scholarly journals Method to determine fact and place of commercial losses in distribution networks

Vestnik IGEU ◽  
2021 ◽  
pp. 18-29
Author(s):  
I.M. Kazymov ◽  
B.S. Kompaneets
Keyword(s):  
Low Voltage ◽  
Electrical Engineering ◽  
Distribution Networks ◽  
Measuring System ◽  
Power Networks ◽  
Rigorous Results ◽  
Medium Voltage ◽  
Electric Power Networks ◽  
Unique Method ◽  
Electrical Distribution Networks

The improvement of methods to register the commercial losses in electrical distribution networks, and especially in low voltage networks, is one of the most important tasks for power supply providers. It is rather difficult to correctly register the fact of occurrence of such losses in the network. It is objectively impossible to analyze the state of the networks based on data obtained from various points of the specified network with the required accuracy. In this regard, at present no methods have been developed for remote detection of the fact and determination of the place of commercial losses in distribution networks, that could work in the mode of integration with automated information-measuring system of fiscal electricity metering. To solve this problem a method is to be developed that allows us to establish accurately for practical purposes the volume of commercial losses in the network and determine the place of their occurrence. During the research, methods of electric power networks modeling have been used. The assumption has been made about no flow of capacitive leakage currents to ground in the network, about full compliance of the line parameters with their calculated (nominal) values, as well as the basic laws of electrical engineering science. A unique method is proposed to determine the fact and the place of commercial losses in distribution networks. In contrast to the prototypes, it is based on the analysis of data obtained from metering devices, based on the key laws of electrical engineering and it allows us to get reliable arithmetically rigorous results without using fuzzy logic. The authors have proved theoretically and practically the effectiveness of the proposed solutions, and the possibility of their application. A calculation has been made to determine the place of commercial losses in the network using an example. The proposed method to determine the fact and place of commercial losses in distribution networks of low and medium voltage levels solves the problem of inability to effectively identify the points of occurrence of commercial losses in distribution networks. The reliability of the results obtained is confirmed by mathematical rigor of the method and algorithmic nature of the procedure for analyzing the distribution network.

scholarly journals Machine Learning and GIS Approach for Electrical Load Assessment to Increase Distribution Networks Resilience

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4133
Author(s):  
Alessandro Bosisio ◽  
Matteo Moncecchi ◽  
Andrea Morotti ◽  
Marco Merlo
Keyword(s):  
Machine Learning ◽  
Distribution System ◽  
Low Voltage ◽  
Regression Tree ◽  
Distribution Networks ◽  
Machine Learning Algorithms ◽  
Extreme Weather Events ◽  
Medium Voltage ◽  
Weather Events ◽  
Building Area

Currently, distribution system operators (DSOs) are asked to operate distribution grids, managing the rise of the distributed generators (DGs), the rise of the load correlated to heat pump and e-mobility, etc. Nevertheless, they are asked to minimize investments in new sensors and telecommunication links and, consequently, several nodes of the grid are still not monitored and tele-controlled. At the same time, DSOs are asked to improve the network’s resilience, looking for a reduction in the frequency and impact of power outages caused by extreme weather events. The paper presents a machine learning GIS-based approach to estimate a secondary substation’s load profiles, even in those cases where monitoring sensors are not deployed. For this purpose, a large amount of data from different sources has been collected and integrated to describe secondary substation load profiles adequately. Based on real measurements of some secondary substations (medium-voltage to low-voltage interface) given by Unareti, the DSO of Milan, and georeferenced data gathered from open-source databases, unknown secondary substations load profiles are estimated. Three types of machine learning algorithms, regression tree, boosting, and random forest, as well as geographic information system (GIS) information, such as secondary substation locations, building area, types of occupants, etc., are considered to find the most effective approach.

scholarly journals Automatic Fault Localization and Isolation in Power Distribution Network by Decision Support Method

2021 ◽  
Vol 18 (4) ◽  
Author(s):  
Satya PRAKASH ◽  
Manoj HANS ◽  
Vikas THORAT
Keyword(s):  
Electricity Market ◽  
Power Distribution ◽  
Low Voltage ◽  
Distribution Network ◽  
Distribution Networks ◽  
Distribution Automation ◽  
Power Distribution Network ◽  
Medium Voltage ◽  
Time Observation ◽  
And Control

