ELECTRICITY CONSUMPTION PATTERN DISAGGREGATION USING NON-INTRUSIVE APPLIANCE LOAD MONITORING METHOD

2016 ◽  
Vol 78 (5-7) ◽  
Author(s):  
Nur Farahin Asa @ Esa ◽  
Md Pauzi Abdullah ◽  
Mohammad Yusri Hassan ◽  
Faridah Hussin
Keyword(s):  
Electricity Consumption ◽  
Consumption Pattern ◽  
Time Interval ◽  
Time Sampling ◽  
Monitoring Method ◽  
Fluorescent Lamps ◽  
Energy Meter ◽  
Load Monitoring ◽  
Air Conditioning Systems ◽  
The Impact

In practice, a standard energy meter can only capture the overall electricity consumption and estimating electricity consumption pattern of various appliances from the overall consumption pattern is complicated. Therefore, the Non-Intrusive Appliance Load Monitoring (NIALM) technique can be applied to trace electricity consumption from each appliance in a monitored building. However, the method requires a detailed, second-by-second power consumption data which is commonly not available without the use of high specification energy meter. Hence, this paper analyzes the impact of different time sampling data in estimating the energy consumption pattern of various appliances through NIALM method.  This is so that consumers will have an overview of time sampling data which is required in order to apply the NIALM technique. As for the analysis, air-conditioning systems and fluorescent lamps were used in the experimental setup. One minute sample rate was the minimum time interval required by NIALM carried out in this analysis. Through the study presented in this paper, it can be established that higher time sampling led to uncertain appliance detection and low accuracy.

scholarly journals A Data-Driven Clustering Analysis for the Impact of COVID-19 on the Electricity Consumption Pattern of Zhejiang Province, China

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8187
Author(s):  
Zhiang Zhang ◽  
Ali Cheshmehzangi ◽  
Saeid Pourroostaei Ardakani
Keyword(s):  
Electricity Consumption ◽  
Zhejiang Province ◽  
Data Driven ◽  
Time Shift ◽  
Consumption Pattern ◽  
Short Term ◽  
Consumption Data ◽  
Multiple Regions ◽  
The Impact

The COVID-19 pandemic has impacted electricity consumption patterns and such an impact cannot be analyzed by simple data analytics. In China, specifically, city lock-down policies lasted for only a few weeks and the spread of COVID-19 was quickly under control. This has made it challenging to analyze the hidden impact of COVID-19 on electricity consumption. This paper targets the electricity consumption of a group of regions in China and proposes a new clustering-based method to quantitatively investigate the impact of COVID-19 on the industrial-driven electricity consumption pattern. This method performs K-means clustering on time-series electricity consumption data of multiple regions and uses quantitative metrics, including clustering evaluation metrics and dynamic time warping, to quantify the impact and pattern changes. The proposed method is applied to the two-year daily electricity consumption data of 87 regions of Zhejiang province, China, and quantitively confirms COVID-19 has changed the electricity consumption pattern of Zhejiang in both the short-term and long-term. The time evolution of the pattern change is also revealed by the method, so the impact start and end time can be inferred. Results also show the short-term impact of COVID-19 is similar across different regions, while the long-term impact is not. In some regions, the pandemic only caused a time-shift in electricity consumption; but in others, the electricity consumption pattern has been permanently changed. The data-driven analysis of this paper can be the first step to fully interpret the COVID-19 impact by considering economic and social parameters in future studies.

Energy Efficiency and Electricity Reliability

2020 ◽  
pp. 1-78 ◽  
Author(s):  
Eliana Carranza ◽  
Robyn Meeks
Keyword(s):  
Energy Efficiency ◽  
Electricity Consumption ◽  
Kyrgyz Republic ◽  
Electrical Systems ◽  
Fluorescent Lamps ◽  
Compact Fluorescent Lamps ◽  
Reduce Electricity Consumption ◽  
Electricity Reliability ◽  
The Impact

Overloaded electrical systems are a major source of unreliable power. Using a randomized saturation design, we estimate the impact of compact fluorescent lamps (CFLs) on electricity reliability and household electricity consumption in the Kyrgyz Republic. Greater saturation of CFLs within a transformer leads to fewer outages, a technological externality benefitting all households, regardless of individual adoption. Spillovers in CFL adoption further reduce electricity consumption, contributing to increased reliability within a transformer. CFLs' impacts on household electricity consumption vary according to the effects on reliability. Receiving CFLs significantly reduces electricity consumption, but increased reliability permits greater consumption of electricity services.

scholarly journals Impact of nonintrusive load monitoring on CO2 emissions in Malaysia

2021 ◽  
Vol 10 (4) ◽  
pp. 1803-1810
Author(s):  
Keh-Kim Kee ◽  
Yun Seng Lim ◽  
Jianhui Wong ◽  
Kein Huat Chua
Keyword(s):  
Energy Efficiency ◽  
Co2 Emissions ◽  
User Interfaces ◽  
Open Data ◽  
Electricity Consumption ◽  
Supporting Evidence ◽  
Carbon Reduction ◽  
Co2 Intensity ◽  
Load Monitoring ◽  
The Impact

