scholarly journals Efficient Energy Management for a Proposed Integrated Internet of Things-Electric Smart Meter (2IOT-ESM) System

2022 ◽  
Vol 28 (1) ◽  
pp. 108-121
Author(s):  
Maha Yousif Hasan ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Internet Of Things ◽  
Energy Management ◽  
Electrical Power ◽  
Electrical Energy ◽  
Smart Meter ◽  
Smart Meters ◽  
Efficient Energy ◽  
Working Together ◽  
Energy Theft ◽  
Internet Of Thing

In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurements are sent using the internet of thing (IoT) technology to Google Firebase cloud, where the electric consumer's service center is located to store, analyze the measured data, and detect cases of energy penetration when it exceeds 53  and the cases of the electrical energy theft if any below 20  and then take the appropriate decision about it. Finally, an electric smart metering application (ESM-app) is designed and implemented to read and pull data information from the Google firebase cloud and then send the electric bill to the end consumer, and sending alert messages to the thieves and electrical power hackers to prohibit them if something wrong has detected. In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurements are sent using the internet of thing (IoT) technology to Google Firebase cloud, where the electric consumer's service center is located to store, analyze the measured data, and detect cases of energy penetration when it exceeds 53  and the cases of the electrical energy theft if any below 20  and then take the appropriate decision about it. Finally, an electric smart metering application (ESM-app) is designed and implemented to read and pull data information from the Google firebase cloud and then send the electric bill to the end consumer, and sending alert messages to the thieves and electrical power hackers to prohibit them if something wrong has detected.

Enhanced RSA key encryption application for metering data in smart grid

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anita Philips ◽  
Jayakumar Jayaraj ◽  
Josh F.T. ◽  
Venkateshkumar P.
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Electrical Power ◽  
Prime Numbers ◽  
Combination Method ◽  
Smart Devices ◽  
Smart Meter ◽  
Content Type ◽  
Efficient Energy ◽  
Low Level

Purpose Digitizing of the electrical power grid promotes the advantages of efficient energy management alongside the possibilities of major vulnerabilities. A typical inadequacy that needs critical attention to ensure the seamless operation of the smart grid system remains in the data transmission between consumer premises smart devices and the utility centres. Many researches aim at establishing security protocols to ensure secure and efficient energy management resulting in perfect demand–supply balance. Design/methodology/approach In this paper, the authentication of the smart meter data has been proposed with enhanced Rivest–Shamir–Adleman (RSA) key encryption using an efficient way of generating large prime numbers. The trapdoor one-way function applied in the RSA algorithm makes it almost impossible for the reverse engineering attempts of cracking the key pair. Findings The algorithm for generating prime numbers has been tested both with the convention method and with the enhanced method of including a low-level primality test with a first few hundred primes. The combination of low-level and high-level primality tests shows an improvement in execution time of the algorithm. Originality/value There is a considerable improvement in the time complexities when using the combination method. This efficient generation of prime numbers can be successfully applied to the smart meter systems, thereby increasing the strength and speed of the key encryption.

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.

scholarly journals Smart metering system data analytics platform using multicore edge computing

2021 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Juan C. Olivares-Rojas ◽  
Enrique Reyes-Archundia ◽  
José A. Gutiérrez-Gnecchi ◽  
Ismael Molina-Moreno ◽  
Adriana C. Téllez-Anguiano ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Data Processing ◽  
Data Analytics ◽  
Electricity Consumption ◽  
Edge Computing ◽  
Smart Meter ◽  
Smart Metering ◽  
Smart Meters ◽  
System Data

The smart grid revolution has only been possible, thanks to the development and proliferation of smart meters. The increasingly growing computing capabilities for Internet of Things devices have made it possible for data to be processed directly from the devices where it is produced; this has been called edge computing. Edge computing is allowing the smart grid to become increasingly intelligent to solve problems that make electricity consumption more efficient and environmentally friendly. This work presents the implementation of a smart metering system that allows data analytics using a multiprocessing architecture directly on the smart meter. The results show that the development of smart meters with data analytics capabilities at the edge is a reality today, and the use of multiprocessing permits the improvement of data processing.

scholarly journals Application of Spritz Encryption in Smart Meters to Protect Consumer Data

