scholarly journals Time-Pattern Profiling from Smart Meter Data to Detect Outliers in Energy Consumption

IoT ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 92-108
Author(s):  
William Hurst ◽  
Casimiro A. Curbelo Montañez ◽  
Nathan Shone
Keyword(s):  
Energy Consumption ◽  
Spatial Clustering ◽  
Smart Meter ◽  
Energy Usage ◽  
Smart Meters ◽  
Time Pattern ◽  
Behavioural Patterns ◽  
Utility Companies ◽  
The Uk ◽  
The Internet Of Things

Smart meters have become a core part of the Internet of Things, and its sensory network is increasing globally. For example, in the UK there are over 15 million smart meters operating across homes and businesses. One of the main advantages of the smart meter installation is the link to a reduction in carbon emissions. Research shows that, when provided with accurate and real-time energy usage readings, consumers are more likely to turn off unneeded appliances and change other behavioural patterns around the home (e.g., lighting, thermostat adjustments). In addition, the smart meter rollout results in a lessening in the number of vehicle callouts for the collection of consumption readings from analogue meters and a general promotion of renewable sources of energy supply. Capturing and mining the data from this fully maintained (and highly accurate) sensing network, provides a wealth of information for utility companies and data scientists to promote applications that can further support a reduction in energy usage. This research focuses on modelling trends in domestic energy consumption using density-based classifiers. The technique estimates the volume of outliers (e.g., high periods of anomalous energy consumption) within a social class grouping. To achieve this, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Ordering Points to Identify the Clustering Structure (OPTICS) and Local Outlier Factor (LOF) demonstrate the detection of unusual energy consumption within naturally occurring groups with similar characteristics. Using DBSCAN and OPTICS, 53 and 208 outliers were detected respectively; with 218 using LOF, on a dataset comprised of 1,058,534 readings from 1026 homes.

scholarly journals Wireless Home Energy Meter Manager using Android: A Preliminary study

2019 ◽  
Vol 18 (3-2) ◽  
pp. 32-36
Author(s):  
Sh. Nurul Hidayah Wan Julihi ◽  
Ili Najaa Aimi Mohd Nordin ◽  
Muhammad Rusydi Muhammad Razif ◽  
Amar Faiz Zainal Abidin
Keyword(s):  
Energy Consumption ◽  
Personal Information ◽  
Current Sensor ◽  
Smart Meter ◽  
Smart Meters ◽  
Long Distance ◽  
Energy Meter ◽  
Utility Companies ◽  
Preliminary Study ◽  
To Receive

Manual home energy meter reading and billing had caused inconvenience to the utility companies due to lack of manpower to read the energy meter at each household especially in the remote area, explains the increasing number of smart meter reader in the current market. Most of the smart meters in the market do not offer safety of privacy of consumers’ personal information since the data of electricity usage is being transferred digitally to the utility companies for more accurate bills calculation. Plus, the smart meter system is also a bit pricey to be installed in the rural area. Therefore, a private system that able to read energy consumption from a DC load and calculate its bill according to the tariff is proposed. Value of current is being obtained by using ACS712 current sensor. Hall circuit in the current sensor will converts magnetic field into a proportional voltage. The proposed system allows energy meter monitoring from an Android-based smartphone by displaying the real-time energy consumption and bill on Blynk application. An interface of Blynk is developed and connected to WiFi module, ESP8266 for visualizing the energy consumption of the DC load. In conclusion, the Energy Meter transmitter part able to read, calculate and transmit value of energy consumption and current bills to the Blynk application and Blynk application able to receive and show all the data transmitted at the present time. This system will be further improved for long-distance monitoring of electrical appliances used at home.

scholarly journals Smart Meter Awareness in Italy, Ancona

2021 ◽  
pp. 47-66
Author(s):  
Vasileios Ntouros ◽  
Nikolaos Kampelis ◽  
Martina Senzacqua ◽  
Theoni Karlessi ◽  
Margarita-Niki Assimakopoulos ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Smart Grid ◽  
Energy Use ◽  
Second Generation ◽  
Energy Savings ◽  
General View ◽  
Smart Meter ◽  
Accurate Data ◽  
Energy Usage ◽  
Smart Meters

