatically when it reaches to the specified threshold value. The implement system uses a Raspberry Pi 3 which realizes the data received form the remote users and the webcam. The data is uploaded into the web sever through Raspberry Pi which act as central server and visualization of data will be done the user in the website. The proposed and implemented system performs the monitoring and controlling of electrical appliance dynamically with low cost and efficiently which reduce the power consumption.
10
Jamil, Aqib, Turki Ali Alghamdi, Zahoor Ali Khan, Sakeena Javaid, Abdul Haseeb, Zahid Wadud, and Nadeem Javaid. "An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory." Sustainability 11, no. 22 (November 8, 2019): 6287. http://dx.doi.org/10.3390/su11226287.
Full textAbstract:
The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.
11
Joshi, Gauri, Vasundhara Sen, and Monica Kunte. "Do Star Ratings Matter?" International Journal of Social Ecology and Sustainable Development 11, no. 4 (October 2020): 40–55. http://dx.doi.org/10.4018/ijsesd.2020100104.
Full textAbstract:
Increasing environmental concerns have resulted in consumers indulging in conserving energy by curtailing energy usage rather than switching to energy efficient practices. Energy efficient appliances (EEAs) offer the dual advantages of appliance usage with reduced energy consumption. Research suggests that use of such appliances, in residences is limited. This study was thus undertaken to understand individual resident's awareness towards EEAs and factors influencing their purchase. A qualitative approach consisting of 31 personal interviews were conducted with individuals from socio-economic categories A1, A2 and B1. While awareness of EEAs was present among respondents; benefits of using such appliances were neither widely known nor easily quantifiable. Purchase decisions were ruled by appliance price but did not deter adoption, the availability of appliances in desired aesthetics and family involvement in purchase decision. Higher penetration of such appliances can be ensured if consumers can estimate exact savings in monthly electricity bills due to EEAs at the time of purchase.
12
Osama, Sarah, Marco Alfonse, and Abdel-Badeeh M. Salem. "Mining Temporal Patterns to Discover Inter-Appliance Associations Using Smart Meter Data." Big Data and Cognitive Computing 3, no. 2 (March 29, 2019): 20. http://dx.doi.org/10.3390/bdcc3020020.
Full textAbstract:
With the emergence of the smart grid environment, smart meters are considered one of the main key enablers for developing energy management solutions in residential home premises. Power consumption in the residential sector is affected by the behavior of home residents through using their home appliances. Respecting such behavior and preferences is essential for developing demand response programs. The main contribution of this paper is to discover the association between appliances’ usage through mining temporal association rules in addition to applying the temporal clustering technique for grouping appliances with similar usage at a particular time. The proposed method is applied on a time-series dataset, which is the United Kingdom Domestic Appliance-Level Electricity (UK-DALE), and the results that are achieved discovered appliance–appliance associations that have similar usage patterns with respect to the 24 h of the day.
13
Li, Mingfu, Guan-Yi Li, Hou-Ren Chen, and Cheng-Wei Jiang. "QoE-Aware Smart Home Energy Management Considering Renewables and Electric Vehicles." Energies 11, no. 9 (September 1, 2018): 2304. http://dx.doi.org/10.3390/en11092304.
Full textAbstract:
To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE.
14
Ahmed, Nauman, and Uzma Nisar. "Electricity Demand in Pakistan: A Household Analysis." Journal of Economic Impact 1, no. 2 (May 2, 2019): 34–39. http://dx.doi.org/10.52223/jei0102191.
Full textAbstract:
Availability of electricity is essential in modern age because it becomes a necessity of life. The present study used some economic and non-economic determinants that affect household demand for electricity. This study used PSLM survey data for the year 2013-14. The amount of electricity consumed by household was used as dependent variable whereas electricity price, household income, appliances, heating days, region, awareness, and rooms were taken as explanatory variables. Ordinary least square technique (OLS) was used for analysis. The findings of the study showed that Economic and demographic factors are important in determining electricity expenditure. In micro level analysis prices has strong and positive effect on electricity expenditures and it didn’t represent traditional behavior of demand with price. Price and income had positive impact during the period of study with demand for electricity. Expenditure on electricity is fairly higher during summer season. Positive and significant effect is estimated for stock of electricity appliances. Household members have significant effect on electricity expenditure but shows very smaller influence. The dummy variable for region indicates that electricity expenditure is higher for those households who are living in urban areas as compared to rural. Over the time period residential demand of electricity is increasing in Pakistan. As Pakistan is consumption oriented society and demand for appliances is increasing so government should take necessary measures to shift appliances on other resources other than electricity. Increasing use of the appliances increases demand for electricity therefore generation of electricity resources should be increased to meet this increasing demand.
15
Ashraf, A., M. Faisal, K. Parvin, Pin Jern Ker, and M. A. Hannan. "Air Conditioning for Smart Home Energy Management System." International Journal of Engineering & Technology 7, no. 4.35 (November 30, 2018): 487. http://dx.doi.org/10.14419/ijet.v7i4.35.22896.
