scholarly journals Feasibility of using smart meter water consumption data and in-sewer flow observations for sewer system analysis: a case study

2021 ◽  
Author(s):  
N. S. V. Lund ◽  
J. K. Kirstein ◽  
H. Madsen ◽  
O. Mark ◽  
P. S. Mikkelsen ◽  
...  
Keyword(s):  
Water Consumption ◽  
System Analysis ◽  
Temporal Dynamics ◽  
Distribution Data ◽  
High Temporal Resolution ◽  
Detailed Knowledge ◽  
Urban Drainage ◽  
Smart Meter ◽  
Smart Meters ◽  
Sewer System

Abstract Globally, smart meters measuring the water consumption with a high temporal resolution at the consumers' households are deployed at an increasing rate. In addition to their use for billing or leak detection purposes, smart meters may provide a detailed knowledge of the wastewater inflow to the sewer systems in space and time and open up for new types of system analyses aimed at closing the urban water balance. In this study, we first validate the smart meter data against other, independent water distribution data. Subsequently, we use a detailed hydrodynamic sewer system model to link the smart meter data from almost 2,000 consumers with in-sewer flow observations in order to simulate the wastewater component of the dry weather flow (DWF) and to identify potential anomalies. Results show that it is feasible to use smart meter data as input to a distributed urban drainage model, as the temporal dynamics of the model results and in-sewer flow observations match well. Furthermore, the study suggests that in-sewer flow observations may be subject to unrecognised uncertainties, which make them unsuitable for advanced investigations of the DWF composition, and this underlines the necessity of collecting data from independent sources. The study also exemplifies that digital system integration in the water sector may be complicated. However, overcoming these obstacles may improve both offline and real-time urban drainage management.

scholarly journals Framing Smart Meter Feedback in Relation to Practice Theory

2018 ◽  
Vol 10 (10) ◽  
pp. 3553 ◽  
Author(s):  
Hanna Mela ◽  
Juha Peltomaa ◽  
Marja Salo ◽  
Kirsi Mäkinen ◽  
Mikael Hildén
Keyword(s):  
Renewable Energy ◽  
Water Consumption ◽  
Social Practice ◽  
Practice Theory ◽  
Decision Makers ◽  
Smart Meter ◽  
Smart Metering ◽  
Smart Meters ◽  
Domestic Energy

Smart metering is advancing rapidly and consumption feedback from smart meters is expected to help residents to reduce their energy and water consumption. In recent years, more critical views have been expressed based on theories of social practice, arguing that smart meter feedback ignores the role of various mundane practices where energy and water are consumed and instead targets individuals as active decision-makers. We present a review of qualitative studies on smart meter feedback and results of a survey to European smart metering projects. We argue that theories of social practice can be used to reframe the challenges and potentials of smart meter feedback that have been identified in the literature and our survey. This presents challenges of smart meter feedback as resulting from normalised resource intensive practices rather than from uninterested and comfort-loving individuals. Potentials of improving the effectiveness of smart meter feedback relate to supporting communities and peer-learning and combining smart meter feedback with micro-generation of renewable energy. This has implications for how domestic energy and water consumption is targeted by policy.

scholarly journals Long-term water conservation is fostered by smart meter-based feedback and digital user engagement

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andrea Cominola ◽  
Matteo Giuliani ◽  
Andrea Castelletti ◽  
Piero Fraternali ◽  
Sergio Luis Herrera Gonzalez ◽  
...  
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Behavioral Change ◽  
User Engagement ◽  
Smart Meter ◽  
Smart Meters ◽  
Engagement Interventions ◽  
Pre Treatment ◽  
Experimental Trials

AbstractConsumption-based feedback has been demonstrated to encourage water conservation behaviors. Smart meters and digital solutions can support customized feedback and reinforce behavioral change. Yet, most of the studies documenting water conservation effects induced by feedback and smart meter data visualization evaluate them in short-term experimental trials only. Here we show that water conservation behaviors promoted by smart meter-based consumption feedback and digital user engagement interventions might persist in the long term. We developed an analysis of 334 households in Valencia, Spain. We find that approximately 47% of the households engaged in our water conservation program achieved a long-term 8% reduction of volumetric water consumption, compared with pre-treatment observations. Water conservation behaviors persisted more than two years after the beginning of the program, especially for the households receiving sub-daily smart meter information. Our results provide empirical evidence that smart meter-based water consumption feedback and digital user engagement can effectively promote durable conservation behaviors.