The power distribution network has grown complex and vulnerable as it increases its demand. The system's reliability has become a prominent factor for the end-users, although the continuity of supply in the distribution network still remains a challenge. In order to achieve the same distribution, automation came into the picture. The term “Distribution Automation” usually refers to an advanced switching system, which works as a subsystem of the existing network. The purpose of the subsystem is to offer real-time observation and control in distribution networks and electricity market operations. Consequently, the development of an autonomous system for isolating failures and restoring power for the distribution of LV (low voltage)/MV (medium voltage) can be an attractive solution for improving energy facilities' reliability. Advanced management techniques are devices and algorithms used to analyze, diagnose, and predict conditions in a distribution network, as well as to identify and take appropriate corrective actions to eliminate, mitigate, and prevent power outages and power quality problems. To demonstrate the model, we used a PIC16F877, CT microcontroller, and a power supply unit.

scholarly journals Hour-Ahead Energy Trading Management with Demand Forecasting in Microgrid Considering Power Flow Constraints

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3494
Author(s):  
Kuo Feng ◽  
Chunhua Liu ◽  
Zaixin Song
Keyword(s):  
Power Flow ◽  
Low Voltage ◽  
Supply And Demand ◽  
Demand Forecasting ◽  
Distribution Networks ◽  
Small Scale ◽  
Energy Trading ◽  
Medium Voltage ◽  
The Neural Network ◽  
Flow Constraints

Multiple small-scale low-voltage distribution networks with distributed generators can be connected in a radial pattern to form a multi-bus medium voltage microgrid. Additionally, each bus has an independent operator that can manage its power supply and demand. Since the microgrid operates in the market-oriented mode, the bus operators aim to maximize their own benefits and expect to protect their privacy. Accordingly, in this paper, a distributed hour-ahead energy trading management is proposed. First, the benefit optimization problem of the microgrid is solved, which is decomposed into the local benefit optimization sub problems of buses. Then, the local sub problems can be solved by the negotiation of operators with their neighbors. Additionally, the reference demand before negotiation is forecasted by the neural network rather than given in advance. Furthermore, the power flow constraints are considered to guarantee the operational stability. Meanwhile, the power loss minimization is considered in the objective function. Finally, the demonstration and simulation cases are given to validate the effectiveness of the proposed hour-ahead energy trading management.

OPERATIONAL ACTIVITIES FOR ACHIEVING ENERGY EFFICIENCY IN ELECTRICAL NETWORKS

2019 ◽  
pp. 268-273
Author(s):  
Stefka Nedelcheva ◽  
Mihaela Ivanova ◽  
Mehmed Hassan
Keyword(s):  
Energy Efficiency ◽  
Low Voltage ◽  
Electrical Power ◽  
Distribution Networks ◽  
Efficiency Improvement ◽  
Electrical Networks ◽  
Power Networks ◽  
Operational Conditions ◽  
Energy Efficiency Improvement ◽  
Operational Activities

The energy efficiency improvement actions of the electrical networks are divided into two main groups: operational and technical. Technical events require significant investment. Operating events do not require investment and are limited to optimal solutions in operational conditions that achieve energy efficiency. The report presents a methodology for assessing of the energy efficiency when changing the configuration of distribution electrical power networks. It is summarizing the results of the reconstruction and exploitation of the distribution networks for medium and low voltage under optimized schemes, which achieve energy efficiency. Recommendations are made for the implementation of energy efficiency activities in the exploitation of distribution networks.

scholarly journals A Three-Phase Weather-Dependent Power Flow Approach for 4-Wire Multi-Grounded Unbalanced Microgrids with Bare Overhead Conductors

2020 ◽  
Author(s):  
Evangelos Pompodakis
Keyword(s):  
Power Flow ◽  
Low Voltage ◽  
Flow Analysis ◽  
Single Layer ◽  
Distribution Networks ◽  
Medium Voltage ◽  
The Core ◽  
Magnetic Effects ◽  
Three Phase ◽  
The Impact