Full textAbstract:
Smart load management system with an advanced metering infrastructure operates to monitor the electricity consumption by the load and transferring data to the utility grid. It has direct benefit to the end-users by managing the load. This system has incorporated with home appliance for achieving the goal of home energy management system (HEMS) such as efficient energy utilization of house by avoiding the wastage. Efficient loading system can strengthen the efficient power utilization and thus can save the economy greatly. Air conditioner (AC), thermostat associated with a room were selected for this purpose as they have the high demand of electricity consumption. This study mainly focuses on developing the mathematical model and simulate it for the considered home appliances to assess the trend of electricity consumption. Research proved that, considering the ambient temperature developed model can provide the specific instructions for automatic controlling of the appliances which will save the electricity consumption and utility bill of end-users compare to the manual operation of the system. Matlab /Simulink software was used to implement and justify the model.
16
Taik, Salma, and Bálint Kiss. "Household electricity usage optimization using MPC and mixed integer programming." Pollack Periodica 15, no. 1 (April 2020): 136–47. http://dx.doi.org/10.1556/606.2020.15.1.13.
Full textAbstract:
Abstract This paper discusses the control of the electric energy consumption in a household equipped with smart devices. The household consumption pattern is the result of a two-level optimization framework. The scheduling of the electric appliances is determined by the first optimization, receiving Time of Use tariffs proposed by the utility company. The scheduler considers the consumer's preferences on the powering on for each appliance. Secondly a model predictive controller is developed to control the electric heating system based on energy constraints resulting from the appliance scheduling. Simulations show the energy efficiency and an optimized electricity cost of the strategy proposed.
17
Won, An Na, and Won Hwa Hong. "A Survey on Ownership of Home Appliances and Electric Energy Consumption Status According to the Number of Household Member." Applied Mechanics and Materials 672-674 (October 2014): 2165–68. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.2165.
Full textAbstract:
With increasing trend of nuclear family, modern society is also showing a gradual increase in single households. Increase in single household leads to increased use of home appliances. Accordingly, the aim of this study was to examine ownership of electric home appliances (home appliance products that use electricity) and energy consumption status and to obtain implications for energy conservation.A survey was conducted / analyzed on 2,250 households, and the following results were obtained. First, ratio of home appliance ownership and number of appliances per household member were examined. Average number of home appliances was 10.6 for single households, 13.8 for 2-person households and 17.5 for households with 6 persons or more. Second, electric rate was found to be 46,000 won for single households and 114,000 won for households with 6 persons or more. Electric rate per member of household was rapidly reduced from <single household> to <4-person household>, showing about 50% conservation. In other words, increase in single households is regarded to have great impact on increase in energy consumption.
18
Kim, Jihyun, Thi-Thu-Huong Le, and Howon Kim. "Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature." Computational Intelligence and Neuroscience 2017 (2017): 1–22. http://dx.doi.org/10.1155/2017/4216281.
Full textAbstract:
Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM) is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM) based models have been studied very much. However, increasing appliances, multistate of appliances, and similar power consumption of appliances are three big issues in NILM recently. In this paper, we address these problems through providing our contributions as follows. First, we proposed state-of-the-art energy disaggregation based on Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model and additional advanced deep learning. Second, we proposed a novel signature to improve classification performance of the proposed model in multistate appliance case. We applied the proposed model on two datasets such as UK-DALE and REDD. Via our experimental results, we have confirmed that our model outperforms the advanced model. Thus, we show that our combination between advanced deep learning and novel signature can be a robust solution to overcome NILM’s issues and improve the performance of load identification.
19
Baharum, Aslina, Chew Yun Fai, Rozita Ismail, Ismassabah Ismail, Farhana Diana Deris, and Noorsidi Aizuddin Mat Noor. "Evaluation of appliances mobile controller system using expectation-confirmation theory model." Bulletin of Electrical Engineering and Informatics 10, no. 4 (August 1, 2021): 2119–29. http://dx.doi.org/10.11591/eei.v10i4.3061.
Full textAbstract:
Nowadays, most Malaysians have used overpower usage of house appliances. Malaysian does not have the habit of controlling the household’s electricity consumption every day. Reducing electricity consumption is better for the earth, reducing harmful greenhouse emissions and minimizing the household's overall impact. Besides, one of the safety problems that Malaysian currently face is thieves entering the house when the owner is outstation or traveling. The proposed home appliance controller application can control and calculate the power consumption of home appliances. It can also control and set automatic timing based on the light to cause thieves to realize that the house may have people since the lights were turned on. This paper aims to identify the application features of controllers for home appliances, then develop the mobile application not only for gaming or entertainment but for better, enhanced, convenience and efficiency of lifestyle and finally to evaluate the users’ acceptance towards mobile app using expectation-confirmation theory model. Results show that perceived usefulness significant with confirmation (0.61) and continuance intentions (0.69). Perceived usefulness was demonstrated to be an essential predictor of continuance intentions (0.44). With this system or app, house appliances will be communicated and under control by the house owner.
20
M. Sri Lakshmi, K., P. Sairam, V. Yeswanth, and A. Akhila. "IOT Based Monitoring Of Household Electricity Appliances." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 174. http://dx.doi.org/10.14419/ijet.v7i2.32.15398.
