Search

In filter based reactive power measurements, the voltage is phase shifted by 90 ∘ relative to the current. This paper presents a technique of measuring reactive power based on differential 90 ∘ shifter. According to this method, the sampled voltage and the current signal passes through a pair of FIR filters that shifts + 45 ∘ and - 45 ∘ . Then, the two outputs are multiplied to measure the reactive power. A pair of FIR filters that are having identical flat magnitude responses and orthogonal phase responses are designed. Multiplier-less FIR structure is adopted for hardware implementation to reduce the chip area cost making the technique implementable in digital power meter. A detailed hardware architecture and its implementation in FPGA is presented. Furthermore, the measurement of reactive power for various frequencies between 50 and 250 Hz is also presented. [ABSTRACT FROM AUTHOR]

Energy consumption is dependent on temperature, humidity, occupancy, occupant type, building area etc. All these factors collectively define the context of an energy meter. Once the context is known, the meters within the same context can be grouped and their behaviour can be analyzed together. This paper presents four heuristics, including one novel heuristic, to identify abnormal energy consumption. Using these heuristics, data collected from fifty smart meters deployed inside hostels of IIIT-Delhi was investigated for abnormal energy consumption detection. The anomalies and possible causes were discussed with IIIT-Delhi campus administrator. Energy consumption per occupant for one of the meters was found four times when compared to rest of the meters. The results demonstrated that the proposed heuristics successfully found abnormal energy consumption behaviour. [ABSTRACT FROM AUTHOR]

Smart meters are devices that provide detailed information about the energy consumed by specific electricity supply points, such as homes, offices, and businesses. Data from smart meters are useful for modeling energy systems, predicting electricity consumption, and understanding human behavior. We present the first smart meter dataset from Spanish electricity supply points, expanding the geographic diversity of available data on energy consumption at the household level and reducing biases in existing data, which typically come from a limited number of countries. The dataset consists of 25,559 raw hourly time series with an average length of nearly three years, spanning from November 2014 to June 2022. It also includes three subsets obtained by segmenting and cleaning the raw time series data, each focusing on the periods before, during, and after the COVID-19 lockdowns in Spain. This dataset is a valuable resource for studying electricity consumption patterns and behaviors that emerge in response to different natural experiments, such as nationwide and regional lockdowns, nighttime curfews, and changes in electricity pricing. [ABSTRACT FROM AUTHOR]

This article presents an efficient home energy management system for residential household within a microgrid. The smart meter's database initially stores the consumer's solar generation, battery's state of charge, and appliance-level information. Both the appliance's consumption and its state of operation are gathered. The end-user's energy use habits are then investigated using this data. As a consequence, accurate data on the frequency of usage, preferred operation interval, and average power consumption of the appliances were gathered using a time-of-day schedule. The outcomes were integrated with a Competitive Price Tracking algorithm to produce a smart home energy management solution that is efficient and user-focused. In addition to providing the optimum energy management strategy for a smart home in a microgrid, the developed model planned the controllable loads by taking into account consumer comfort and a separate waiting factor for each Appliances. The suggested model is demonstrated via simulation in the Typhoon HIL Real-Time Simulator. The operating cost recorded from the simulation is 155.08 INR, 150.56 INR, and 130.54 INR for case 1, 2, and 3, respectively. However, the proposed method is compared to other method, where operating cost from NILM-based method is recorded as 155.08 INR,153.12 INR, and 142.98 INR for case 1,2, and 3, respectively, and 151.38 INR for all cases, recorded from traditional Method. [ABSTRACT FROM AUTHOR]

In this research, the main objective is to design a smart meter to measure electricity consumption in households with communications based on long-range wide area network (LoRaWAN) wireless technology. Two devices have been designed, a smart meter for electrical energy in households (SMEEH) and a LoRa network supervisor (LNS), which optimises the LoRAWAN parameters using the teaching–learning-based optimisation (TLBO) algorithm. This algorithm allows obtaining the parameters' spreading factor, bandwidth, and code rate so that the minimum value of the packet loss rate (PLR) is reached, and the load profiles of the households are modelled in real time using cloud data storage. The algorithm implemented in the LNS determines the most appropriate parameters of the LoRaWAN by checking data traffic in real time. The household's electrical energy measuring system obtains data through sensors. Load profiles of households obtained by measuring the voltage, current, and active power with the SMEEH using the TLBO algorithm are more accurate. They allow the consumer and/or company to adjust the time and perform actions such as energy management and tariff adjustments. In addition, LoRaWAN optimisation means less data loss, more reliable load profiles, mean relative errors lower than 7.7%, and improved network performance. The TBLO algorithm uses short computation times to get the best solution for the LoRaWAN in real time and achieves a PLR of around 20% using the LNS. [ABSTRACT FROM AUTHOR]

