scholarly journals Energy Losses Estimation in Low Voltage Smart Grids by using Loss Maps

2019 ◽  
pp. 247-258
Author(s):  
Jose Angel Velasco ◽  
Keyword(s):  
Smart Grids ◽  
Low Voltage ◽  
Energy Losses

scholarly journals Time Synchronized Low-voltage Measurements for Smart Grids

2015 ◽  
Vol 100 ◽  
pp. 1389-1395 ◽  
Author(s):  
Ladislav Stastny ◽  
Lesek Franek ◽  
Zdenek Bradac
Keyword(s):  
Smart Grids ◽  
Low Voltage

An integrated low-voltage rated HTS DC power system with multifunctions to suit smart grids

2015 ◽  
Vol 510 ◽  
pp. 48-53 ◽  
Author(s):  
Jian Xun Jin ◽  
Xiao Yuan Chen ◽  
Ronghai Qu ◽  
Hai Yang Fang ◽  
Ying Xin
Keyword(s):  
Power System ◽  
Smart Grids ◽  
Low Voltage ◽  
Dc Power

scholarly journals Calculations, norming and reducing of electrical energy losses in city electrical networks

2019 ◽  
Vol 21 (3) ◽  
pp. 46-54
Author(s):  
A. V. Lykin ◽  
E. A. Utkin
Keyword(s):  
High Voltage ◽  
Power Transmission ◽  
Low Voltage ◽  
Demand Curve ◽  
Electrical Energy ◽  
Electrical Network ◽  
Energy Losses ◽  
Capital Investments ◽  
Electrical Networks

The article considers the feasibility of changing the structure of a distribution electrical network by transferring points of electricity transformation as close to consumers as possible. This approach is based on installation of pole-mounted transformer substations (PMTS) near consumer groups and changes the topology of the electrical network. At the same time, for groups of consumers, the configuration of sections of the low-voltage network, including service drops, changes. The efficiency of approaching transformer substations to consumers was estimated by the reduction in electrical energy losses due to the expansion of the high-voltage network. The calculation of electrical losses was carried out according to twenty-four hour consumer demand curve. To estimate the power losses in each section of the electrical network of high and low voltage, the calculated expressions were obtained. For the considered example, the electrical energy losses in the whole network with a modified topology is reduced by about two times, while in a high-voltage network with the same transmitted power, the losses are reduced to a practically insignificant level, and in installed PMTS transformers they increase mainly due to the rise in total idle losses. The payback period of additional capital investments in option with modified topology will be significantly greater if payback is assessed only by saving losses cost. Consequently, the determination of the feasibility of applying this approach should be carried out taking into account such factors as increasing the reliability of electricity supply, improving the quality of electricity, and increasing the power transmission capacity of the main part of electrical network.

scholarly journals A Methodology for Dependability Evaluation of Smart Grids

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1817 ◽  
Author(s):  
Gisliany Alves ◽  
Danielle Marques ◽  
Ivanovitch Silva ◽  
Luiz Affonso Guedes ◽  
Maria da Guia da Silva
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Information And Communication Technologies ◽  
Power Distribution ◽  
Smart Grids ◽  
Low Voltage ◽  
Hierarchical Topology ◽  
Automation Systems ◽  
Dependability Evaluation ◽  
Information And Communication

Smart grids are a new trend in electric power distribution, which has been guiding the digitization of electric ecosystems. These smart networks are continually being introduced in order to improve the dependability (reliability, availability) and efficiency of power grid systems. However, smart grids are often complex, composed of heterogeneous components (intelligent automation systems, Information and Communication Technologies (ICT) control systems, power systems, smart metering systems, and others). Additionally, they are organized under a hierarchical topology infrastructure demanded by priority-based services, resulting in a costly modeling and evaluation of their dependability requirements. This work explores smart grid modeling as a graph in order to propose a methodology for dependability evaluation. The methodology is based on Fault Tree formalism, where the top event is generated automatically and encompasses the hierarchical infrastructure, redundant features, load priorities, and failure and repair distribution rates of all components of a smart grid. The methodology is suitable to be applied in early design stages, making possible to evaluate instantaneous and average measurements of reliability and availability, as well as to identify eventual critical regions and components of smart grid. The study of a specific use-case of low-voltage distribution network is used for validation purposes.

scholarly journals Incremental Heuristic Approach for Meter Placement in Radial Distribution Systems

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3917 ◽  
Author(s):  
Giovanni Artale ◽  
Antonio Cataliotti ◽  
Valentina Cosentino ◽  
Dario Di Cara ◽  
Salvatore Guaiana ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Power Distribution ◽  
Smart Grids ◽  
Distribution Systems ◽  
Low Voltage ◽  
Distribution Network ◽  
Load Flow ◽  
State Variables ◽  
Medium Voltage ◽  
Meter Placement

The evolution of modern power distribution systems into smart grids requires the development of dedicated state estimation (SE) algorithms for real-time identification of the overall system state variables. This paper proposes a strategy to evaluate the minimum number and best position of power injection meters in radial distribution systems for SE purposes. Measurement points are identified with the aim of reducing uncertainty in branch power flow estimations. An incremental heuristic meter placement (IHMP) approach is proposed to select the locations and total number of power measurements. The meter placement procedure was implemented for a backward/forward load flow algorithm proposed by the authors, which allows the evaluation of medium-voltage power flows starting from low-voltage load measurements. This allows the reduction of the overall costs of measurement equipment and setup. The IHMP method was tested in the real 25-bus medium-voltage (MV) radial distribution network of the Island of Ustica (Mediterranean Sea). The proposed method is useful both for finding the best measurement configuration in a new distribution network and also for implementing an incremental enhancement of an existing measurement configuration, reaching a good tradeoff between instrumentation costs and measurement uncertainty.

scholarly journals An Analysis of the Systematic Error of a Remote Method for a Wattmeter Adjustment Gain Estimation in Smart Grids

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 37 ◽  
Author(s):  
Robertas Lukočius ◽  
Žilvinas Nakutis ◽  
Vytautas Daunoras ◽  
Ramūnas Deltuva ◽  
Pranas Kuzas ◽  
...  
Keyword(s):  
Systematic Error ◽  
Power Factor ◽  
Smart Grids ◽  
Low Voltage ◽  
Voltage Drop ◽  
Estimation Method ◽  
Data Communication ◽  
Pattern Search ◽  
Error Monitoring ◽  
Worst Case

Smart energy meters supporting bidirectional data communication enable novel remote error monitoring applications. This research targets characterization of the systematic worst-case error of the previously published remote watthour meter’s gain estimation method based on the comparison of synchronous measurements by the reference and meter under test. To achieve the research aim a methodology based on global maximization of the systematic error objective function assuming the typical low voltage electrical distribution network operation parameters ranges as defined by the standard recommendations for network design. To cross verify the reliability of the assessed solutions the suggested error analysis methodology was implemented utilizing two stochastic global extremum search techniques (genetic algorithms, pattern search) and the third one utilizing nonlinear programming solver. It was determined that the wattmeter adjustment gain worst-case error does not exceed 0.5% if the remote wattmeter monitored load power factor is larger than 0.1 and a network is designed according to the recommendation of the acceptable voltage drop less than 5%. For a load exhibiting power factor larger than cos φ = 0.9 the worst-case error was found to be less than 0.1%. It is concluded therefore that considering the systematic worst-case error the previously suggested remote wattmeter adjustment gain estimation method is suitable for remote error monitoring of Class 2 and Class 1 wattmeters.

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