Nonintrusive load monitoring (NILM) based energy efficiency can conserve electricity by creating awareness with the behaviour change and shrinking CO2 emissions to the environment. However, the lack of effective models and strategies is problematic for policymakers to forecast quantitatively CO2 emissions. This paper aims to study the impact of NILM on CO2 emissions in Malaysia. Firstly, the predictive models were established based on Malaysia open data from 1996 to 2018. After that, scenario simulations were conducted to predict CO2 emissions and NILM impact on environmental degradation in 2019-2030. The results revealed that a 12% reduction in electricity consumption due to NILM could contribute to a 10.2% shrinkage of the total CO2 emissions. The result also statistically confirmed Malaysia to achieve a 45% reduction of CO2 intensity in 2030. With NILM, the carbon reduction can be further enhanced to 60.2%. The outcomes provide valuable references and supporting evidence for policymakers in planning effective carbon emission control policies and energy efficiency measures. The work can be extended by developing a decision support system and user interfaces access via the cloud.

Application of vacuum belt press filters for cane mud filtration and performance comparison with rotary filters

2014 ◽  
pp. 298-301 ◽  
Author(s):  
Arnaud Petit
Keyword(s):  
Electricity Consumption ◽  
Performance Comparison ◽  
Operating Conditions ◽  
Vacuum Filter ◽  
Sugar Mill ◽  
Belt Press ◽  
Vacuum Belt ◽  
And Performance ◽  
Mud Filtration ◽  
The Impact

Bois-Rouge factory, an 8000 t/d cane Reunionese sugarcane mill, has fully equipped its filtration station with vacuum belt press filters since 2010, the first one being installed in 2009. The present study deals with this 3-year experience and discusses operating conditions, electricity consumption, performance and optimisation. The comparison with the more classical rotary drum vacuum filter station of Le Gol sugar mill highlights advantages of vacuum belt press filters: high filtration efficiency, low filter cake mass and sucrose content, low total solids content in filtrate and low power consumption. However, this technology needs a mud conditioning step and requires a large amount of water to improve mud quality, mixing of flocculant and washing of filter belts. The impact on the energy balance of the sugar mill is significant. At Bois-Rouge mill, studies are underway to reduce the water consumption by recycling low d.s. filtrate and by dry cleaning the filter belts.

scholarly journals Time-to-Treatment in Oral Cancer: Causes and Implications for Survival

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1321
Author(s):  
Constanza Saka-Herrán ◽  
Enric Jané-Salas ◽  
Antoni Mari-Roig ◽  
Albert Estrugo-Devesa ◽  
José López-López
Keyword(s):  
Oral Cancer ◽  
Previous Treatment ◽  
Diagnostic Procedures ◽  
Original Data ◽  
Primary Treatment ◽  
Medical Attention ◽  
Time Interval ◽  
Pre Treatment ◽  
The Impact ◽  
Lack Of Knowledge

The purpose of this review was to identify and describe the causes that influence the time-intervals in the pathway of diagnosis and treatment of oral cancer and to assess its impact on prognosis and survival. The review was structured according to the recommendations of the Aarhus statement, considering original data from individual studies and systematic reviews that reported outcomes related to the patient, diagnostic and pre-treatment intervals. The patient interval is the major contributor to the total time-interval. Unawareness of signs and/or symptoms, denial and lack of knowledge about oral cancer are the major contributors to the process of seeking medical attention. The diagnostic interval is influenced by tumor factors, delays in referral due to higher number of consultations and previous treatment with different medicines or dental procedures and by professional factors such as experience and lack of knowledge related to the disease and diagnostic procedures. Patients with advanced stage disease, primary treatment with radiotherapy, treatment at an academic facility and transitions in care are associated with prolonged pre-treatment intervals. An emerging body of evidence supports the impact of prolonged pre-treatment and treatment intervals with poorer survival from oral cancer.

scholarly journals Impact of Passive Energy Efficiency Measures on Cooling Energy Demand in an Architectural Campus Building in Karachi, Pakistan

2021 ◽  
Vol 13 (13) ◽  
pp. 7251
Author(s):  
Mushk Bughio ◽  
Muhammad Shoaib Khan ◽  
Waqas Ahmed Mahar ◽  
Thorsten Schuetze
Keyword(s):  
Energy Efficiency ◽  
Energy Demand ◽  
Electricity Consumption ◽  
Information Modeling ◽  
Base Case ◽  
Energy Efficiency Measures ◽  
Efficiency Measures ◽  
The Impact ◽  
Cooling Energy Demand ◽  
Campus Building

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.

scholarly journals The Impact of Time Interval between Hepatic Resection and Liver Transplantation on Clinical Outcome in Patients with Hepatocellular Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2398
Author(s):  
Matteo Serenari ◽  
Enrico Prosperi ◽  
Marc-Antoine Allard ◽  
Michele Paterno ◽  
Nicolas Golse ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Hepatic Resection ◽  
Primary Outcome ◽  
Polynomial Regression ◽  
Secondary Outcome ◽  
Time Interval ◽  
Comprehensive Complication Index ◽  
Fractional Polynomial ◽  
The Impact

