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Energy efficiency is an important issue in industry, especially with the ever-increasing consumption of electrical energy. The power quality and the traceability of metering devices are essential when integrating energy metering systems for energy efficiency. This management requires an understanding of electrical current events such as pulse and transient currents. Current transducers are widely used to measure these electrical current events up to a few megahertz. Their use makes it possible to measure not only the main current flowing through the transducer, but also the bypass current that affects electrical equipment. Calibration of these sensors up to a few megahertz then becomes an essential step. Currently, most calibration methods are limited to 100 kHz frequency for a current of 10 A. This paper presents an improvement of a traceable calibration methodology for current transducers up to 10 A and 1 MHz, thus increasing, by 10 times, the current level for such high frequency applications. This calibration methodology is based on a metrological traceability chain (uninterrupted link to the International System of Units) with respect to a calculable current shunt and is currently the only traceable method for calibrating current transducers at 10 A and up to 1 MHz. The uncertainty obtained for the transimpedance ratio is less than 0.2%, which is considerably reduced with respect to the existing capabilities. [ABSTRACT FROM AUTHOR]

In the European Union, increasing attention is already being paid not only to the development of renewable energy sources, but also to the establishment of solutions to achieve local energy self-sufficiency while increasing the role of citizens in managing the energy they generate. This approach is expected both to have a positive impact on the environment and the reduction of greenhouse gas emissions, and to enhance energy security—both in economic and civic terms by, i.a., combating energy poverty. The development of local energy communities promoted in the EU is supported i.a. by energy cooperatives. These contribute to the efficient harnessing of renewable energy potential in rural and urban-rural areas, and have been developing in Poland for several years now. In their previous studies, the authors of this research paper attempted to verify the generation (number, type and capacity of installed sources) and consumption (energy demand) configurations in which an energy cooperative would be a viable solution for prosumers who might establish it. However, over the past few years, the conditions for prosumers and the method of their accounting with the electricity seller have changed radically in Poland (shift from net metering to net billing). This situation has opened up space for further research and encouraged the authors to revisit the problem of analyzing the viability of establishing energy cooperatives in relation to the rules of operation of individual prosumers. This research was carried out for three scenarios, and the horizon of the analyses conducted and described extends to 2045. The comparative analysis included energy consumers without their own generation sources, prosumers with a photovoltaic generation installation covered by the net billing model, as well as a scenario involving prosumers' cooperation within an energy cooperative, which by law is settled in the net metering model. Conclusions from the research and simulations made it possible to confirm the claim that, despite changes in the rules of prosumer billing, developing energy independence in the energy community formula results in a significant reduction in the cost of purchasing electricity (even several times lower purchase costs in the timeframe analyzed) and can lead to a reduction in the payback time of investments in generation sources even by a factor of two. The results presented in this research paper open up space for further research. The outcomes allow us to assume that energy cooperatives—in the organizational and institutional model in Poland—are a good tool for reducing the phenomenon of energy poverty on a local scale. [ABSTRACT FROM AUTHOR]

Featured Application: Improving the measurement of electricity consumption by reducing errors is the main objective of this article. As a concrete application, the presented algorithm is used for the determination of electricity meters by the end user. With minimal costs, a correct assessment of energy consumption can be made, and therefore the calculated electricity costs should be accurate. Although data acquisition is a very usual technique, several aspects are not always considered, such as the synchronization of the acquired measures and the evaluation of the resulting errors. This paper aims to highlight this fact by the mathematical determination of the necessary correction and the implementation of software meant to evaluate the performances of acquisition systems. As an example, a three-phased acquisition system was developed in order to monitor the currents and voltages on the three phases. Also, other measures were performed, such as of power and phase. The components on each phase did not have to be fully identified because a whole system calibration could be performed in the first stage. The calibration consisted in finding the weighting coefficients for each measured quantity. The implemented solution for three-phased measure acquisition started from the hypothesis of a sampling frequency that respected the Shannon theorem. The distance between two samples was small enough to consider a linear evolution between two moments for the same measure. Errors that affected the above-mentioned measures, due to the fact that the samples were examined in different moments, were analyzed and brought to the minimum value. Finding a solution to reduce the sampling errors is closely related to reducing the costs. [ABSTRACT FROM AUTHOR]