AbstractSmart meters, one of the crucial enablers of the smart-grid concept and cornerstones in smart planning for cities, offer the opportunity for consumers to address their energy consumption effectively through timely and accurate data on their energy usage. However, previous studies have shown that smart meters may not lead to the desired energy savings unless actively used by households. To this end, the research presented in this paper investigates the penetration of smart meters at community level and explores how such a metering system can help people to understand and manage their energy use better. It examines the awareness about smart meters, looks into their presence in current accommodation and focuses on the views people have about smart meters. For this purpose, a questionnaire was prepared and distributed to a group of individuals residing in the wide area of Ancona province in Italy. Although the deployment of modern second-generation smart meters started in 2017 replacing the outdated smart meters massively installed in the 2000s, the results show low-to-moderate levels of awareness of modern smart meters among the respondents and a low presence of second-generation metering devices in their current accommodation. However, the general view expressed by the participants about smart meters is positive. The findings demonstrate that respondents are in need not only of a gauge that measures energy consumption but also of a tool that assists them to manage effectively their energy use.

scholarly journals Mobile Application for Electric Power Monitoring on Energy Consumptions at a Campus University

2018 ◽  
Vol 11 (2) ◽  
pp. 637
Author(s):  
Murizah Kassim ◽  
Maisarah Abdul Rahman ◽  
Cik Ku Haroswati Che Ku Yahya ◽  
Azlina Idris
Keyword(s):  
Energy Consumption ◽  
Electric Power ◽  
Mobile Applications ◽  
Working Hours ◽  
Mobile App ◽  
Smart Meter ◽  
University Campus ◽  
Smart Meters ◽  
Power Monitoring ◽  
Energy Consumptions

This paper presents a research on electric power monitoring prototype mobile applications development on energy consumptions in a university campus. Electric power energy consumptions always are the issue of monitoring usage especially in a broad environment. University campus faces high used of electric power, thus crucial analysis on cause of the usage is needed. This research aims to analyses electric power usage in a university campus where implemented of few smart meters is installed to monitor five main buildings in a campus university. A Monitoring system is established in collecting electric power usage from the smart meters. Data from the smart meter then is analyzed based on energy consume on 5 buildings. Results presents graph on the power energy consume and presented on mobile applications using Live Code coding. The methodology involved the setup of the smart meters, monitoring and data collected from main smart meters, analyzed electrical consumptions for 5 buildings and mobile system development to monitor. A Live Code mobile app is designed then data collected from smart meter using ION software is published in graphs. Results presents the energy consumed for 5 building during day and night. Details on maximum and minimum energy consumption presented that show load of energy used in the campus. Result present Tower 1 saved most eenergy at night which is 65% compared to block 3 which is 8% saved energy although block 3 presents the lowest energy consumption in the working hours and non-working hours. This project is significant that can help campus facility to monitor electric power used thus able to control possible results in future implementations.

Smart Metering for Applications

2014 ◽  
Vol 960-961 ◽  
pp. 823-827
Author(s):  
Ying Pan ◽  
Bo Jiang
Keyword(s):  
Smart Grid ◽  
Electrical Energy ◽  
Smart Meter ◽  
Smart Metering ◽  
Power Network ◽  
Energy Usage ◽  
Smart Meters ◽  
Additional Information ◽  
Energy Efficiency Improvement ◽  
Energy Meter

As an important part of Smart Grid, smart metering attracts more and more attention all over the world. It is the way for energy consumer to sense the benefit of smart grid directly. Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. This paper discusses various applications and technologies that can be integrated with a smart meter. Smart meters can be used not only from the supply side monitoring but also for the demand side management as well. It plays an important role to monitor the performance and the energy usage of the grid loadings and power quality. In addition, This paper gives a comprehensive view on the benefit of smart metering in power network such as energy efficiency improvement.