Hepatic resection (HR) for hepatocellular carcinoma (HCC) may require secondary liver transplantation (SLT). However, a previous HR is supposed to worsen post-SLT outcomes. Data of patients treated by SLT between 2000 and 2018 at two tertiary referral centers were analyzed. The primary outcome of the study was to analyze the impact of HR on post-LT complications. A Comprehensive Complication Index ≥ 29.6 was chosen as cutoff. The secondary outcome was HCC-related death by means of competing-risk regression analysis. In the study period, 140 patients were included. Patients were transplanted in a median of 23 months after HR (IQR 14–41). Among all the features analyzed regarding the prior HR, only time interval between HR and SLT (time HR-SLT) was an independent predictor of severe complications after LT (OR = 0.98, p < 0.001). According to fractional polynomial regression, the probability of severe complications increased up to 15 months after HR (43%), then slowly decreased over time (OR = 0.88, p < 0.001). There was no significant association between HCC-related death and time HR-SLT at the multivariable competing risks regression model (SHR, 1.06; 95% CI: 0.69–1.62, p = 0.796). This study showed that time HR-SLT was key in predicting complications after LT, without affecting HCC-related death.

scholarly journals Effect of the Assimilation Frequency of Radar Reflectivity on Rain Storm Prediction by Using WRF-3DVAR

2021 ◽  
Vol 13 (11) ◽  
pp. 2103
Author(s):  
Yuchen Liu ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Wei Wang
Keyword(s):  
Data Assimilation ◽  
Northern China ◽  
Horizontal Resolution ◽  
Radar Reflectivity ◽  
Small Scale ◽  
Time Interval ◽  
Outer Domain ◽  
Storm Prediction ◽  
The Impact ◽  
Assimilation Time

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in the three-dimensional variational data assimilation (3DVAR) system of the Weather Research Forecast (WRF) model on rain storm prediction in Daqinghe basin of northern China. The aim of this study was to explore the potential effects of data assimilation frequency and to evaluate the outputs from different domain resolutions in improving the meso-scale NWP rainfall products. In this study, four numerical experiments (no assimilation, 1 and 6 h assimilation time interval with DWR and GTS at 1 km horizontal resolution, 6 h assimilation time interval with radar reflectivity, and GTS data at 3 km horizontal resolution) are carried out to evaluate the impact of data assimilation on prediction of convective rain storms. The results show that the assimilation of radar reflectivity and GTS data collectively enhanced the performance of the WRF-3DVAR system over the Beijing-Tianjin-Hebei region of northern China. It is indicated by the experimental results that the rapid update assimilation has a positive impact on the prediction of the location, tendency, and development of rain storms associated with the study area. In order to explore the influence of data assimilation in the outer domain on the output of the inner domain, the rainfall outputs of 3 and 1 km resolution are compared. The results show that the data assimilation in the outer domain has a positive effect on the output of the inner domain. Since the 3DVAR system is able to analyze certain small-scale and convective-scale features through the incorporation of radar observations, hourly assimilation time interval does not always significantly improve precipitation forecasts because of the inaccurate radar reflectivity observations. Therefore, before data assimilation, the validity of assimilation data should be judged as far as possible in advance, which can not only improve the prediction accuracy, but also improve the assimilation efficiency.

scholarly journals Financing Growth through Remittances and Foreign Direct Investment: Evidences from Balkan Countries

2021 ◽  
Vol 14 (3) ◽  
pp. 117
Author(s):  
Esmeralda Jushi ◽  
Eglantina Hysa ◽  
Arjona Cela ◽  
Mirela Panait ◽  
Marian Catalin Voica
Keyword(s):  
Developing Economies ◽  
Central Banks ◽  
Sustainable Growth ◽  
Time Interval ◽  
Foreign Direct Investments ◽  
Factors Affecting ◽  
Balkan Countries ◽  
To Come ◽  
Sustainable Economic Growth ◽  
The Impact

The ultimate goal of central banks, worldwide, is to promote the foundations for sustainable economic growth. In the case of developing economies, in particular, such objective requires time, huge efforts, attention, and plenty of resources in order to be accomplished to the fullest degree. This paper thoroughly investigates key factors affecting Balkan countries’ economic development (as measured by gross domestic product (GDP) growth), focusing especially on the impact of remittances. The analysis was done over an 18-year time interval (2000–2017) and builds on 144 observations. The data figures were retrieved from the World Bank database while two dummies were created to test the impact of the last financial crisis (2008–2012). Econometric tools were employed to carry out a broad analysis on the interdependencies that exist and, in particular, to determine the role of remittance income on growth. The vector auto regressive model was estimated using EViews software, and was used to come up with relevant insights. Empirical findings suggest the following: population growth, remittances, and labor force participation are insignificant factors for sustainable growth. On the other hand, previous levels of GDP, trade, and foreign direct investments (FDIs) appear to be relevant for the predictor. This research provides up-to-date conclusions, which can be considered during the decision-making process of central banks, as well as by government policymakers.

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