Metrological characterisation of static energy meters under realistic low power quality conditions is a basic requirement for proper grid control and fair energy billing. The paper reports about a new proposed methodology, where the meters are tested under conditions directly recorded at installation sites. The waveforms of voltages and currents are sampled using a portable instrument; they are reproduced in laboratory conditions with a phantom power generator, with a bandwidth covering up to the 40th harmonic. The recording site is a photovoltaic energy production facility, having a a nominal power of 50 kW, at the coupling section to the grid. These waveforms were then reproduced in the laboratory, and tested on different models of single- and three-phase commercial static energy meters; the models chosen represent both energy meters used by energy providers at the point of common-coupling, and also meters typically used for in-line monitoring by end users. The quantity of interest is the reading error of the measured energy, when tested with the conditions reproduced from the on-field measurements, in comparison with a reference meter. All tested energy meter models comply with the present international documentary standards, which require tests under low power quality conditions; nevertheless, there are models that show unacceptable errors (up to 25%) in the measurement of active energy when tested with the on-field recorded waveforms. This suggests that the standardised testing waveforms might, in some cases, be not fully representative of the actual conditions encountered in the field. [ABSTRACT FROM AUTHOR]

Energy is one of the essential inputs for modernization and social development. Energy demand is increasing, and the primary energy source is fossil fuels, which negatively impact the environment. Energy saving and renewables are the potential solutions which could minimize environmental impact. This paper investigates the energy-saving and solar photovoltaic energy potential of an educational institution, Politeknik Sultan Azlan Shah (PSAS), Malaysia. The feasibility analysis was conducted by assuming that PSAS joined the Net Energy Metering (NEM 3.0) program, where PSAS, as a NEM consumer, has a tripartite supply agreement with renewable energy (SARE) with a distribution licensee known as Tenaga National Berhad (TNB). This paper focuses on zero capital expenditure (CAPEX) saving through a 20-year contract. This paper proposes a rooftop solar photovoltaic diagram using a NEM meter installed in the ring distribution system at PSAS. The estimated savings to be obtained by PSAS in the 20 years that the contract is in force are calculated based on the assumption that the installed solar system has a capacity of 688 kW. The maximum value of power generated by the system for a year is 990,720 kWh. The feasibility analysis found that the cumulative net savings estimate for PSAS based on the overall calculation for 21 years of solar use is RM 3,534,250. Meanwhile, the cumulative assessment of carbon emission reduction obtained in the same period is 14,559,760 kg CO2 or 14,559.76 tons of CO2, which would save 363,994 mature trees from being cut down. [ABSTRACT FROM AUTHOR]

Various metrological aspects for the correct measurements of electrical energy that is consumed by energy-saving (mainly LED) single phase loads are discussed in this paper. One of the most important problems presented here concerns the question of how strong distortions of the current waveform, introduced by typical LED lighting, affects the operation of electronic energy meters. Measurement results for the energy consumption of different LED lamps used in households in various conditions, alongside comparative results that were obtained by electronic and electromechanical energy meters, were also offered and the appropriate conclusions were then drawn. [ABSTRACT FROM AUTHOR]

This study aims to develop and evaluate an LSTM neural network for predicting household energy consumption. To conduct the experiment, a testbed was created consisting of five common appliances, namely, a TV, air conditioner, fan, computer, and lamp, each connected to individual smart meters within a Home Energy Management System (HEMS). Additionally, a meter was installed on the distribution board to measure total consumption. Real-time data were collected at 15-min intervals for 30 days in a residence that represented urban energy consumption in Sincelejo, Sucre, inhabited by four people. This setup enabled the capture of detailed and specific energy consumption data, facilitating data analysis and validating the system before large-scale implementation. Using the detailed power consumption information of these devices, an LSTM model was trained to identify temporal connections in power usage. Proper data preparation, including normalisation and feature selection, was essential for the success of the model. The results showed that the LSTM model was effective in predicting energy consumption, achieving a mean squared error (MSE) of 0.0169. This study emphasises the importance of continued research on preferred predictive models and identifies areas for future research, such as the integration of additional contextual data and the development of practical applications for residential energy management. Additionally, it demonstrates the potential of LSTM models in smart-home energy management and serves as a solid foundation for future research in this field. [ABSTRACT FROM AUTHOR]

Estimating line impedance is relevant in transmission and distribution networks, in particular for planning and control. The large number of deployed PMUs has fostered the use of passive indirect methods based on network model identification. Electrified railways are a particular example of a distribution network, with moving highly dynamic loads, that would benefit from line impedance information for energy efficiency and optimization purposes, but for which many of the methods used in industrial applications cannot be directly applied. The estimate is carried out onboard using a passive method in a single-point perspective, suitable for implementation with energy metering onboard equipment. A comparison of two methods is carried out based on the non-linear least mean squares (LMS) optimization of an over-determined system of equations and on the auto- and cross-spectra of the pantograph voltage and current. The methods are checked preliminarily with a simulated synthetic network, showing good accuracy, within 5%. They are then applied to measured data over a 20 min run over the Swiss  16.7  Hz railway network. Both methods are suitable to track network impedance in real time during the train journey; but with suitable checks on the significance of the pantograph current and on the values of the coefficient of determination, the LMS method seems more reliable with predictable behavior. [ABSTRACT FROM AUTHOR]