Full textAbstract:
A Smart Electricity meter is a new kind of electricity meter that can send meter reading and billing to the user. They are a replacement for standard meters, which use technology created decades ago .Smart electricity meters have been in development in many countries. Presently, people have to come to electricity meter to generate bill. We could not know how many units of current we have been consuming from time to time. The system we propose in this paper is a smart electricity meter which will monitor the current electricity usage and gives a notification to us which says how many units of current have been consumed and the amount we have to pay. we can also enable a setting that will notify us whenever particular units of current have been consumed. The entire consumption history of current from time to time can be monitored in the database.
21
Sri lakshmi, M., P. Sairam, V. Yeswanth, and P. Akhila. "IOT Based Monitoring of Household Electricity Appliances." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 312. http://dx.doi.org/10.14419/ijet.v7i2.32.15702.
Full textAbstract:
A Smart Electricity meter is a new kind of electricity meter that can send meter reading and billing to the user. They are a replacement for standard meters, which use technology created decades ago .Smart electricity meters have been in development in many countries. Presently, people have to come to electricity meter to generate bill. We could not know how many units of current we have been consuming from time to time. The system we propose in this paper is a smart electricity meter which will monitor the current electricity usage and gives a notification to us which says how many units of current have been consumed and the amount we have to pay. we can also enable a setting that will notify us whenever particular units of current have been consumed. The entire consumption history of current from time to time can be monitored in the database.
22
Völker, Benjamin, Marc Pfeifer, Philipp M. Scholl, and Bernd Becker. "A Framework to Generate and Label Datasets for Non-Intrusive Load Monitoring." Energies 14, no. 1 (December 25, 2020): 75. http://dx.doi.org/10.3390/en14010075.
Full textAbstract:
In order to reduce the electricity consumption in our homes, a first step is to make the user aware of it. Raising such awareness, however, demands to pinpoint users of specific appliances that unnecessarily consume electricity. A retrofittable and scalable way to provide appliance-specific consumption is provided by Non-Intrusive Load Monitoring methods. These methods use a single electricity meter to record the aggregated consumption of all appliances and disaggregate it into the consumption of each individual appliance using advanced algorithms usually utilizing machine-learning approaches. Since these approaches are often supervised, labelled ground-truth data need to be collected in advance. Labeling on-phases of devices is already a tedious process, but, if further information about internal device states is required (e.g., intensity of an HVAC), manual post-processing quickly becomes infeasible. We propose a novel data collection and labeling framework for Non-Intrusive Load Monitoring. The framework is comprised of the hardware and software required to record and (semi-automatically) label the data. The hardware setup includes a smart-meter device to record aggregated consumption data and multiple socket meters to record appliance level data. Labeling is performed in a semi-automatic post-processing step guided by a graphical user interface, which reduced the labeling effort by 72% compared to a manual approach. We evaluated our framework and present the FIRED dataset. The dataset features uninterrupted, time synced aggregated, and individual device voltage and current waveforms with distinct state transition labels for a total of 101 days.
23
Wang, Xin Tong, Xiao Bo Wang, and Hui Zhong Zhang. "Waveform Measurement and Analysis of Common Household Appliances." Applied Mechanics and Materials 599-601 (August 2014): 767–75. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.767.
Full textAbstract:
Electricity power companies have the obligation to provide qualified electrical energy to the power user, the same as electricity customers, the power company claims to provide qualified energy, electricity customers are obliged to choose the right appliances to minimize the impact on the power quality of the power system . Higher harmonics is an important indicator of the impact of power quality, household appliances majority of non-linear loads, the use of the process will produce high harmonics, although the power is not, but a huge number, pooled together, will still PQ great impact. Therefore, the measurement of electrical waveforms common household appliances, will harmonic analysis, harmonic control, or other harmonic study is instructive.
24
Mahlia,, T. M. I., H. H. Masjuki,, I. A. Choudhury, and And R. Saidur R. Saidur. "A review on energy efficiency standards and labels: present status and implementation possibilities in malaysia." ASEAN Journal on Science and Technology for Development 18, no. 1 (November 15, 2017): 71–84. http://dx.doi.org/10.29037/ajstd.201.
Full textAbstract:
This article is a review on energy efficiency standards and labels for household electrical appliances around the world. Through the review of other country experiences on energy efficiency standards and labels, we attempt to identify savings possibilities in Malaysian households. The implementation possibilities of standards and labels for various household electrical appliances in Malaysia are also examined. It is found that various household appliances in Malaysia offer some potential in reducing electricity consumption. Finally, it is concluded that there are many advantages for Malaysia to implement the standards and labels for household electrical appliances as soon as possible in order to reduce electricity bills and energy consumption in Malaysian households.
25
Li, Qiang, Kui Yang, and Tian Ji Wu. "Intelligent Detection System of Illegal Appliances’ Malignant Load of Campus Electrical Grid." Applied Mechanics and Materials 575 (June 2014): 800–804. http://dx.doi.org/10.4028/www.scientific.net/amm.575.800.
