Smart Gas Meters Research Articles

Effect of hydrogen blending on the accuracy of smart gas meters

The exploitation of green hydrogen blending with natural gas (NG) is expected to contribute in lowering greenhouse gas emissions and fostering the share of renewable energy sources (RES). The NG infrastructure, in fact, can act as a storage facility for green hydrogen produced from excess RES, also providing flexibility to the electric system. However, the unbalance of the networks and the raise of protection issues for consumers may occur as a consequence of the potential decay of the metrological performance of gas meters operating with natural gas and hydrogen blends. In this paper, the authors present the results of an experimental campaign aimed at analysing the effect of hydrogen blending on the accuracy of smart domestic gas meters. Experimental tests were performed in the laboratory using air, natural gas and gas-hydrogen blends up to 23%vol. The results show no criticalities occur for diaphragm and ultrasonic gas meters, regardless of the hydrogen content. On the other hand, thermal mass gas meters show good reliability when hydrogen blends are within 2%vol, whereas for higher hydrogen contents, reliability is demonstrated only when they are equipped with a specific new design routine capable to address the gas quality changes.

Smart Gas Meter and Information Transmission Procedure for an IoT Structure

This research presents an IoT structure for smart gas metering, including a smart gas meter sensing and management structure, a gas network connectivity structure, and a gas company comprehensive gas administration structure. The smart gas meter sensing and management structure consists of a detection unit and a control unit, while the gas network connectivity structure comprises communication structures for detection information and control information. The gas company comprehensive gas administration structure integrates detection details management and control details management. The objective of this study is to design a smart gas meter and develop an effective information transmission procedure for the IoT structure. The proposed structure aims to enhance gas metering accuracy, optimize communication efficiency, and enable comprehensive gas administration.

Study on the Optimization of the Material Distribution Path in an Electronic Assembly Manufacturing Company Workshop Based on a Genetic Algorithm Considering Carbon Emissions

In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using an improved genetic algorithm. The problem is processed using Gray code and crossover and variation operations with a genetic algorithm. To improve the search accuracy and convergence speed of the algorithm, an adaptive mutation method is proposed to enhance the diversity of the population and to achieve global optimal path objective finding. The improved algorithm is applied to workshop path multi-station logistics path planning, which effectively solves the transport path optimization and station solving problems in workshop logistics distribution, and the convergence speed and convergence accuracy of the algorithm are significantly improved. Finally, a simulation analysis is carried out on the optimization of the production material distribution of a smart gas meter workshop owned by K Company, which is an electronic assembly manufacturing company. We used MATLAB software for the case company logistics distribution route model for data analysis and solving. Due to the consideration of carbon emissions, we did not consider two kinds of experiments, which were two different cases of the optimal path. The experimental results verify that the distribution optimization scheduling model can meet the demands for immediate material distribution in the production workshop, which is conducive to improving material distribution efficiency, reducing logistics costs and achieving the goal of lowering carbon emissions. This optimization model has a certain utility in that in the current context of aiming for carbon neutral and carbon peaking, early low carbon distribution layout can reduce the environmental cost of the enterprise, making material distribution a more environmental economic path.

Low-Power Transit Time-Based Gas Flow Sensor with Accuracy Optimization.

In this paper, a fully designed ultrasonic transit time-based gas flow sensor is presented. The proposed sensor has been optimized in terms of accuracy, sensitivity, and power consumption at different design stages: mechanical design of the sensor pipe, piezoelectric transducer configuration and validation over temperature, time of flight detection algorithm, and electronics design. From the optimization and integration of each design part, the final designed gas flow sensor is based on the employment of 200 kHz-piezoelectric transducers mounted in a V-configuration and on the implementation of a cross-correlation algorithm based on the Hilbert Transform for time-of-flight detection purposes. The proposed sensor has been experimentally validated at different flow rates and temperatures, and it fully complies with the accuracy specifications required by the European standard EN14236, placing the proposed design into the state of the art of ultrasonic gas flow sensors regarding cost, accuracy, and power consumption, the latter of which is crucial for implementing smart gas meters that are able to autonomously operate as IoT devices by extending their battery life.