A smart meter is a critical component of the smart grid that collects data and reports to electricity companies in several minutes or seconds. The real-time power consumption of smart meters helps electricity companies to provide reliable services but can expose smart meter customers' privacy. Therefore, aggregation of encrypted power consumption of smart meters is used to protect privacy. To meet the requirements, we propose a Privacy-Preserving Multidimensional Data Aggregation (PP-MDA) scheme for smart grid. Paillier cryptosystem is used to aggregate the encrypted power consumption at the fog and cloud sites. In addition to aggregation, PP-MDA scheme is also used for secure query processing; ID-based and time-based. Simulation results show the superiority of the PP-MDA scheme with existing solutions in terms of communication cost and features. [ABSTRACT FROM AUTHOR]

Energy smart meters have become very popular in monitoring and smart energy management applications. However, the acquired measurements except the energy consumption information may also carry information about the residents' daily routine, preferences and profile. In this article, we investigate the potential of extracting information from smart meters related to residents' security- and privacy-sensitive information. Specifically, using methodologies for load demand prediction, non-intrusive load monitoring and elastic matching, evaluation of extraction of information related to house occupancy, multimedia watching detection, socioeconomic and health profiling of residents was performed. The evaluation results showed that the aggregated energy consumption signals contain information related to residents' privacy and security, which can be extracted from the smart meter measurements. [ABSTRACT FROM AUTHOR]

The deployment of smart electricity meter (SEM) via the advanced metering infrastructure (AMI) has come under cyber-attacks as adversaries continue to exploit the communication links for possible evasion of electricity bill payments. Various detection models relying on energy consumption data offer a disadvantage of delayed detection and consequent huge financial losses before frauds are detected. Moreover, existing techniques mostly concentrate on detection of electricity thefts and rely on energy consumption data alone as the basis of theft perpetration whereas other potential parameters which could be exploited for electricity theft prevention exist in AMI. In this study, AMI parameters, which are indicative of electricity thefts are preselected and modelled for electricity theft prevention. First, a given AMI network is sectioned into zones with the selected parameters modelled to define security risks by formulated set of rules based on real-time scenarios. Fuzzy inference system is then employed to model the security risks to ascertain the compromised state of the monitored parameters at the defined scenarios. The result of the developed model at 50% weight of each of the modelled parameters with interdependencies show clear indications of the modelled parameters and their interactions in the determination of risks. The decisions on monitored parameters evaluated at every timestep reveal varied dense velocity behaviours for every scenario. The result is suitable for monitoring the AMI in reporting and/or disconnecting any compromised SEM within a considerable timestep before huge losses are incurred. Implementation of this scheme will contribute a significant success in the attempt to prevent electricity theft perpetration via the AMI. [ABSTRACT FROM AUTHOR]

The influence of distortions in voltage and current waveforms on state-of-the-art single-phase and three-phase power meters, commonly used in the utility power system of the Slovak Republic, was studied. A computer-controlled test system capable of generating nonsinusoidal voltages and currents and a reference power quality analyzer were used for this purpose. The results of the experiments on several revenue meters are presented. Some samples exhibited high errors under the tests, while the others operated within their tolerance limit. The overview of the current standards and previously published related studies on the operation of electric energy measuring equipment under determined and random nonsinusoidal conditions is given. The discussion including possible explanations of the phenomenon supervised under the conducted tests is provided. [ABSTRACT FROM AUTHOR]

A detailed analysis of the mathematical model of the adiabatic calorimeter is presented. An unsteady solution of the corresponding heat equation is presented and its features are considered. Two definitions of the response time of an adiabatic calorimeter operating, generally speaking, in a nonstationary mode are proposed. The question of determining the sensitivity of an adiabatic calorimeter is considered. Based on these definitions, a solution to the problem of the optimal choice of the material of the receiving plate in terms of the ratio of sensitivity and response time is proposed. Comparisons are made with some published experimental and theoretical results. The results obtained in this study can be used in the development and design of calorimetric systems for the diagnostics of beams of fast neutral particles. [ABSTRACT FROM AUTHOR]