Full textAbstract:
With the appliances increasing on campus, illegal appliances caused a great security risk to the campus grid security. For malignant load of illegal appliances, we design intelligent detection system of load to solve the problem. First, this paper analyzes the forecasting method for campus electricity load, and does statistical analysis of the amount of college electricity load for 24 hours; followed by the overall design of intelligent detection system of malignant load, describing its features and performance indicators; finally, the system’s part implementation and source code. This
26
Tandon, G., and B. Natarajan. "Contribution of Appliances to Domestic Electricity Consumption." IFAC Proceedings Volumes 22, no. 17 (October 1989): 357–60. http://dx.doi.org/10.1016/s1474-6670(17)52954-7.
Full text
27
Cerna, Fernando V., Mahdi Pourakbari-Kasmaei, Luizalba S. S. Pinheiro, Ehsan Naderi, Matti Lehtonen, and Javier Contreras. "Intelligent Energy Management in a Prosumer Community Considering the Load Factor Enhancement." Energies 14, no. 12 (June 18, 2021): 3624. http://dx.doi.org/10.3390/en14123624.
Full textAbstract:
In prosumers’ communities, the use of storage batteries (SBs) as support for photovoltaic (PV) sources combined with coordination in household appliances usage guarantees several gains. Although these technologies increase the reliability of the electricity supply, the large-scale use of home appliances in periods of lower solar radiation and low electricity tariff can impair the performance of the electrical system. The appearance of new consumption peaks can lead to disturbances. Moreover, the repetition of these events in the short term can cause rapid fatigue of the assets. To address these concerns, this research proposes a mixed-integer linear programming (MILP) model aiming at the optimal operation of the SBs and the appliance usage of each prosumer, as well as a PV plant within a community to achieve the maximum load factor (LF) increase. Constraints related to the household appliances, including the electric vehicle (EV), shared PV plant, and the SBs, are considered. Uncertainties in consumption habits are simulated using a Monte Carlo algorithm. The proposed model was solved using the CPLEX solver. The effectiveness of our proposed model is evaluated with/without the LF improvement. Results corroborate the efficient performance of the proposed tool. Financial benefits are obtained for both prosumers and the energy company.
28
Jiang, Lei, Su Huai Luo, and Jia Ming Li. "Intelligent Electrical Appliance Event Recognition Using Multi-Load Decomposition." Advanced Materials Research 805-806 (September 2013): 1039–45. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.1039.
Full textAbstract:
The management of electricity system in home environments plays an important role in generating energy consumption and improving efficiency of energy usage. At present, nonintrusive appliance load monitoring (NIALM) techniques are the most effective approach for estimating the electrical power consumption of individual appliances. This paper presents our contribution in intelligent electrical appliance decomposition in home environment. It is a modified power appliance disaggregation technique based on power harmonic features and support vector machine (SVM). It has higher recognition accuracy and faster computational speed. The experimental results of the power decomposition technique on real date are presented with promising results.
29
Veras, Jaclason, Igor Silva, Plácido Pinheiro, Ricardo Rabêlo, Artur Veloso, Fábbio Borges, and Joel Rodrigues. "A Multi-Objective Demand Response Optimization Model for Scheduling Loads in a Home Energy Management System." Sensors 18, no. 10 (September 22, 2018): 3207. http://dx.doi.org/10.3390/s18103207.
Full textAbstract:
Demand Response (DR) aims to motivate end consumers to change their energy consumption patterns in response to changes in electricity prices or when the reliability of the electrical power system (EPS) is compromised. Most of the proposals found in the literature only aim at reducing the cost for end consumers. However, this article proposes a home energy management system (HEMS) that aims to schedule the use of each home appliance based on the price of electricity in real-time (RTP) and on the consumer satisfaction/comfort level in order to guarantee the stability and the safety of the EPS. Thus, this paper presents a multi-objective DR optimization model which was formulated as a multi-objective nonlinear programming problem subjected to a set of constraints and was solved using the Non-Dominated Sorted Genetic Algorithm (NSGA-II), in order to determine the scheduling of home appliances for the time horizon. The multi-objective DR optimization model not only to minimize the cost of electricity consumption but also to reduce the level of inconvenience for residential consumers. Moreover, a priori, it is expected to obtain a more uniform demand with fewer peaks in the system and, potentially, achieving a more reliable and safer EPS operation. Thus, the energy management controller (EMC) within the HEMS determines an optimized schedule for each home appliance through the multi-objective DR model presented in this article, and ensures a more economic scenario for end consumers. In this paper, a performance evaluation of HEMS in 15 Brazilian families between 1 January and 31 December 2016 is presented with different electric energy consumption patterns in the cities of Belém—PA, Teresina—PI, Cuiabá—MT, Florianópolis—SC and São Paulo—SP, with three families per city, located in the regions north, northeast, central west, south and the southeast of Brazil, respectively. In addition, a total of 425 home appliances were used in the simulations. The results show that the HEMS achieved reductions in the cost of electricity for all the Scenarios used while minimally affecting the satisfaction/comfort of the end consumers as well as taking into account all the restrictions. The largest reduction in the total cost of electricity occurred for the couple without children, resident in the city of Teresina—PI; with a drop from US$ 99.31 to US$ 90.72 totaling 8.65% savings in the electricity bill. Therefore, the results confirm that the proposed HEMS effectively improves the operating efficiency of home appliances and reduces electricity costs for end consumers.