Building penetration loss measurements and modelling in the 900 and 2100 MHz band for smart meter installation

One of the most significant applications of Internet of Things are smart meters with wireless capabilities. Smart gas and electricity meters can capture half-hourly pricing and consumption data and send automated meter readings to your energy provider, in contrast to regular meters that can only register a running total of energy used. However, the legacy regular meters were not installed with wireless connectivity in mind and are usually found in hard-to-reach places for wireless radio coverage. To understand these scenarios, this paper provides signal strength measurements conducted at the Building Research Establishment determining building penetration losses in both 900 and 2,100 MHz band. We then present a building penetration loss model using these measurements that is practical and cost effective when compared to traditional statistical propagation loss models.

Ultralow-Power Sensing Framework for Internet of Things: A Smart Gas Meter as a Case

Gas serves as one of the most indispensable energy sources for industrial production and household life. In order to improve the gas utilization efficiency, smart gas meters for the Internet of Things (IoT) has been designed to achieve two-way communication and remote control functions. However, the existing smart gas meter does not consider further reduction of power consumption. Thus, we designed an ultralow-power sensing framework for IoT and applied it to the smart gas meter. Based on a thorough analysis of the metering system, we propose an ultralow power system framework and a low-power peripheral management solution to reach ultralow power consumption. Also, we propose a cooperative sensing scheme to achieve stability and accuracy of gas volume detection. Finally, we implement a real smart gas manage system to evaluate our low-power smart gas meter solution. Verified by a comparative test, the proposed gas meter successfully reduces the power consumption by at least 37% compared to the baseline. The experimental results verify the innovative design and confirm that the proposed gas meter features ultralow power consumption, high precision, and high reliability.

Density Based Fuzzy C Means Clustering to prolong Network Lifetime in Smart Grids

Wireless sensor networks (WSN's) are preferred for industrial applications due to progressive increase of sensor electronics. One such application is deployment of WSN's in smart grids. Smart Grid integrates information and communication techniques with electricity network. Smart grids utilize sophisticated control and monitoring devices for improving the efficiency of the grid. For energy efficient, low cost monitoring and control in smart grid WSN's is treated as a promising technology. Advanced Metering Infrastructure (AMI) is the key technology in the distribution networks of Smart Grid. The AMI is composed of various sensors for metering purpose. The meter data is also useful for the distribution operators to manage the demand response. The network involves smart meters, smart electric gas and water meters along with digital network management appliances for optimizing the electric network with real time data management. The smart sensors are limited in terms of battery, operational power and memory. These sensors communicate with the base station in restricted range. The communication between smart grid nodes and base station (sink) is multi-hop in nature. The communication takes place within limited range of communication so the security concerns that are involved in the network are to be handled by the routing protocols. So as to make the bidirectional communication efficient between the smart sensors and utility an effective routing scheme is required for these energy limited devices to handle the heavy network traffic in smart grids. Here energy efficient routing for WSN's in NAN networks to attain load balancing is proposed through density based Fuzzy C means clustering (DFCM). The obtained simulation results show that DFCM can provide a satisfactory performance for enhancing the network life span.

MFVL HCCA: A Modified Fast-Vegas-LIA Hybrid Congestion Control Algorithm for MPTCP Traffic Flows in Multihomed Smart Gas IoT Networks

Multihomed smart gas meters are Internet of Things (IoT) devices that transmit information wirelessly to a cloud or remote database via multiple network paths. The information is utilized by the smart gas grid for accurate load forecasting and several other important tasks. With the rapid growth in such smart IoT networks and data rates, reliable transport layer protocols with efficient congestion control algorithms are required. The small Transmission Control Protocol/Internet Protocol (TCP/IP) stacks designed for IoT devices still lack efficient congestion control schemes. Multipath transmission control protocol (MPTCP) based congestion control algorithms are among the recent research topics. Many coupled and uncoupled congestion control algorithms have been proposed by researchers. The default congestion control algorithm for MPTCP is coupled congestion control by using the linked-increases algorithm (LIA). In battery powered smart meters, packet retransmissions consume extra power and low goodput results in poor system performance. In this study, we propose a modified Fast-Vegas-LIA hybrid congestion control algorithm (MFVL HCCA) for MPTCP by considering the requirements of a smart gas grid. Our novel algorithm operates in uncoupled congestion control mode as long as there is no shared bottleneck and switches to coupled congestion control mode otherwise. We have presented the details of our proposed model and compared the simulation results with the default coupled congestion control for MPTCP. Our proposed algorithm in uncoupled mode shows a decrease in packet loss up to 50% and increase in average goodput up to 30%.