<p><b>Conventional power flow (CPF) algorithms assume that the network resistances and reactances remain constant regardless of the weather and loading conditions. Although the impact of the weather in power flow analysis has been recently investigated via the weather-dependent power flow (WDPF) approaches, the magnetic effects in the core of ACSR conductors have not been explicitly considered. ACSR conductors are widely used in distribution networks. Therefore, this manuscript proposes a three-phase weather-dependent power flow algorithm for 4-wire multi-grounded unbalanced microgrids (MGs), which takes into consideration the impact of weather as well as the magnetic effects in the core of ACSR conductors. It is shown that the magnetic effects in the core can significantly influence the power flow results, especially for networks composed of single-layer ACSR conductors. Furthermore, the proposed algorithm explicitly considers the multi-grounded neutral conductor, thus it can precisely simulate unbalanced low voltage (LV) and medium voltage (MV) networks. In addition, the proposed approach is generic and can be applied in both grid-connected and islanded networks. Simulations conducted in a 25-Bus unbalanced LV microgrid highlight the accuracy and benefit of the proposed approach. </b></p>

scholarly journals A Three-Phase Weather-Dependent Power Flow Approach for 4-Wire Multi-Grounded Unbalanced Microgrids with Bare Overhead Conductors

2020 ◽  
Author(s):  
Evangelos Pompodakis
Keyword(s):  
Power Flow ◽  
Low Voltage ◽  
Flow Analysis ◽  
Single Layer ◽  
Distribution Networks ◽  
Medium Voltage ◽  
The Core ◽  
Magnetic Effects ◽  
Three Phase ◽  
The Impact

<p><b>Conventional power flow (CPF) algorithms assume that the network resistances and reactances remain constant regardless of the weather and loading conditions. Although the impact of the weather in power flow analysis has been recently investigated via the weather-dependent power flow (WDPF) approaches, the magnetic effects in the core of ACSR conductors have not been explicitly considered. ACSR conductors are widely used in distribution networks. Therefore, this manuscript proposes a three-phase weather-dependent power flow algorithm for 4-wire multi-grounded unbalanced microgrids (MGs), which takes into consideration the impact of weather as well as the magnetic effects in the core of ACSR conductors. It is shown that the magnetic effects in the core can significantly influence the power flow results, especially for networks composed of single-layer ACSR conductors. Furthermore, the proposed algorithm explicitly considers the multi-grounded neutral conductor, thus it can precisely simulate unbalanced low voltage (LV) and medium voltage (MV) networks. In addition, the proposed approach is generic and can be applied in both grid-connected and islanded networks. Simulations conducted in a 25-Bus unbalanced LV microgrid highlight the accuracy and benefit of the proposed approach. </b></p>

scholarly journals A Multi-Stage Coordinated Volt-Var Optimization for Integrated and Unbalanced Radial Distribution Networks

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4877
Author(s):  
Xiangjing Su ◽  
Jining Liu ◽  
Shuxin Tian ◽  
Ping Ling ◽  
Yang Fu ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Low Voltage ◽  
Distribution Networks ◽  
Voltage Regulation ◽  
Load Flow ◽  
Medium Voltage ◽  
Modified Particle Swarm Optimization ◽  
Multi Stage ◽  
Network Operation ◽  
Radial Distribution Networks

The growing penetrations of rooftop photovoltaics (PVs) into low-voltage (LV) distribution networks are challenging voltage regulation. Developing an effective volt-var (VV) control has been the focus of many researchers with various approaches proposed so far. However, assuming a single voltage level and balanced network model, widely adopted in existing literatures, tends to cause inaccurate and even infeasible control solutions. Besides, existing distribution VV control studies are usually based on the day-ahead predictions of PV generations and loads, introducing inevitable and non-negligible errors. To address the challenges above, this paper proposes a VV co-optimization across unbalanced medium-voltage (MV) and LV networks, by traditional and emerging techniques, to ensure the network operation with the required power quality. Specifically, the operation of MV delta-connected switched capacitors and LV distributed PV inverters is coordinated, under a three-stage strategy that suits integrated and unbalanced radial distribution networks. The proposal aims to simultaneously improve voltage magnitude and balance profiles while reducing network power loss, at the least controlling cost. To effectively solve the proposed VV optimization problem, a joint solver of the modified particle swarm optimization and the improved direct load flow is employed. Finally, the proposal is evaluated by simulations on real Australian distribution networks over 24 h.

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