30
Ozoh, P., S. Abd-Rahman, and J. Labadin. "A Preliminary Study on the Cost Implications and Validity of Executing a Control Strategy on Individual Appliance Usage." Circulation in Computer Science 2, no. 7 (August 20, 2017): 1–4. http://dx.doi.org/10.22632/ccs-2017-252-34.
Full textAbstract:
This study evaluates a number of power-saving measures that were applied on individual electric appliances to investigate their contributions to energy savings of the electricity network. In order to carry out the study, power-saving measures were applied on all appliances under study for certain period periods at the Universiti Malaysia Sarawak (UNIMAS). The appliances are the air conditioner (AC), computers, lightings and closed-circuit television (CCTV). As a means of validating the accuracy of models developed for electricity costs, a comparison of was done between measurements taken from the electricity network and those taken from PowerLogic PM5350 power meter (PM5350) installed for the purpose of this research. The results from model analysis show significant cost savings of 39.9%, 20.3%, 8% and 0.6% when control strategies were applied to AC, lightings, computers and CCTV
31
Nagpal, Himanshu, Andrea Staino, and Biswajit Basu. "Application of Predictive Control in Scheduling of Domestic Appliances." Applied Sciences 10, no. 5 (February 29, 2020): 1627. http://dx.doi.org/10.3390/app10051627.
Full textAbstract:
In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.
32
Wójcik, Augustyn, Robert Łukaszewski, Ryszard Kowalik, and Wiesław Winiecki. "Nonintrusive Appliance Load Monitoring: An Overview, Laboratory Test Results and Research Directions." Sensors 19, no. 16 (August 20, 2019): 3621. http://dx.doi.org/10.3390/s19163621.
Full textAbstract:
Nonintrusive appliance load monitoring (NIALM) allows disaggregation of total electricity consumption into particular appliances in domestic or industrial environments. NIALM systems operation is based on processing of electrical signals acquired at one point of a monitored area. The main objective of this paper was to present the state-of-the-art in NIALM technologies for the smart home. This paper focuses on sensors and measurement methods. Different intelligent algorithms for processing signals have been presented. Identification accuracy for an actual set of appliances has been compared. This article depicts the architecture of a unique NIALM laboratory, presented in detail. Results of developed NIALM methods exploiting different measurement data are discussed and compared to known methods. New directions of NIALM research are proposed.
33
Cannas, Barbara, Sara Carcangiu, Daniele Carta, Alessandra Fanni, Carlo Muscas, Giuliana Sias, Beatrice Canetto, Luca Fresi, and Paolo Porcu. "NILM techniques applied to a real-time monitoring system of the electricity consumption." ACTA IMEKO 10, no. 2 (June 29, 2021): 139. http://dx.doi.org/10.21014/acta_imeko.v10i2.1054.
Full textAbstract:
Non-Intrusive Load Monitoring (NILM) allows providing appliance-level electricity consumption information and decomposing the overall power consumption by using simple hardware (one sensor) with a suitable software. This paper presents a low-frequency NILM-based monitoring system suitable for a typical house. The proposed solution is a hybrid event-detection approach including an event-detection algorithm for devices with a finite number of states and an auxiliary algorithm for appliances characterized by complex patterns. The system was developed using data collected at households in Italy and tested also with data from BLUED, a widely used dataset of real-world power consumption data. Results show that the proposed approach works well in detecting and classifying what appliance is working and its consumption in complex household load dataset.
34
Setyawan, Gembong Edhi, Agung Setiabudi, Adharul Muttaqin, and Mochammad Hannats Hanafi Ichsan. "Centralized Smart Home Framework Monitoring for Power Savings." Journal of Information Technology and Computer Science 1, no. 2 (December 31, 2016): 98. http://dx.doi.org/10.25126/jitecs.2016128.
Full textAbstract:
Abstract. Electrical energy has become a staple for humans. Almost all human activities always require electrical energy. To maintain the availability of electricity at any time, then it takes the process of global electricity savings. The electricity savings can be done in two ways, the first is the development of technology to make electric appliances that require low power for operation and the second is to improve human behavior in the use of electrical appliances (turning off electrical appliances when not in use). This research aims to create a centralized smart home that can help people to monitor the condition of electrical appliances in the house and turn off automatically when not being used. Besides this system could also be used in manual mode and be controlled remotely using a smartphone through the Internet. The system is made centrally so not only for the home but can be used for many homes. After application was implemented it can monitored which device is turned on or turned off.Keywords: Smart Home, Monitoring and Power Savings
35
İzmitligil, Hasan, and Hanife Apaydn Özkan. "A home energy management system." Transactions of the Institute of Measurement and Control 40, no. 8 (February 1, 2018): 2498–508. http://dx.doi.org/10.1177/0142331217741537.