Integrated modelling: comparison of state variables, processes and parameters in sewer and wastewater treatment plant models

1997 ◽  
Vol 36 (5) ◽  
pp. 373-380 ◽  
Author(s):  
C. Fronteau ◽  
W. Bauwens ◽  
P.A. Vanrolleghem
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Drainage System ◽  
Integrated Modelling ◽  
Urban Drainage ◽  
State Variables ◽  
Sewer System ◽  
Wastewater Treatment Process ◽  
Urban Drainage System

All the parts of an urban drainage system, i.e. the sewer system, the wastewater treatment plant (WWTP) and the river, should be integrated into one single model to assess the performance of the overall system and for the development of design and control strategies assisting in its sustainable and cost effective management. Existing models for the individual components of the system have to be merged in order to develop the integrated tool. One of the problems arising from this methodology is the incompatibility of state variables, processes and parameters used in the different modelling approaches. Optimisation of an urban drainage system, and of the wastewater treatment process in particular, requires a good knowledge of the wastewater composition. As important transformations take place between the emission from the household and the arrival at the treatment facility, sewer models should include these transformations in the sewer system. At present, however, research is still needed in order to increase our knowledge of these in-sewer processes. A comparison of the state variables, processes and parameters has been carried out in both sewer models (SMs) and activated sludge models (ASMs). An ASM approach is used for the description of reactions in sewer models. However, a difference is found in the expression for organic material (expressed in terms of BOD) and heterotrophic biomass is absent as a state variable, resulting in differences in processes and parameters. Reconciliation of both the models seems worthwhile and a preliminary solution is suggested in this paper.

scholarly journals Evaluation Model of Operation State Based on Deep Learning for Smart Meter

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4674
Author(s):  
Qingsheng Zhao ◽  
Juwen Mu ◽  
Xiaoqing Han ◽  
Dingkang Liang ◽  
Xuping Wang
Keyword(s):  
Deep Learning ◽  
Power Consumption ◽  
Detection Efficiency ◽  
Evaluation Model ◽  
Smart Meter ◽  
Smart Meters ◽  
Abnormal Detection ◽  
Prediction Residual ◽  
Threshold Setting ◽  
Training Efficiency

The operation state detection of numerous smart meters is a significant problem caused by manual on-site testing. This paper addresses the problem of improving the malfunction detection efficiency of smart meters using deep learning and proposes a novel evaluation model of operation state for smart meter. This evaluation model adopts recurrent neural networks (RNN) to predict power consumption. According to the prediction residual between predicted power consumption and the observed power consumption, the malfunctioning smart meter is detected. The training efficiency for the prediction model is improved by using transfer learning (TL). This evaluation uses an accumulator algorithm and threshold setting with flexibility for abnormal detection. In the simulation experiment, the detection principle is demonstrated to improve efficient replacement and extend the average using time of smart meters. The effectiveness of the evaluation model was verified on the actual station dataset. It has accurately detected the operation state of smart meters.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

Automatic, semi-automatic and manual validation of urban drainage data

2010 ◽  
Vol 62 (5) ◽  
pp. 1013-1021 ◽  
Author(s):  
N. Branisavljević ◽  
D. Prodanović ◽  
D. Pavlović
Keyword(s):  
Data Quality ◽  
Sensor Technology ◽  
Urban Drainage ◽  
Data Validation ◽  
Validation Process ◽  
Long Distance ◽  
Sewer System ◽  
Validation Data ◽  
Data Quality Assessment ◽  
Distance Data

