scholarly journals Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset

Data ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Patrick Huber ◽  
Melvin Ott ◽  
Martin Friedli ◽  
Andreas Rumsch ◽  
Andrew Paice
Keyword(s):  
Energy Consumption ◽  
Power Flow ◽  
Electrical Power ◽  
Measurement Data ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Hot Water ◽  
Electricity Production ◽  
Load Monitoring ◽  
Tumble Dryer

Datasets with measurements of both solar electricity production and domestic electricity consumption separated into the major loads are interesting for research focussing on (i) local optimization of solar energy consumption and (ii) non-intrusive load monitoring. To this end, we publish the iHomeLab RAPT dataset consisting of electrical power traces from five houses in the greater Lucerne region in Switzerland spanning a period from 1.5 up to 3.5 years with a sampling frequency of five minutes. For each house, the electrical energy consumption of the aggregated household and specific appliances such as dishwasher, washing machine, tumble dryer, hot water boiler, or heating pump were metered. Additionally, the data includes electric production data from PV panels for all five houses, and battery power flow measurement data from two houses. Thermal metadata is also provided for the three houses with a heating pump.

scholarly journals Pengembangan Sistem Pemantauan Konsumsi Energi Rumah Tangga Berbasis Internet of Things (IoT)

2018 ◽  
Vol 6 (3) ◽  
pp. 357
Author(s):  
HARTONO BUDI SANTOSO ◽  
SAPTO PRAJOGO ◽  
SRI PARYANTO MURSID
Keyword(s):  
Energy Consumption ◽  
Measurement Accuracy ◽  
Measurement Data ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Average Error ◽  
Android Application ◽  
Wireless Technology ◽  
Power Meter ◽  
Communication Device

ABSTRAKPenghematan pada konsumsi listrik rumah tangga akan memberikan dampak pada konsumsi listrik nasional. Penelitian menunjukkan pemantauan terhadap konsumsi listrik rumah tangga akan memberikan dampak pada penghematan konsumsi listrik hingga 30%. Beberapa penelitian terkait pengembangan pemantauan terhadap konsumsi listrik rumah tangga masih menunjukkan hasil yang kurang memuaskan. Pada penelitian ini akan dikembangkan sistem pemantauan energi khususnya untuk beban rumah tangga berbasis teknologi IoT, sehingga dapat dilakukan pemantauan menggunaan energi listrik rumah tangga menggunakan aplikasi android di perangkat komunikasi telepon seluler (ponsel). Hasil pengujian akurasi pengukuran, dilakukan dengan membandingkan data pengukuran dengan alat ukur lain, menunjukkan pembacaan arus memiliki rata-rata error sebesar 0% sementara pembacaan tegangan memiliki rata-rata error sebesar 0,06%.Kata kunci: IoT, power meter, power monitor, konsumsi energi ABSTRACTThe savings on household electricity consumption will have an impact on national electricity consumption. Research shows that monitoring of household electricity consumption will have an impact on saving electricity consumption up to 30%. Direct monitoring starts from using cable to wireless technology. Some studies realated to developments of energy consumption monitoring still show unsatisfactory results.In this research will be developed energy monitoring system especially for household load based on IoT technology, so that can be monitored the use of household electrical energy using android application in communication device, handphone. The result of measurement measurement accuracy is done by comparing measurement data with other measuring instrument, indicating current reading has an average error of 0% while the voltage reading has an average error of 0.06%.Keywords: IoT, power meter, power Monitor, energy consumption

Measurement system and dataset for in-depth analysis of appliance energy consumption in industrial environment

2019 ◽  
Vol 86 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Matthias Kahl ◽  
Veronika Krause ◽  
Rudolph Hackenberg ◽  
Anwar Ul Haq ◽  
Anton Horn ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Sampling Rate ◽  
Measurement Data ◽  
Electrical Energy ◽  
Amplitude Resolution ◽  
Depth Analysis ◽  
Machine Learning Approach ◽  
Load Monitoring ◽  
Design Requirements ◽  
Industrial Environments