This effort to make the power grid more intelligent is tightly coupled with the deployment of advanced metering infrastructure (AMI) as an integral part of the future vision of smart grid. The goal of AMI is to provide necessary information for the consumers and utilities to accurately monitor and manage energy consumption and pricing in real time. Immediate benefits are enhanced transparency and efficiency of energy usage and the improvement of customer services. Although the road map toward successful AMI deployment is clearly defined, many challenges and issues are to be solved regarding the design of AMI. In this paper, a multi-agent AMI based on the fog-computing approach is presented. Architecture follows structural decomposition of AMI functionalities encapsulated in a form of local and area-specific service components that reside at the different tiers of hierarchically organized AMI deployment. Fog computing concepts provide the framework to effectively solve the problems of creating refined and scalable solutions capable of meeting the requirements of the AMI as a part of future smart grid. On the other hand, agent-based design enables concurrent execution of AMI operations across the distributed system architecture, in the same time improving performance of its execution and preserving the scalability of the AMI solution. The real-time performance of the proposed AMI solution, related to the periodic and on-demand acquisition of metering data from the connected electricity meters, was successfully verified during one year of pilot project operation. The detailed analysis of the performance of AMI operation regarding data collection, communication and data availability across the deployed pilot AMI, covering several transformer station areas with diverse grid topologies, is also presented. [ABSTRACT FROM AUTHOR]

In the electrical installations of buildings, there is an increasing number of non-linear energy receivers, which introduce strong distortions of the load current of electronic energy meters. Since the readings of these meters are the basis for financial settlements of electricity consumers, it is very important to determine how much the distortion of the receiver current affects the correct operation of commonly used electronic energy meters. The article will present exemplary results and analyses of research work on the impact of individual current harmonics on the readings and errors of selected energy meters. [ABSTRACT FROM AUTHOR]

The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes were collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data were collected, the variables available and the representativeness of the sample compared to national estimates. It is intended to be a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it. [ABSTRACT FROM AUTHOR]

Reducing office buildings' energy consumption can contribute significantly towards carbon reduction commitments since it represents ∼40% of total energy consumption. Major components of this are lighting, electrical equipment, heating, and central cooling systems. Solid evidence demonstrates that individual occupants' behaviors impact these energy consumption components. In this work, we propose the methodology of using virtual choreographies to identify and prioritize behavior-change interventions for office users based on the potential impact of specific behaviors on energy consumption. We studied the energy-related office behaviors of individuals by combining three sources of data: direct observations, electricity meters, and computer logs. Data show that there are behaviors with significant consumption impact but with little potential for behavioral change, while other behaviors have substantial potential for lowering energy consumption via behavioral change. [ABSTRACT FROM AUTHOR]

Mounting concerns pertaining to energy efficiency have led to the research of load monitoring. By Non-Intrusive Load Monitoring (NILM), detailed information regarding the electric energy consumed by each appliance per day or per hour can be formed. The accuracy of the previous residential load monitoring approach relies heavily on the data acquisition frequency of the energy meters. It brings high overall cost issues, and furthermore, the differentiating algorithm becomes much more complicated. Based on this, we proposed a novel non-Intrusive residential load disaggregation method that only depends on the regular data acquisition speed of active power measurements. Additionally, this approach brings some novelties to the traditionally used denoising Auto-Encoder (dAE), i.e., the reconfiguration of the overlapping parts of the sliding windows. The median filter is used for the data processing of the overlapping window. Two datasets, i.e., the Reference Energy Disaggregation Dataset (REDD) and TraceBase, are used for test and validation. By numerical testing of the real residential data, it proves that the proposed method is superior to the traditional Factorial Hidden Markov Model (FHMM)-based approach. Furthermore, the proposed method can be used for energy data, disaggregation disregarding the brand and model of each appliance. [ABSTRACT FROM AUTHOR]

Nowadays, the development, implementation and deployment of smart meters (SMs) is increasing in importance, and its expansion is exponential. The use of SMs in electrical engineering covers a multitude of applications ranging from real-time monitoring to the study of load profiles in homes. The use of wireless technologies has helped this development. Various problems arise in the implementation of SMs, such as coverage, locations without Internet access, etc. LoRa (long range) technology has great coverage and equipment with low power consumption that allows the installation of SMs in all types of locations, including those without Internet access. The objective of this research is to create an SM network under the LoRa specification that solves the problems presented by other wireless networks. For this purpose, a gateway for residential electricity metering networks using LoRa (GREMNL) and an electrical variable measuring device for households using LoRa (EVMDHL) have been created, which allow the development of SM networks with large coverage and low consumption. [ABSTRACT FROM AUTHOR]