The Development of the Smart Gas Distribution: General Trends and the Latvian Context

Abstract A necessity to reduce greenhouse gas (hereinafter – GHG) emissions and energy import dependency, while coping with increasing energy demand, affordability issues and many other factors, causes the European Union (hereinafter – EU) energy policy makers to identify development trends that would help harmonize future energy market and technological changes with ever growing pressure of universal data processing digitalisation. In order to stimulate data processing digitalisation in energy, the European Commission has proclaimed a support to the development of all kind of the smart energy systems, where simultaneous use of the natural gas and renewable gases (hereinafter – RG) will play one of the major sustainability ensuring roles. Firstly, it will help achieve designated energy efficiency goals and, secondly, enable cost saving synergetic solutions at the early stages of the energy supply chain decarbonisation. Synergy of the natural gas and RG emphasises the need for a modern, smart and sustainable energy infrastructure to allow developing more flexible back-up and balancing power capacity, storage solutions and innovative demand-response mechanisms. This paper addresses some trends in development of the smart gas distribution (hereinafter – SGD) as part of the smart energy systems both in the EU and Latvia, with a particular focus on smart energy concepts, smart gas metering and grid modernisation.

Perceptions on Smart Gas Meters in Smart Cities for Reducing the Carbon Footprint

Carbon emission is a prominent issue, and smart urban solutions have the technological capabilities to implement change. The technologies for creating smart energy systems already exist, some of which are currently under wide deployment globally. By investing in energy efficiency solutions (such as the smart meter), research shows that the end-user is able to not only save money, but also reduce their household’s carbon footprint. Therefore, in this paper, the focus is on the end-user, and adopting a quantitative analysis of the perception of 1365 homes concerning the smart gas meter installation. The focus is on linking end-user attributes (age, education, social class and employment status) with their opinion on reducing energy, saving money, changing home behaviour and lowering carbon emissions. The results show that there is a statistical significance between certain attributes of end-users and their consideration of smart meters for making beneficial changes. In particular, the investigation demonstrates that the employment status, age and social class of the homeowner have statistical significance on the end-users’ variance; particularly when interested in reducing their bill and changing their behaviour around the home.

Intelligent Diagnosis of Acquisition Equipment Failure Promote “Multi-integration” Application

The information collection system of State Grid Corporation has accessed a large number of smart energy meter, water meter, gas meter and heat meter data, implemented the “multi-integration” collection and construction to improve the public service level of the society, and actively respond to the call for government smart city construction. However, many operating equipment and complex operating environments often generate various equipment failure problems. It is difficult to identify faults and has low efficiency in troubleshooting. The intelligent diagnosis of the collection equipment fault is based on various information such as operation and maintenance, environment, fault analysis and acquisition. It uses big data analysis and artificial intelligence technology to conduct Intelligent Diagnosis Model of Acquisition Fault research, so as to solve the accurate judgment of the failure of the collection device, qualitative analysis of equipment fault and on-site, workflow troubleshooting guidance issues. Using the intelligent diagnosis of faults to solve the problem of “multi-integration” collection and maintenance, it can effectively improve the efficiency of fault handling, better promote the application of “multi-integration” and promote the construction of smart cities.

On the application of support vector machines to the prediction of propagation losses at 169 MHz for smart metering applications

Recently, the need of deploying new wireless networks for smart gas metering has raised the problem of radio planning in the 169 MHz band. Unluckily, software tools commonly adopted for radio planning in cellular communication systems cannot be employed to solve this problem because of the substantially lower transmission frequencies characterising this application. In this study, a novel data-centric solution, based on the use of support vector machine techniques for classification and regression, is illustrated. The proposed method requires the availability of a limited set of received signal strength measurements and the knowledge of a three-dimensional map of the propagation environment of interest and generates both an estimate of the coverage area and a prediction of the field strength within it. Various numerical results show that the proposed method is able to achieve good accuracy at the price of an acceptable computational cost and of a limited effort for the acquisition of measurements in the considered environments.