AbstractTo support a rational and efficient use of electrical energy in residential and industrial environments, Non-Intrusive Load Monitoring (NILM) provides several techniques to identify state and power consumption profiles of connected appliances. Design requirements for such systems include a low hardware and installations costs for residential, reliability and high-availability for industrial purposes, while keeping invasive interventions into the electrical infrastructure to a minimum. This work introduces a reference hardware setup that allows an in depth analysis of electrical energy consumption in industrial environments. To identify appliances and their consumption profile, appropriate identification algorithms are developed by the NILM community. To enable an evaluation of these algorithms on industrial appliances, we introduce the Laboratory-measured IndustriaL Appliance Characteristics (LILAC) dataset: 1302 measurements from one, two, and three concurrently running appliances of 15 appliance types, measured with the introduced testbed. To allow in-depth appliance consumption analysis, measurements were carried out with a sampling rate of 50 kHz and 16-bit amplitude resolution for voltage and current signals. We show in experiments that signal signatures, contained in the measurement data, allows one to distinguish the single measured electrical appliances with a baseline machine learning approach of nearly 100 % accuracy.

scholarly journals Smart Energy Meter For Iot Applications

2019 ◽  
Vol 8 (11) ◽  
pp. 2708-2712 ◽  
Keyword(s):  
Energy Consumption ◽  
Electrical Power ◽  
Measurement Data ◽  
Electrical Energy ◽  
Energy Usage ◽  
Energy Meter ◽  
Memory Card ◽  
Short Period ◽  
Instant Power ◽  
Domestic Appliance

as domestic electrical energy consumption keeps increasing, consumers become more aware of energy usage and efficiency because of economic and environmental reasons. The energy meter described in this paper is aimed at household smart metering for better energy management. The meter system uses a single microcontroller to acquire mains voltage and current waveforms and calculate power parameters: RMS voltage and current, instant power, power factor and energy. These parameters are stored locally on memory card for long period standalone recording, or transmitted in real time using an IoT Long Range radio for instant readings or short period monitoring. Measurement data of electrical power usage of a typical family household and energy consumption is presented where domestic appliance patterns are identified over an operating period. These patterns enable the estimation of energy usage distribution among appliances.

scholarly journals AUDIT ENERGI PADA SEBUAH HOTEL

2012 ◽  
Vol 16 (3) ◽  
pp. 131
Author(s):  
Didik Ariwibowo
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Savings ◽  
Electric Energy ◽  
Electrical Energy ◽  
Hot Water ◽  
Electrical Energy Consumption ◽  
Energy Audit ◽  
Electric Energy Consumption ◽  
Pumping System

Didik Ariwibowo, in this paper explain that energy audit activities conducted through several phases, namely: the initial audit, detailed audit, analysis of energy savings opportunities, and the proposed energy savings. Total energy consumed consists of electrical energy, fuel, and materials in this case is water. Electrical energy consumption data obtained from payment of electricity accounts for a year while consumption of fuel and water obtained from the payment of material procurement. From the calculation data, IKE hotels accounted for 420.867 kWh/m2.tahun, while the IKE standards for the hotel is 300 kWh/m2.tahun. Thus, IKE hotel included categorized wasteful in energy usage. The largest energy consumption on electric energy consumption. Largest electric energy consumption is on the air conditioning (AC-air conditioning) that is equal to 71.3%, and lighting and electrical equipment at 27.28%, and hot water supply system by 4.44%. Electrical energy consumption in AC looks very big. Ministry of Energy and Mineral Resources of the statutes, the profile of energy use by air conditioning at the hotel by 48.5%. With these considerations in the AC target for audit detail as the next phase of activity. The results of a detailed audit analysis to find an air conditioning system energy savings opportunities in pumping systems. Recommendations on these savings is the integration of automation on the pumping system and fan coil units (FCU). The principle of energy conservation in the pumping system is by installing variable speed drives (VSD) pump drive motor to adjust speed according to load on the FCU. Load variations FCU provide input on the VSD pumps to match. Adaptation is predicted pump can save electricity consumption up to 65.7%. Keywords: energy audit, IKE, AC