Blackout Avoidance and Energy Saving Services with Alert Aggregation

2012 ◽  
Vol 3 (4) ◽  
pp. 40-56
Author(s):  
Erica Fong ◽  
Dickson K.W. Chiu ◽  
Haiyang Hu ◽  
Yi Zhuang ◽  
Hua Hu
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Real Time ◽  
Mobile Devices ◽  
Critical Energy ◽  
The Internet ◽  
Monitor System ◽  
Energy Usage ◽  
Huge Number ◽  
Smart Meters

Peak electricity demands from huge number of households in a mega-city would cause contention, leading to potential blackout. This paper proposes bi-directional collaboration via a Smart Energy Monitor System (SEMS) between consumers and energy suppliers, exchanging real-time energy usage data with smart meters over the Internet and mobile devices for well-informed decisions and even predictions. The authors further propose the use of an Alert Management System (AMS) to monitor and aggregate critical energy consumption events for this purpose.

scholarly journals A Decade On, How Has the Visibility of Energy Changed? Energy Feedback Perceptions from UK Focus Groups

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2566 ◽  
Author(s):  
David Fredericks ◽  
Zhong Fan ◽  
Sandra Woolley ◽  
Ed de Quincey ◽  
Mike Streeton
Keyword(s):  
Energy Consumption ◽  
Focus Groups ◽  
Energy Use ◽  
Environmental Concern ◽  
Energy Reduction ◽  
Smart Meters ◽  
Central System ◽  
Energy Feedback ◽  
The Uk ◽  
Feedback Perceptions

The Smart Meter Rollout Programme in the UK has required energy suppliers to offer new smart meters to customers to provide near real-time energy use information and enable two-way communication between the meter and the central system. The provision was expected to result in meaningful energy reductions, but recent estimates suggest that these reductions may be as low as 2%. This paper contributes to the ongoing debate about the effectiveness of smart meters and in-home energy displays by providing insights on energy feedback perceptions from a series of focus groups with postgraduate consumers. In addition to domestic energy use, the study investigated how participants perceived their energy use at work and how they perceived the energy reduction efforts of their institutions and employers. A laddered and projective methodology was used to more deeply question participant perceptions and reveal their attitudes. The analysis of responses revealed a limited awareness around energy efficiency strategies and opportunities for more visual, mobile, engaging and target-driven interfaces for energy data. The findings also agree with previous observations that environmental concerns are not a key driver of energy reduction behaviours. This was shown by laddered questioning, not to be due to a lack of environmental concern, but rather the perception that reducing energy consumption would have negligible impact. A decade after in-home energy displays enabled a means of providing ‘visibility’ to ‘invisible’ energy consumption, little appears to have changed in the perception and experience of energy feedback.

scholarly journals The Impact of Smart Meter Installation on Attitude Change Towards Energy Consumption Behavior Among Northern Ireland Households

2020 ◽  
Vol 28 (4) ◽  
pp. 21-37
Author(s):  
Roya Gholami ◽  
Ali Emrouznejad ◽  
Yazan Alnsour ◽  
Hasan B. Kartal ◽  
Julija Veselova
Keyword(s):  
Energy Consumption ◽  
Northern Ireland ◽  
Attitude Change ◽  
Deep Understanding ◽  
Smart Meter ◽  
Smart Meters ◽  
Consumption Behavior ◽  
Energy Management Systems ◽  
Energy Consumption Patterns ◽  
The Impact

The continuous development of energy management systems, coupled with a growing population, and increasing energy consumption, highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavioral change. Using a data mining segmentation technique, 2,505 Northern Ireland households were segmented into four distinctive profiles, based on their energy consumption patterns, socio-demographic, and dwelling characteristics. The change in attitude towards energy consumption behavior was analyzed to evaluate the impact of smart meter feedback as well. The key finding was 81% of trial participants perceived smart meters to be helpful in reducing their energy consumption. In addition, we found that the potential to reduce energy bills and environmental concerns were the strongest motivations for behavior change.

scholarly journals Partitional Clustering-Hybridized Neuro-Fuzzy Classification Evolved through Parallel Evolutionary Computing and Applied to Energy Decomposition for Demand-Side Management in a Smart Home