MEMS-Based Smart Gas Metering for Internet of Things

Utilities have traditionally employed or contracted meter readers to collect natural gas usage data, which is expensive and time consuming, and thus necessitates the need of smart natural gas metering. Existing gas metering systems mainly focus on measuring the amount of gas flowing through an microelectro mechanical system (MEMS) thermal gas flow sensor and simply ignore the detailed gas composition. From computational fluid mechanics simulations, however, we discover that gases with different compositions will cause different effects on the reading of an MEMS sensor. Based on a thorough analysis of the working principle of MEMS thermal gas flow sensor, we propose an innovative mechanism to compensate the errors caused by different types of natural gases on the sensor’s reading. The proposed solution first measures the physical property of metered gas to derive the composition correction coefficient that will then be used to correct the meter’s reading errors, considering the relation between the calorific value and physical property of natural gases. In this way, the proposed solution realizes a real-time multicomposition gas metering via thermal gas flow sensors. We implement and evaluate the proposed gas metering technique in various Internet of Things systems, including industrial flow metering, gas metering in smart home, and gas metering in low-power wide-area networks. Experiment results verify the innovative design and confirm that the proposed solution features high sensitivity, high precision, and high range ratio.

Vulnerability and resistance in the United Kingdom's smart meter transition

The Smart Meter Implementation Program (SMIP) lays the legal framework in the United Kingdom so that a smart gas and electricity meter, along with an in-home display, can be installed in every household by 2020. Intended to reduce household energy consumption by 5–15%, the SMIP represents the world's largest and most expensive smart meter rollout. However, a series of obstacles and delays has restricted implementation. To explore why, this study investigates the socio-technical challenges facing the SMIP, with a strong emphasis on the “social” side of the equation. It explains its two primary sources of data, a systematic review of the academic literature coupled with observation of seven major SMIP events. It offers a history of the SMIP rollout, including a summary of 67 potential benefits as well as often-discussed technical challenges, before delving into pertinent non-technical challenges, specifically vulnerability as well as consumer resistance and ambivalence. In doing so, the paper not only presents a critique of SMIP, it also offers a review of academic studies on consumer responses to smart meters, an analysis of the intersection between smart meters and other social concerns such as poverty or the marginalization of rural areas, and the generation of policy lessons.

Energy and Congestion-Aware Routing Metric for Smart Grid AMI Networks in Smart City

Advanced metering infrastructure (AMI) is becoming a vital part of utility distribution networks, allowing the development of smart cities. AMI consists of smart electric, gas, and water meters, and the devices are very limited in terms of battery, processing power, and memory. The deployment and operational needs of energy-constrained network infrastructures in smart water and gas metering systems require the use of routing mechanisms that consider energy consumption, minimize energy use, and prolong network lifetime. An efficient routing metric is needed for energy-constrained devices. In this paper, we propose an energy- and congestion-aware routing metric for smart meter networks to be deployed in smart cities. The proposed metric is an adaptive parent node selection mechanism that considers the residual energy and queue utilization of neighboring nodes. Minimizing power consumption will enhance network lifetime. The proposed scheme was evaluated with the Cooja Simulator 3.0 using random and grid topology. The simulation results show greater network performance in terms of average power consumption and packet delivery ratio.

Multi-Antenna Data Collector for Smart Metering Networks with Integrated Source Separation by Spatial Filtering

AbstractWireless transmission systems in smart metering networks share the advantage of lower installation costs due to the expandability of separate infrastructure but suffer from transmission problems. In this paper the issue of interference of wireless transmitted smart meter data with third party systems and data from other meters is investigated and an approach for solving the problem is presented. A multi-channel wireless m-bus receiver was developed to separate the desired data from unwanted interferers by spatial filtering. The according algorithms are presented and the influence of different antenna types on the spatial filtering is investigated. The performance of the spatial filtering is evaluated by extensive measurements in a realistic surrounding with several hundreds of active wireless m-bus transponders. These measurements correspond to the future environment for data-collectors as they took place in rural and urban areas with smart gas meters equipped with wireless m-bus transponders installed in almost all surrounding buildings.