EXPERIMENTAL STUDY OF BIOELECTRICITY-MICROBIAL FUEL CELL FOR ELECTRICITY GENERATION: PERFORMANCE CHARACTERIZATION AND CAPACITY IMPROVEMENT

2017 ◽  
Vol 79 (5-2) ◽  
Author(s):  
Zul Hasrizal Bohari ◽  
Nur Asyhikin Azhari ◽  
Nuraina Nasuha Ab Rahman ◽  
Mohamad Faizal Baharom ◽  
Mohd Hafiz Jali ◽  
...  
Keyword(s):  
Organic Matter ◽  
Fuel Cell ◽  
Microbial Fuel Cell ◽  
Electrical Power ◽  
Electrical Energy ◽  
Sewage Water ◽  
Electricity Production ◽  
Sample Type ◽  
Series Of Experiments ◽  
The Right

Energy trending lately shown the need of new possible renewable energy. This paper studies about the capability and capacity generating of electricity by using Bio-electricity-Microbial Fuel Cell (Bio-MFC). Bio-MFC is the device that converts chemical energy to electrical energy by using microbes that exist in the sewage water. The energy contained in organic matter can be converted into useful electrical power. MFC can be operated by microbes that transfer electrons from anode to cathode for generating electricity. There are two major goals in this study. The first goal is to determine the performance characteristics of MFCs in this application. Specifically we investigate the relationship between the percentages of organic matter in a sample results in higher electricity production of MFCs power by that sample. As a result, the sewage (wastewater) chosen in the second series experiment because the sewage (wastewater) also produced the highest percentage of organic matter which is around 10%. Due to these, the higher percentage of organic matter corresponds to higher electricity production. The second goal is to determine the condition under which MFC work most efficiently to generating electricity. After get the best result of the combination for the electrode, which is combination of zinc and copper (900mV),the third series of experiments was coducted, that show the independent variable was in the ambient temperature. The reasons of these observations will be explained throughout the paper. The study proved that the electricity production of MFC can be increased by selecting the right condition of sample type, temperature and type of electrode. 

scholarly journals ANALISIS POTENSI PENGHEMATAN PADA PLTU UNIT 5 DENGAN AUDIT ENERGI PADA MOTOR PEMAKAIAN SENDIRI DI PT PJB MUARA KARANG

2018 ◽  
Vol 9 (1) ◽  
pp. 1-7
Author(s):  
Redaksi Tim Jurnal
Keyword(s):  
Energy Consumption ◽  
Power Plant ◽  
Performance Test ◽  
Energy Savings ◽  
Quality Measurement ◽  
Electrical Energy ◽  
Test Method ◽  
Electricity Production ◽  
Voltage Source ◽  
Personal Use

PT PJB Muara Karang power plant is an industry with a large electrical energy consumption for auxiliary power. In ISO50001 itensitas Energy Consumption (IKE) is a great need to audit energy consumption. In the contract the company's performance also set a percentage of personal use should not exceed 6% of the electricity production. Currently Posentase usage of own consumption at power plant unit 5 is greater than the power plant unit 4. It is necessary for an energy audit for the usage of its own in order to decrease the percentage of personal use in the power plant 5 0.5% of the current conditions and find energy savings opportunities in the power plant unit 5.To analyze this problem using energy audits, analyzes the performance test method using "gate cycle" and testing the quality of the voltage source by using the power quality measurement analysis. Having found the equipment with the largest energy comsumtion fish bone tools used to find the main cause of this disorder.

scholarly journals Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
Jihyun Kim ◽  
Thi-Thu-Huong Le ◽  
Howon Kim
Keyword(s):  
Deep Learning ◽  
Power Consumption ◽  
Distribution System ◽  
Short Term Memory ◽  
Electrical Power ◽  
Electricity Consumption ◽  
Classification Performance ◽  
Robust Solution ◽  
Proposed Model ◽  
Load Monitoring

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.