Full textAbstract:
In this study, an offline home energy management system that reduces electricity expense and peak demand without deteriorating residents’ contentment is considered. The main goal is to improve the system in the sense of reducing electricity expense, via interfering with appliances by means of interrupting as well as shifting their operation; and keeping up with the benefits of the newest technology, via plug-in hybrid electrical vehicle integration. The proposed offline home energy management system (OF-HEM) consists of smart electrical appliances, power resources (photovoltaic system, grid, backup battery), main controller, communication network and plug-in hybrid electrical vehicle. The main controller manages the power resources, appliances and plug-in hybrid electrical vehicle based on the solution of a mixed integer linear program with defined smart and energy-efficient operation constraints related to the smart appliances and power sources for data collected at the beginning of the day from the power resources and residents’ preferences. Conducted case studies demonstrate that OF-HEM significantly reduces electricity expenses and high peak demand.
36
Qu, Zhao Yang, Tian Hang Zhang, Jia Yan, and Shao Qing Xu. "An Intelligent Household Electricity Load Control Method Based on Demand Response." Applied Mechanics and Materials 740 (March 2015): 307–10. http://dx.doi.org/10.4028/www.scientific.net/amm.740.307.
Full textAbstract:
This paper presents a method for smart house electricity load control. The method, combined with TOU price and Real-time pricing, arranges various appliances and meets daily household electricity demand at the same time, so that to reduce the daily electricity consumption and realize Demand Response. First, this paper attempts to summarize problem witch need to be solved for realizing load control in a smart house. Second, the smart house load control problem was described as high-dimensional complex functions unconstrained optimization model and solved with Particle Swarm Optimization. Finally, design experiments used the method for a smart house. Experimental results show that the method can arrange various appliances and reduce electricity consumption.
37
Lesic, Vedran, Brock Glasgo, Tamar Krishnamurti, Wändi Bruine de Bruin, Matthew Davis, and Inês Lima Azevedo. "Comparing consumer perceptions of appliances’ electricity use to appliances’ actual direct-metered consumption." Environmental Research Communications 1, no. 11 (October 21, 2019): 111002. http://dx.doi.org/10.1088/2515-7620/ab4a99.
Full text
38
Ahmed, Maytham S., Hussein Shareef, Azah Mohamad, Jamal Abd Ali, and Ammar Hussein Mutlag. "Rule Base Home Energy Management System Considering Residential Demand Response Application." Applied Mechanics and Materials 785 (August 2015): 526–31. http://dx.doi.org/10.4028/www.scientific.net/amm.785.526.
Full textAbstract:
The increasing number of consumer and household appliances causes the rise in home energy use. Therefore, home energy management (HEM) technology is essential to manage and reduce electricity consumption. The objective of this paper is to present an intelligent algorithm for HEM using rule base technique to manage the power consumption with demand response (DR) feature. The scheduling algorithm considers household loads according to the comfort level, customer preference setting and priority of appliance that can be managed at a given time. The algorithm guarantees the total power consumption to be below the electrical demand limit. To exhibit the performance of the proposed HEM, a number of simulations are carried out including DR signal from the network operator. The results show that the algorithm can effectively respond to DR signal, comfort level, customer preference setting and priority of appliance. Furthermore, the algorithm is simple to implement and has flexibility to control the appliances.
39
Pothitou, Mary, Richard F. Hanna, and Konstantinos J. Chalvatzis. "ICT entertainment appliances’ impact on domestic electricity consumption." Renewable and Sustainable Energy Reviews 69 (March 2017): 843–53. http://dx.doi.org/10.1016/j.rser.2016.11.100.
Full text
40
Herring, H. "Electricity use in minor appliances in the UK." Energy 20, no. 7 (July 1995): 705–10. http://dx.doi.org/10.1016/0360-5442(95)00021-8.
Full text
41
Du, Shengli, Mingchao Li, Shuai Han, Jonathan Shi, and Heng Li. "Multi-Pattern Data Mining and Recognition of Primary Electric Appliances from Single Non-Intrusive Load Monitoring Data." Energies 12, no. 6 (March 14, 2019): 992. http://dx.doi.org/10.3390/en12060992.
Full textAbstract:
The electric power industry is an essential part of the energy industry as it strengthens the monitoring and control management of household electricity for the construction of an economic power system. In this paper, a non-intrusive affinity propagation (AP) clustering algorithm is improved according to the factor graph model and the belief propagation theory. The energy data of non-intrusive monitoring consists of the actual energy consumption data of each electronic appliance. The experimental results show that this improved algorithm identifies the basic and combined class of home appliances. According to the possibility of conversion between different classes, the combination of classes is broken down into different basic classes. This method provides the basis for power management companies to allocate electricity scientifically and rationally.
42
Balmer, M. "Household coal use in an urban township in South Africa." Journal of Energy in Southern Africa 18, no. 3 (August 1, 2007): 27–32. http://dx.doi.org/10.17159/2413-3051/2007/v18i3a3382.