A Comprehensive Review of Smart Energy Meters in Intelligent Energy Networks

The significant increase in energy consumption and the rapid development of renewable energy, such as solar power and wind power, have brought huge challenges to energy security and the environment, which, in the meantime, stimulate the development of energy networks toward a more intelligent direction. Smart meters are the most fundamental components in the intelligent energy networks (IENs). In addition to measuring energy flows, smart energy meters can exchange the information on energy consumption and the status of energy networks between utility companies and consumers. Furthermore, smart energy meters can also be used to monitor and control home appliances and other devices according to the individual consumer’s instruction. This paper systematically reviews the development and deployment of smart energy meters, including smart electricity meters, smart heat meters, and smart gas meters. By examining various functions and applications of smart energy meters, as well as associated benefits and costs, this paper provides insights and guidelines regarding the future development of smart meters.

A new low-cost hydrogen sensor build with a thermopile IR detector adapted to measure thermal conductivity

Abstract. It is demonstrated how a commercially available MEMS thermopile infrared radiation sensor can be used as thermal conductivity gas detector (TCD). Since a TCD requires a heater while IR-thermopile sensors have no integrated heater, the thermopile itself is used as heater and temperature sensor at the same time. It is exposed to the measured gas environment in its housing. It is shown that, by using a simple driving circuitry, a mass-produced low-cost IR sensor can be used for hydrogen detection in applications such as hydrogen safety and smart gas metering. The sensor was tested to measure hydrogen in nitrogen with concentration of 0–100 % with a noise equivalent concentration of 3.7 ppm.

An assessment of the Italian smart gas metering program

The introduction of smart metering is one of the core elements in recent European policies targeting environmental sustainability and competitiveness of energy markets. Following the roll-out of smart electricity meters, in 2008 the Italian regulator designed an ambitious deployment program also for smart gas meters, that was recently modified in both scope and timing. This paper assesses Italy's original and current deployment plans, with a specific focus on the results of its cost–benefit analysis. In light of the evidence derived from the literature, we observe that the case for the roll-out of smart gas meters in Italy was not supported by a strong emphasis on energy savings but rather focused on increasing efficiency of the Italian gas market; in this respect, we argue that options other than smart gas metering should also be considered. Moreover the Italian cost–benefit analysis, which mostly dealt with the potential cost savings for distributors and suppliers, led to ambiguous results in terms of net present values; thus, we believe that an updated assessment would be extremely useful. Finally, in terms of technological choices, our analysis positively evaluates the regulator's recent proposal to consider a dual-fuel solution for the mass market deployment.

An Ultra Low-Power MR*1) Sensor for a Smart Water Meter or a Smart Gas Meter

A new ultra low power MR sensor comprising MR elements integrated with Bi-CMOS IC chip, which is optimal for the use in smart water meters and gas meters playing important role in global smart gridization, has been developed. MR elements are configured as a Wheatstone bridge circuit. MR element patterns are placed in the perpendicular configurations as resistive components of the circuit. Those detect the magnetic field applied to X and Y axis respectively, and then outputs either high or low-level electric signal. Optimization of the MR element pattern aspect ratio (ratio of the element length to the element width) and configuration of the two-row parallel MR patterns in a longitudinal direction enable the equivalent current flow in the direction. This provides mutual magnetostatic coupling and cancellation of each demagnetizing field, and led to achieve minimizing the hysteresis of the resistance change rate affected by up and down of the applied magnetic field. Furthermore, this led to the improvement of mutual symmetry for both S to N and N to S direction of the magnetic field. This resulted in enhanced magnetic sensitivity and successfully obtained magnetic sensitivity higher than 0.8kA/m. For the power supply of the MR sensor, external intermittent control was adopted. Furthermore, active (on) time of the MR element was considerably shortened by utilizing the internal circuit of the IC. As a result, the sampling time was shortened to 1μs and the drive current of MR sensor was reduced to 0.3 μA. *1)MR: Magneto-resistance