THE POTENTIAL ECONOMIC ANALYSIS OF SOLAR HOME SYSTEM WITH SWITCHING METHOD ON HOUSEHOLD ELECTRICITY SCALE

2020 ◽  
Vol 9 (2) ◽  
pp. 125-134
Author(s):  
Kurnia Paranita Kartika ◽  
Riska Dhenabayu
Keyword(s):  
Electrical Power ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Point Of View ◽  
Solar Panels ◽  
Economic Point ◽  
Household Appliances ◽  
Cost Of Energy ◽  
Solar Home System ◽  
Switching Method

This study aims to design a Solar Home System with an Arduino-based Smart Switching system so that the use of electrical energy generated by solar panels can be adjusted without adding power from other electricity sources, such as PLN. Calculation of Leveled Cost of Energy (LCOE) is used as the basis for the switching process that will be carried out to regulate the use of household appliances that are routinely used, regulate electricity consumption automatically, minimize usage, and calculate the effectiveness of electric power usage. The way SHS works is to collect electrical energy from sunlight, then convert DC voltage to AC so that it can be used to run household electronic equipment. To accommodate the adequacy of electrical power, an automatic adjustment is made for household appliances that are routinely used, namely house lights, which includes setting the lights on and off and the number of lights that can be activated. The advantage of this research is that the SHS system is integrated with the automatic setting of the lights installed in the house so that the number of lights on will adjust the availability of electrical energy in the battery. In addition, with the LCOE method, the level of usage can be calculated so that users can save electricity. From the results of usage testing, it is found that the application of this switching technology provides benefits for users because it is no longer dependent on PLN supply. From an economic point of view, based on the calculation of Leveled Cost of Energy (LCOE), there is a kWh value savings of Rp. 77, - for each kWh price or about 4.53% compared to purchasing electricity with prepaid mode.

scholarly journals Nonintrusive Appliance Load Monitoring: An Overview, Laboratory Test Results and Research Directions

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3621 ◽  
Author(s):  
Augustyn Wójcik ◽  
Robert Łukaszewski ◽  
Ryszard Kowalik ◽  
Wiesław Winiecki
Keyword(s):  
Smart Home ◽  
State Of The Art ◽  
Measurement Data ◽  
Electricity Consumption ◽  
Identification Accuracy ◽  
Test Results ◽  
Research Directions ◽  
Laboratory Test Results ◽  
New Directions ◽  
Load Monitoring

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.

scholarly journals Comparative Analysis of Two Urban Microclimates: Energy Consumption and Greenhouse Gas Emissions

2019 ◽  
Vol 11 (7) ◽  
pp. 2045 ◽  
Author(s):  
Néstor Santillán-Soto ◽  
O. García-Cueto ◽  
Alejandro Lambert-Arista ◽  
Sara Ojeda-Benítez ◽  
Samantha Cruz-Sotelo
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Scientific Evidence ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Air Conditioner ◽  
Comparative Performance ◽  
Urban Complex ◽  
Arid Desert ◽  
Urban Microclimates

This paper presents a hypothetical and comparative performance of a 5 ton air conditioner (AC) operating in two zones in different urban microclimates for 25 days. One site represents a type of homogeneous planned urbanism and the other is a traditional heterogeneous zone. Air temperature data was collected and then processed using a linear regression model included in the operating manual of the AC in order to obtain their energy consumption. Results indicate that for an area with 500 homes, a traditional urban complex requires 12,350 kWh of electrical energy more than a planned zone (1.89%). This extra energy amounts up to $1180 and adds 9191 kg of CO2 to the atmosphere. The increased energy consumption has implications that increase the cost and environmental aspects of two urban microclimates, so that urbanization without planning is less friendly to the environment. In this sense, this study highlights the effects of urban microclimates on domestic electricity consumption from air conditioning. In addition, for a city with an arid desert climate, the variation in electricity consumption is associated with changes in the urban mosaic. The results found represent scientific evidence that can be used as a reference to establish public policies that could be incorporated into the local construction regulations, oriented to reduce the energy consumption associated with the use of air conditioning equipment.

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