Full textAbstract:
Coal is used as a domestic source of energy by low-income households in South Africa. Coal is an affordable fuel source and provides a dual utility – it warms the house and allows cooking to take place in the same appliance utilising only one fuel. Despite affordability and accessibility of the fuel, the use of coal results in extremely high levels of air pol-lution and concomitant respiratory diseases – an estimated $160 million per annum in South Africa. Access to electricity does not result in households switching away from coal since electricity and elec-trical appliances are regarded as unaffordable. This paper presents information collected during a base-line energy survey in an electrified urban township in South Africa, and outlines the way in which coal is used and purchased by poor households. An alternative fire lighting method, proven to reduce smoke and air pollution form coal fires has been demonstrated to households with promising results. An integrated approach, addressing energy efficient housing design, the supply of clean and efficient energy appliances together with the use of the alter-native fire lighting method, is recommended to address pollution from household coal use.
43
Shahi, Dinesh Kumar, Hom Bahadur Rijal, and Masanori Shukuya. "Study on Household Energy Usage Patterns in Urban and Rural Areas of Nepal." Journal of the Institute of Engineering 15, no. 3 (November 8, 2020): 402–10. http://dx.doi.org/10.3126/jie.v15i3.32761.
Full textAbstract:
In the last decades, the household’s energy demand has increased significantly in various countries including Nepal. In the case ofNepal, 94% of energy use is in the domestic sector. There is a possibility of a huge increase in electricity production, but we are stillsuffering from load shedding due to the high electricity demand. Electricity use is an important factor for the quality of life anddevelopment of a nation. There is not a sufficient number of researches done about electricity consumption in different climaticregions of Nepal which are analyzed by the income level of residents. This study gives descriptive information on the household’senergy uses patterns and investigates the electricity use rate, using electrical appliances in households. This study also identifies themajor source of energy use and awareness of energy use. The data were collected from 442 households in three regions in the winterseason of 2018. Kalikot is a rural area, Chitwan is a semi-urban, and Kathmandu is an urban area. We have collected electricity bills,family income, and family size, electricity using appliances, expenditure for energy and energy use for heating/cooling, cooking, andlighting. The electricity was used only for lighting purposes in the rural area, but other electrical appliances were used in semi-urbanand urban areas. The amount of electricity use has not affected by household income level in the rural area, but it has affected in semi-urban and urban areas. The level of education affects the use of the LED significantly. This study would be helpful to know theelectricity use patterns which is useful for energy saving and energy management of the rural and urban areas of Nepal.
44
Awais, Muhammad, Nadeem Javaid, Khursheed Aurangzeb, Syed Haider, Zahoor Khan, and Danish Mahmood. "Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids." Energies 11, no. 11 (November 12, 2018): 3125. http://dx.doi.org/10.3390/en11113125.
Full textAbstract:
Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme to accomplish the electricity demand of automated appliances. Recently, many Demand Side Management (DSM) schemes have been explored to alleviate Electricity Cost (EC) and Peak to Average Ratio (PAR). In this paper, energy consumption problem in a residential area is considered. To solve this problem, a heuristic based DSM technique is proposed to minimize EC and PAR with affordable user’s Waiting Time (WT). In heuristic techniques: Bacterial Foraging Optimization Algorithm (BFOA) and Flower Pollination Algorithm (FPA) are implemented.
45
Naz, Lubna, and Munir Ahmad. "What Inspires Electricity Crises at the Micro Level: Empirical Evidence from Electricity Consumption Pattern of Households from Karachi." Pakistan Development Review 52, no. 4I (December 1, 2013): 375–403. http://dx.doi.org/10.30541/v52i4ipp.375-403.
Full textAbstract:
With urbanisation1 and modernisation of the economy, the use of electrical appliances has increased manifold in Pakistan. Now, household shares in the total electricity use account for 46.5 percent. While other users have lower shares that are industrial 27.5 percent, agriculture 11.6 percent, commercial 7.5 percent and the government 6.2 percent only [Pakistan (2012-13)]. Overtime, the household electricity consumption has also increased because of the increase in electricity consumers2 and of village electrification.3 Other important reasons include the use of modern appliances including both locally made and smuggled and increase in the share of urban women in the labour force by 6.5 percent during 2007-08 and 2012- 13 [Pakistan (2012-13)]. These reasons are also responsible for enlarging electricity demand and supply gap over the years and have led to the electricity shortage to alarming proportions in March 2012. The electricity gap increased to 57,754 GW from 56,930 GW showing an increase of 1.4 percent from the corresponding period of the last year. The acute electricity shortage has caused long hours of the electricity load shedding in the country. The population living in urban areas bears the direct fall out of the electricity breakdown because of the modern lifestyle and sheer dependence on electricity [Pakistan (2012-13)].
46
Pano, Marijon. "Measurements of Standby Power Consumption of Domestic Appliances in Albania." European Journal of Interdisciplinary Studies 3, no. 1 (January 21, 2017): 71. http://dx.doi.org/10.26417/ejis.v3i1.71-74.
