ENERGY METERING DIGITALIZATION IN HOUSING AND UTILITIES SERVICES

2020 ◽  
pp. 96-100
Author(s):  
M. S. Agybayev ◽  
Z. S. Rakhimbekova
Keyword(s):  
Energy Metering ◽  
Utilities Services

scholarly journals Financial Impacts of Net-Metered Distributed PV on a Prototypical Western Utility’s Shareholders and Ratepayers

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4794 ◽  
Author(s):  
Peter Cappers ◽  
Andrew Satchwell ◽  
Will Gorman ◽  
Javier Reneses
Keyword(s):  
Capital Investment ◽  
Operating Conditions ◽  
Net Energy ◽  
Electricity Pricing ◽  
Operating Characteristics ◽  
Financial Model ◽  
Energy Metering ◽  
Percentage Basis ◽  
Financial Impacts ◽  
Net Energy Metering

Distributed solar photovoltaic (DPV) under net-energy metering with volumetric retail electricity pricing has raised concerns among utilities and regulators about adverse financial impacts for shareholders and ratepayers. Using a pro forma financial model, we estimate the financial impacts of different DPV deployment levels on a prototypical Western U.S. investor-owned utility under a varied set of operating conditions that would be expected to affect the value of DPV. Our results show that the financial impacts on shareholders and ratepayers increase as the level of DPV deployment increases, though the magnitude is small even at high DPV penetration levels. Even rather dramatic changes in DPV value result in modest changes to shareholder and ratepayer impacts, but the impacts on the former are greater than the latter (in percentage terms). The range of financial impacts are driven by differences in the amount of incremental capital investment that is deferred, as well as the amount of incremental distribution operating expenses that are incurred. While many of the impacts appear relatively small (on a percentage basis), they demonstrate how the magnitude of impacts depend critically on utility physical, financial, and operating characteristics.

Research the Test Method of the Voltage Transformer Secondary Load in the Three-Phase Three-Wire Electric Energy Metering Device

2014 ◽  
Vol 687-691 ◽  
pp. 3110-3115
Author(s):  
Gu Li ◽  
Zi Ming Fu ◽  
Jie Feng Yan ◽  
Bing Wen Li ◽  
Zhi Rong Cen
Keyword(s):  
Power Supply System ◽  
Electric Energy ◽  
Test Methods ◽  
Test Method ◽  
Testing Methods ◽  
Voltage Transformer ◽  
Secondary Load ◽  
Three Phase ◽  
Energy Metering ◽  
Definition Of

This paper analyzes and studies the definition of the voltage transformer secondary load, examines the practical purposes of the measured values of the voltage transformer secondary load, and presents a variety of testing methods to analyze and compare the differences. This paper gives the test methods of the voltage transformer secondary load when the connection of the voltage transformer is the Y / Y in a three-phase three-wire power supply system, filling the blank of this type of test method in the industry. When other units within the industry carry out such work, the conclusions of this paper are available for reference, and the conclusions of this paper can be referred when drafting relevant regulations in the future.

Research on Intelligent Power Management System Based on CAN Bus

2014 ◽  
Vol 539 ◽  
pp. 669-673
Author(s):  
Xie Hong
Keyword(s):  
Power Management ◽  
Management System ◽  
Can Bus ◽  
Electrical Power ◽  
Electricity Consumption ◽  
Power Measurement ◽  
Conversion Function ◽  
Management Level ◽  
Field Level ◽  
Energy Metering

This paper analyzes the actual situation of the electricity management about student apartments, and design intelligent energy student housing management system based on CAN bus. The system uses the field level, the underlying management level and upper management level three management systems. Field level with a dedicated energy metering chip AD7755 and STM32F103 microcontroller with A/D conversion function as the core, to achieve real-time power measurement; via CAN bus timing or random read live energy data for monitoring electricity consumption of the apartment, investigate abnormal electricity, thus effectively limiting the students to use electrical power to achieve the modernization and automation of power management solutions student apartments.

An Improved Residual Network for Electricity Power Meter Error Estimation

2019 ◽  
Vol 33 (08) ◽  
pp. 1959024
Author(s):  
Zichao Kou ◽  
Yanjun Fang
Keyword(s):  
Deep Learning ◽  
Error Estimation ◽  
Back Propagation ◽  
Electrical Energy ◽  
Residual Network ◽  
Propagation Process ◽  
Power Meter ◽  
Energy Metering ◽  
Electricity Power ◽  
Comparable Model

The lack of research on the metering characteristics of electricity power meters under complex conditions is a major obstacle to the on-site verification of electrical energy metering equipment. Establishing a predictive model for electricity power meter errors offers an effective way of dealing with this issue. Deep learning has been proven to have the capacity to reduce end-to-end dimensionality and improve recognition. Through the analysis of the back propagation process in residual networks, an improved residual network is set out in this paper. While preserving the advantages of residual network gradient propagation, it adds an adjustable shortcut and designs a convex [Formula: see text]-parameter strategy that can be improved according to different processing objects. Experimental results show that the predicted errors produced by the proposed technique are significantly lower than in a comparable model. At the same time, the improved residual network does not increase the network’s complexity.

Towards a Data Calibrated, Simulation-Based Campus Energy Analysis Environment for Situational Awareness and Future Energy System Planning

2014 ◽  
Author(s):  
Scott Duncan ◽  
Michael Balchanos ◽  
Woongje Sung ◽  
Juhyun Kim ◽  
Yongchang Li ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
Visual Analytics ◽  
Distribution Systems ◽  
Situational Awareness ◽  
Energy System ◽  
Integrated Analysis ◽  
Test Bed ◽  
Energy Metering ◽  
Campus Energy ◽  
Analysis Environment

Researchers at Georgia Tech (GT) have recently begun the GT Smart Energy Campus initiative, which combines campus energy metering data with physics-based modeling and simulation to create an integrated analysis environment for campus energy. The environment consists of a digital representation of campus, which supports situational awareness, as well as a virtual test bed for analyzing emerging energy technologies and future scenarios. The first year of the initiative has focused on evaluating campus energy metering data using visual analytics and statistical analysis techniques. Data analysis is presented as having value for two main uses: (1) as attention-directing information to help system operators diagnose anomalies and (2) as a precursor to modeling and simulation (M&S) in future phases of the Smart Energy Campus initiative. The environment is explained using the initial study scoping of the campus thermal energy generation and distribution systems. Furthermore, a modeling and simulation approach leveraging the Modelica M&S language is described, and preliminary results in using it to represent the campus chilled water system are presented.

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