Advances in sensor technology and the possibility of automated long distance data transmission have made continuous measurements the preferable way of monitoring urban drainage processes. Usually, the collected data have to be processed by an expert in order to detect and mark the wrong data, remove them and replace them with interpolated data. In general, the first step in detecting the wrong, anomaly data is called the data quality assessment or data validation. Data validation consists of three parts: data preparation, validation scores generation and scores interpretation. This paper will present the overall framework for the data quality improvement system, suitable for automatic, semi-automatic or manual operation. The first two steps of the validation process are explained in more detail, using several validation methods on the same set of real-case data from the Belgrade sewer system. The final part of the validation process, which is the scores interpretation, needs to be further investigated on the developed system.

scholarly journals Electric Consumption Assessment using Smart Meter Data and KPI Methodology

2020 ◽  
Vol 57 (3) ◽  
pp. 3-19
Author(s):  
A. Mutule ◽  
I. Zikmanis ◽  
A.-M. Dumitrescu
Keyword(s):  
State Of The Art ◽  
Residential Area ◽  
Electric Power System ◽  
Modern World ◽  
Specific Situation ◽  
Smart Meter ◽  
Smart Meters ◽  
The World ◽  
Study Case ◽  
Grid Operators

AbstractIn the modern world, many cities make use of state-of-the-art technologies for a diversity of applications. A field with very specific needs is the electric power system that deals with both large entities that govern themselves (grid operators) and the citizens. For both and all actors in between, there is an increased need for information. Steps to provide these data are always taken and several initiatives are ongoing across the world to equip residential users with last generation smart meters. However, a full deployment is still not possible. Considering this aspect, the authors propose KPIs for the specific situation when some information is available from the meters and other sources, but some is not. The study case is based on a residential area occupied mainly by university students and after an extensive measurement campaign the results have been studied and analysis methods proposed.

scholarly journals Decline of unique Pontocaspian biodiversity in the Black Sea Basin: a review

2021 ◽  
Author(s):  
Aleksandre Gogaladze ◽  
Mikhail Son ◽  
Matteo Lattuada ◽  
Vitaliy Anistratenko ◽  
Vitaly Syomin ◽  
...  
Keyword(s):  
Black Sea ◽  
Species Distribution ◽  
The Black Sea ◽  
Distribution Data ◽  
Past Century ◽  
Detailed Knowledge ◽  
The Past ◽  
Mollusc Species ◽  
Anthropogenic Threats ◽  
Effective Conservation

Aim The unique aquatic Pontocaspian (PC) biota of the Black Sea Basin (BSB) is in decline. Lack of detailed knowledge on the status and trends of species, populations and communities hampers a thorough risk assessment and precludes effective conservation. This paper aims to review PC biodiversity trends using endemic molluscs as a model group. We aim to assess changes in PC habitats, community structure and species distribution over the past century and to identify direct anthropogenic threats. Location Black Sea Basin (Bulgaria, Romania, Moldova, Ukraine and Russia). Methods Presence/absence data of target mollusc species was assembled from literature, reports and personal observations. PC biodiversity trends in the NW BSB coastal regions were established by comparing 20th and 21st century occurrences. Direct drivers of habitat and biodiversity change were identified and documented. Results A very strong decline of PC species and communities during the past century is driven by a) damming of rivers, b) habitat modifications negatively affecting salinity gradients, c) pollution and eutrophication, d) invasive alien species and e) climate change. Four out of 10 studied regions, namely, the Danube Delta – Razim Lake system, Dniester Liman, Dnieper-South Bug Estuary and Taganrog Bay-Don Delta contain the entire spectrum of ecological conditions to support PC communities and still host threatened endemic PC mollusc species. Distribution data is incomplete, but the scale of deterioration of PC species and communities is evident from the assembled data, as are major direct threats. Main conclusions PC biodiversity in the BSB is profoundly affected by human activities. Standardised observation and collection data as well as precise definition of PC biota and habitats are necessary for targeted conservation actions. This study will help to set the research and policy agenda required to improve data collection to accommodate effective conservation of the unique PC biota.

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.

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.

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