Full textAbstract:
Nearly all modern domestic appliances used in typical homes consume some energy when they are left on standby mode or even switched off. I investigated the variation in standby power consumption in five homes in Korça city. The typical standby energy loss for studied homes ranged from 8–115 W, with an average of 37 W. This corresponded to 3%-20% of the homes annual electricity use. This loss and the associated cost are not high enough to get noticed by the consumer. However, when such power losses of all domestic appliances are aggregated at the level of a country, the amount becomes significant and cannot be ignored. The appliances with the largest standby losses were coffee machines, televisions, set-top boxes and printers. They account for a significant proportion of the electricity consumption in more and more Albanian households. The wide variation in the standby power of appliances providing the same benefits indicates that producers are able to reduce standby losses without degrading performance. The standby power consumption of various domestic appliances was determined using an energy smart meter and data-logger connected with a computer. The purpose of this paper is to estimate how much power is wasted in a typical Albanian home due to household appliances being in the standby mode.
47
Pano, Marijon. "Measurements of Standby Power Consumption of Domestic Appliances in Albania." European Journal of Interdisciplinary Studies 3, no. 1 (January 21, 2017): 71. http://dx.doi.org/10.26417/ejis.v3i1.p71-74.
Full textAbstract:
Nearly all modern domestic appliances used in typical homes consume some energy when they are left on standby mode or even switched off. I investigated the variation in standby power consumption in five homes in Korça city. The typical standby energy loss for studied homes ranged from 8–115 W, with an average of 37 W. This corresponded to 3%-20% of the homes annual electricity use. This loss and the associated cost are not high enough to get noticed by the consumer. However, when such power losses of all domestic appliances are aggregated at the level of a country, the amount becomes significant and cannot be ignored. The appliances with the largest standby losses were coffee machines, televisions, set-top boxes and printers. They account for a significant proportion of the electricity consumption in more and more Albanian households. The wide variation in the standby power of appliances providing the same benefits indicates that producers are able to reduce standby losses without degrading performance. The standby power consumption of various domestic appliances was determined using an energy smart meter and data-logger connected with a computer. The purpose of this paper is to estimate how much power is wasted in a typical Albanian home due to household appliances being in the standby mode.
48
Pano, Marijon. "Measurements of Standby Power Consumption of Domestic Appliances in Albania." European Journal of Interdisciplinary Studies 7, no. 1 (January 21, 2017): 71. http://dx.doi.org/10.26417/ejis.v7i1.p71-74.
Full textAbstract:
Nearly all modern domestic appliances used in typical homes consume some energy when they are left on standby mode or even switched off. I investigated the variation in standby power consumption in five homes in Korça city. The typical standby energy loss for studied homes ranged from 8–115 W, with an average of 37 W. This corresponded to 3%-20% of the homes annual electricity use. This loss and the associated cost are not high enough to get noticed by the consumer. However, when such power losses of all domestic appliances are aggregated at the level of a country, the amount becomes significant and cannot be ignored. The appliances with the largest standby losses were coffee machines, televisions, set-top boxes and printers. They account for a significant proportion of the electricity consumption in more and more Albanian households. The wide variation in the standby power of appliances providing the same benefits indicates that producers are able to reduce standby losses without degrading performance. The standby power consumption of various domestic appliances was determined using an energy smart meter and data-logger connected with a computer. The purpose of this paper is to estimate how much power is wasted in a typical Albanian home due to household appliances being in the standby mode.
49
Hussain, Irshad, Majid Ullah, Ibrar Ullah, Asima Bibi, Muhammad Naeem, Madhusudan Singh, and Dhananjay Singh. "Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm." Electronics 9, no. 3 (February 28, 2020): 406. http://dx.doi.org/10.3390/electronics9030406.
Full textAbstract:
Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case.
50
Chellamani, Ganesh Kumar, M. Firdouse Ali Khan, and Premanand Venkatesh Chandramani. "Supervised electricity tariff prediction using random forest validated through user comfort and constraint for a home energy management scheme." Journal of Intelligent & Fuzzy Systems 40, no. 1 (January 4, 2021): 745–57. http://dx.doi.org/10.3233/jifs-200722.
Full textAbstract:
Day-ahead electricity tariff prediction is advantageous for both consumers and utilities. This article discusses the home energy management (HEM) scheme consisting of an electricity tariff predictor and appliance scheduler. The random forest (RF) technique predicts a short-term electricity tariff for the next 24 hours using the past three months of electricity tariff information. This predictor provides the tariff information to schedule the appliances at the most preferred time slot of a consumer with minimum electricity tariff, aiming high consumer comfort and low electricity bill for consumers. The proposed approach allows a user to be aware of their demand and their comfort. The proposed approach makes use of present-day (D) tariff and immediate previous 30 days (D-1, D-2, ... , D-30) of tariff information for training achieves minimum error values for next day electricity tariff prediction. The simulation results demonstrate the benefits of the RF approach for tariff prediction by comparing it with the support vector machine (SVM) and decision tree (DT) predicted tariffs against the actual tariff, provided by the utility day-ahead. The outcomes indicate that the RF produces the best results compared to SVM and DT predictions for performance metrics and end-user comfort.