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1539
Author(s):  
Yu-Chen Hu ◽  
Yu-Hsiu Lin ◽  
Harinahalli Lokesh Gururaj
Keyword(s):  
Energy Consumption ◽  
Electric Energy ◽  
Smart Meter ◽  
Energy Decomposition ◽  
Smart Meters ◽  
Electrical Grid ◽  
Electric Energy Consumption ◽  
Partitional Clustering ◽  
Neuro Fuzzy ◽  
Consumption Data

The key advantage of smart meters over rotating-disc meters is their ability to transmit electric energy consumption data to power utilities’ remote data centers. Besides enabling the automated collection of consumers’ electric energy consumption data for billing purposes, data gathered by smart meters and analyzed through Artificial Intelligence (AI) make the realization of consumer-centric use cases possible. A smart meter installed in a domestic sector of an electrical grid and used for the realization of consumer-centric use cases is located at the entry point of a household/building’s electrical grid connection and can gather composite/circuit-level electric energy consumption data. However, it is not able to decompose its measured circuit-level electric energy consumption into appliance-level electric energy consumption. In this research, we present an AI model, a neuro-fuzzy classifier integrated with partitional clustering and metaheuristically optimized through parallel-computing-accelerated evolutionary computing, that performs energy decomposition on smart meter data in residential demand-side management, where a publicly available UK-DALE (UK Domestic Appliance-Level Electricity) dataset is used to experimentally test the presented model to classify the On/Off status of monitored electrical appliances. As shown in this research, the presented AI model is effective at providing energy decomposition for domestic consumers. Further, energy decomposition can be provided for industrial as well as commercial consumers.

The Impact of Smart Meter Installation on Attitude Change Towards Energy Consumption Behavior Among Northern Ireland Households

2021 ◽  
pp. 925-943
Author(s):  
Roya Gholami ◽  
Ali Emrouznejad ◽  
Yazan Alnsour ◽  
Hasan B. Kartal ◽  
Julija Veselova
Keyword(s):  
Energy Consumption ◽  
Northern Ireland ◽  
Attitude Change ◽  
Deep Understanding ◽  
Smart Meter ◽  
Smart Meters ◽  
Consumption Behavior ◽  
Energy Management Systems ◽  
Energy Consumption Patterns ◽  
The Impact

The continuous development of energy management systems, coupled with a growing population, and increasing energy consumption, highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavioral change. Using a data mining segmentation technique, 2,505 Northern Ireland households were segmented into four distinctive profiles, based on their energy consumption patterns, socio-demographic, and dwelling characteristics. The change in attitude towards energy consumption behavior was analyzed to evaluate the impact of smart meter feedback as well. The key finding was 81% of trial participants perceived smart meters to be helpful in reducing their energy consumption. In addition, we found that the potential to reduce energy bills and environmental concerns were the strongest motivations for behavior change.

scholarly journals A Novel IoT Based Smart Energy Meter with Backup Battery

2021 ◽  
pp. 357-364
Author(s):  
Osman Yakubu ◽  
C. Narendra Babu ◽  
C. Osei Adjei
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Energy Demand ◽  
Single Phase ◽  
Data Repository ◽  
Smart Meters ◽  
Cloud Data ◽  
Energy Meter ◽  
Consumption Data ◽  
Utility Companies

Energy consumption is currently on the ascendency due to increased demand by domestic and industrial consumers. The quest to ensure that consumers manage their consumption and the utility companies also monitor consumers to manage energy demand and production resulted in smart energy meters which are able to transmit data automatically at certain intervals being introduced. These Smart Meters are still fraught with challenges as consumers are unable to effectively monitor their consumption and the meters are also expensive to deploy. This research aims to present a novel IoT based Smart Energy Meter that will gather consumption data in real time and transmit it to a cloud data repository for storage and analysis. The novelty of this inexpensive system is the introduction of an ADM25SC Single Phase DIN-RAIL Watt-hour Energy Meter which sends power to the microcontroller and also the introduction of a backup battery that keeps the meter on for some time to transmit outage data during power outages. Data gathered from the proposed IoT based Smart Energy Meter for a period is compared against that of the same period from a Smart G meter, a widely used energy meter, and is found to be very close confirming the accuracy of the IoT based Smart Energy Meter.

Sign in / Sign up

Export Citation Format

Share Document