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Lincoln Kamau Kiarie ◽  
Philip Kibet Langat ◽  
Christopher Maina Muriithi
Keyword(s):  
Smart Grid ◽  
Electrical Power ◽  
Cyber Attacks ◽  
Smart Meter ◽  
Electrical Power System ◽  
Smart Meters ◽  
Planning And Control ◽  
Privacy Leakage ◽  
Consumer Data ◽  
And Control

The ongoing upgrade of the electrical power system into a more powerful system known as Smart Grid has both benefits and costs. Smart Grid relies on advanced communication and hence offers better services through improved monitoring, planning, and control. However, enhanced communications make Smart Grid more susceptible to privacy leaks and cyber attacks. Small meters collect detailed consumer data, such as power consumption, which can then become a major source of privacy leakage. Encryption can help protect consumer data, but great care is needed. The popular RC4 (Rivest Cipher 4) encryption has been implemented in the widely deployed smart meter standard—Open Smart Grid Protocol (OSGP)—but has been shown to have major weaknesses. This paper proposes the use of Spritz encryption. Spritz is an RC4-like algorithm designed to repair weak design decisions in RC4 to improve security. A test on performing one encryption took only 0.85 milliseconds, showing that it is fast enough not to affect the operations of a smart meter. Its ability to withstand brute force attacks on small keys is also significantly greater than RC4’s ability.

scholarly journals Study of Energy Management and Audit

2020 ◽  
pp. 146-152
Author(s):  
G. Joga Rao ◽  
K. Pavan Srihari
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Electrical Energy ◽  
Management Program ◽  
Energy Audit ◽  
Energy Auditing ◽  
Current Scenario ◽  
Residential House ◽  
The Government

The economic development of a country is often closely linked to its consumption of energy. The government has taken new steps for the development of renewable energy sources and less consideration in conservation of electrical energy in the society. According to the current scenario the demand of energy has increased and became a routine process in our lifestyle. Why electrical auditing and management is essential? Energy audit is the survey of wastage power in different areas like domestic houses, commercial buildings and industries etc. For getting solution to save electrical energy, energy auditing is best way. So we found in India the demand of electrical power rises at the rate of 9-10 % per annum while the generation of electrical power rises at the rate of 5-6 % per annum, ultimately the gap between demand and generation of electrical power is widening at the rate of 3-4 % per annum. Electrical energy auditing and management program can have an originating within one division of saving, motivating people in all forms to undergo conservation activities. In this project we had done the Energy audit in residential house.

scholarly journals Pendekatan Implementasi Model Substractive Clustering Dalam Memetakan Dan Klasifikasi Data Perilaku Konsumen Listrik Tegangan Rendah Studi Kasus : Pelanggan PT PLN (Persero) UP3 Cengkareng

Petir ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 251-261
Author(s):  
Yozika Arvio ◽  
Iriansyah BM Sangadji ◽  
Hengki Sikumbang ◽  
Meilinda Devi Anjarwati
Keyword(s):  
Electrical Energy ◽  
Energy Management System ◽  
Smart Meter ◽  
Smart Meters ◽  
Human Needs ◽  
Electricity Rates ◽  
Usage Patterns ◽  
Infrastructure System ◽  
Measurement Infrastructure ◽  
Major Consideration

Electrical energy is one of the most important and vital human needs that cannot be released from daily needs. Customers also have begun to be critical of the purchase costs that must be paid every month. So by increasing electricity rates, improving efficiency in the use of electric power is a major consideration. The Advanced Measurement Infrastructure System (AMI) provides information on the use of granular energy for needs and customers. The IT system at AMI one of which uses EMS (Energy Management System) is an application to collect data from every smart meter installed in the customer, to store it in a database, and to connect the analysis and statistics of the data stored below. In this study aims to provide an analysis of electricity usage patterns by implementing AMI / Smart meters PT. PLN (Persero) by conducting a cluster of 1 phase and 3 phase electricity usage in customers of PT PLN (Persero) UP3 Cengkareng, namely the distribution booths DK60, TG70 and DK242 for 4 months, from November 2018 to February 2019. From the results of the study sought for customers 1 phase DK 60 with a radius of 0.5 produces 1 cluster that is stable every month depending on the customer at this substation is a household class customer, TG 70 requires stable and spending usage in December 2018, and DK 242 fix stable and use customers in the month December 2018 and January 2019, while for 3-phase DK 60 customers tend to be unstable because the customers of this apartment are different, starting from shops, production sites, and CV. TG 70 substations are predominantly places of worship, namely mosques and mosques, so the average use of mosques is higher, and for DK 242 3-phase customers need to be stable and use the highest in January 2019.AMI, System, EMS, Distribution Substation, Phase.

scholarly journals Advanced energy management system with the incorporation of novel security features

2020 ◽  
Vol 10 (4) ◽  
pp. 3978
Author(s):  
Raheel Muzzammel ◽  
Rabia Arshad ◽  
Saba Mehmood ◽  
Danista Khan
Keyword(s):  
Power Systems ◽  
Energy Management ◽  
Management System ◽  
Nuclear Power ◽  
Industrial Development ◽  
Fossil Fuels ◽  
Electrical Power ◽  
Centralized Control ◽  
Renewable Energy Resources ◽  
Energy Theft

Nowadays, energy management is a subject of great importance and complexity. Pakistan, being in a state of developing country, generates electrical power mainly by using non-renewable sources of energy. Non-renewable entities are fossil fuels such as furnace oil, natural gas, coal, and nuclear power. Pakistan has been facing a severe shortage of production in energy sector for last two decades. This shortfall is affecting the industrial development as well as economic growth. With the growing population, the load demand is rapidly increasing and there must be a need to expand the existing ones or to build new power systems. In this paper, an autonomous management system has been proposed to enhance quality, reliability and confidence of utilization of energy between end consumers and suppliers. Such objectives can only be fulfilled by making the power supply secure for end consumers. Distributed and centralized control systems are involved for maintaining a balance between renewable energy resources and base power, so that end consumers demand can be fulfilled when required. A reliable Two-way communication system between suppliers and end consumers has been proposed by using Message Digest algorithm which ensures that there would be no energy theft. Simulations have been done in MATLAB/ Simulink environment and results have been presented to show the effectiveness of the proposed model.

Efficient Energy Management for the Internet of Things in Smart Cities

2017 ◽  
Vol 55 (1) ◽  
pp. 84-91 ◽  
Author(s):  
Waleed Ejaz ◽  
Muhammad Naeem ◽  
Adnan Shahid ◽  
Alagan Anpalagan ◽  
Minho Jo
Keyword(s):  
Internet Of Things ◽  
Energy Management ◽  
Smart Cities ◽  
The Internet ◽  
Efficient Energy ◽  
The Internet Of Things

scholarly journals A Novel Accurate and Fast Converging Deep Learning-Based Model for Electrical Energy Consumption Forecasting in a Smart Grid

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2244 ◽  
Author(s):  
Ghulam Hafeez ◽  
Khurram Saleem Alimgeer ◽  
Zahid Wadud ◽  
Zeeshan Shafiq ◽  
Mohammad Usman Ali Khan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Energy Consumption ◽  
Convergence Rate ◽  
Smart Grid ◽  
Energy Management ◽  
Electrical Energy ◽  
Features Selection ◽  
Electrical Energy Consumption ◽  
Efficient Energy ◽  
Proposed Model

Energy consumption forecasting is of prime importance for the restructured environment of energy management in the electricity market. Accurate energy consumption forecasting is essential for efficient energy management in the smart grid (SG); however, the energy consumption pattern is non-linear with a high level of uncertainty and volatility. Forecasting such complex patterns requires accurate and fast forecasting models. In this paper, a novel hybrid electrical energy consumption forecasting model is proposed based on a deep learning model known as factored conditional restricted Boltzmann machine (FCRBM). The deep learning-based FCRBM model uses a rectified linear unit (ReLU) activation function and a multivariate autoregressive technique for the network training. The proposed model predicts future electrical energy consumption for efficient energy management in the SG. The proposed model is a novel hybrid model comprising four modules: (i) data processing and features selection module, (ii) deep learning-based FCRBM forecasting module, (iii) genetic wind driven optimization (GWDO) algorithm-based optimization module, and (iv) utilization module. The proposed hybrid model, called FS-FCRBM-GWDO, is tested and evaluated on real power grid data of USA in terms of four performance metrics: mean absolute percentage deviation (MAPD), variance, correlation coefficient, and convergence rate. Simulation results validate that the proposed hybrid FS-FCRBM-GWDO model has superior performance than existing models such as accurate fast converging short-term load forecasting (AFC-STLF) model, mutual information-modified enhanced differential evolution algorithm-artificial neural network (MI-mEDE-ANN)-based model, features selection-ANN (FS-ANN)-based model, and Bi-level model, in terms of forecast accuracy and convergence rate.

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