Losses In Distribution Systems Research Articles

Analytical approach for allocation of energy losses in active distribution system using the method of energy summation

Analytical approach for allocation of energy losses in active distribution system using the method of energy summation

Artificial immune systems (GA-AIS) enabled power loss mitigation in distributed generation: X3PAIS optimization approaches

The distribution network is a crucial component of the power system, with industrialization driving increased energy demand. Traditional power-generating techniques, such as thermal and hydroelectric are not enough to meet this demand, leading to the development of Distributed Generation (DG). DG requires an extensive re-evaluation of the current power system, as it modifies energy losses and line flows. Inadequate integration of DG can cause power outages, disruption of protection coordination, and lead to islanding. AI can help overcome this issue by determining the best system architecture. Researchers have been interested in the Artificial Immune System (AIS) algorithm, which has room for development and lacks a fixed template. In order to improve AIS, X3PAIS, a hybridization strategy that combines clonal selection with a three-parent crossover has been developed within the scope of the study. X3PAIS was pre-tested using applications in a planetary gear train, a wastewater treatment facility, and mathematical calculations, showcasing its robustness and versatility. In the context of power distribution, X3PAIS is used in the multiple DG architecture of the power distribution system, reducing power losses by placing DG units in the best locations and sizing them to match load profiles. The four DGs' experiment results show that X3PAIS can minimize power losses by more than 89 %. To optimize power losses in the power distribution system, X3PAIS may be improved with a three-parent multiple-point crossover operation.

Electricity Theft Detection Using Rule-Based Machine Leaning (rML) Approach

Since electricity theft affects non-technical losses (NTLs) in power distribution systems, power companies are genuinely quite concerned about it. Power companies can use the information gathered by Advanced Metering Infrastructure (AMI) to create data-driven, machine learning-based approaches for Electricity Theft Detection (ETD) in order to solve this problem. The majority of data-driven methods for detecting power theft do take usage trends into account while doing their analyses. Even though consumption-based models have been applied extensively to the detection of power theft, it can be difficult to reliably identify theft instances based only on patterns of usage. In this paper, a novel rule-based combined machine learning (rML) technique is developed for power theft detection to address the drawbacks of systems that rely just on consumption patterns. This approach makes use of the load profiles of energy users to establish rules, identify the rule or rules that apply to certain situations, and classify the cases as either legitimate or fraudulent. The UEDAS smart business power consumption dataset's real-world data is used to assess the performance of the suggested technique. Our technique is an innovation in theft detection that combines years of intensive theft tracking with the use of rule-based systems as feature spaces for traditional machine learning models. With an astounding 93% recall rate for the rule-based feature space combination of the random forest classifier, this novel approach has produced outstanding results. The acquired results show a noteworthy accomplishment in the field of fraud detection, successfully detecting fraudulent consumers 77% of the time during on-site examination.

Efektivitas Mutasi Transformator Dalam Mengatasi Fluktuasi Beban Pada Trafo Distribusi ULP Bululawang

Transformer is a very important component in the distribution of electricity from the distribution substation to consumers. Overloading and underloading of transformers can lead to significant inefficiencies and increased losses in the electrical distribution system. Based on data measurement of the ULP Bululawang transformer in 2022, it was found that the C0177 transformer (100 KVA) was overloaded (88.4%) and the C0254 transformer (160 KVA) was underloaded (21.4%). Load forecasting for 2027 predicts that the C0177 transformer load will reach 107%, causing overheating, while the C0254 transformer will remain underloaded at 23.68%. To address these issues, a transformer mutation was proposed. This study aims to evaluate the effectiveness of transformer mutation in redistributing loads and improving efficiency. The method involved measuring transformer loads before and after mutation and using the Least Square method for load forecasting. Post-mutation measurements showed the C0177 transformer load reduced to 62.6% and the C0254 transformer load increased to 37%. These results indicate that the transformer mutation significantly balanced the load distribution. The study also adjusted the protection settings, including FCO, output cable, main switch, PHB-TR, and NH Fuse output cable. The findings suggest that transformer mutation can effectively address load imbalances, improve operational efficiency, and reduce power losses in the distribution system.

Comparison of Crow Search and Practice Swarm Algorithm for Minimization of Losses in Unbalanced Radial Distribution System

Comparison of Crow Search and Practice Swarm Algorithm for Minimization of Losses in Unbalanced Radial Distribution System

Reduction of Power Distribution System Losses by Using Novel Heuristic Algorithm

The Distribution Networks are the most widespread part of electrical power systems. Researcher has been trying to in the solutions to reduce high energy losses associated with them due to the low voltage level of the supply framework. Capacitors based techniques have been proposed to reduce these losses. These techniques minimize power losses, improve stability, and enhance the voltage profile of the distribution system under normal operating conditions. Finding optimal place and proper size of the capacitor is still a very hot area of research. In this research work, an innovative procedure based on the Archimedes optimization Algorithm (AOA) is presented to solve the optimal capacitor placement as well as sizing problem to improve the voltage profile and reduce the energy losses in the network. The suggested AOA based technique, is implemented on IEEE 33 bus network to find the optimal locations to place the capcitors in the distribution network. The performance of AOA is also compared with a standard model to verify the effectiveness of the scheme. By using AOA active power losses reduced upto 23.62% and reacrive losess by 21.86% respectively. The simulation results reveal that AOA based technique offer better results regarding the capacitor placement for voltage profile improvement of buses and significant reduction in active power losses as comapred to previous studies.

Dynamic Effects of a Regulating Valve in the Assessment of Water Leakages in Single Pipelines

Water losses in water distribution systems are typically analysed using extended period simulations, where its numerical resolution is commonly achieved using the gradient method. These models assume that adjustments to regulating valves occur, either manually or automatically, over an extended period of time, then the system inertia can be neglected. This research introduces the development of a rigid water column model for analysing water leakages in single pipelines, which can be employed to account for regulation valve adjustments in shorter time periods, thereby providing greater accuracy when assessing water losses. The application to a case study is presented to analyse pressure variations and leakage flow patterns over 30, 60, and 180 s. A comparison between the extended period simulation and rigid water column model is presented in order to note the order of magnitude on leakages when the system inertia is not considered. The results confirm that is crucial for water utilities the consideration of inertial system to simulate adequately opening and closure manoeuvres in water distribution systems, since according to the case study the extended period simulation can overestimated or underestimated the total leakage volume in percentages of 37.1 and 55.2 %\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}, respectively.

Optimal feeder routing and phase balancing for an unbalanced distribution system: a case study in Cambodia

This paper aims to minimize the distance of the feeder path from high-voltage/medium-voltage (HV/MV) substation to medium-voltage/low-voltage (MV/LV) transformers and minimize power loss in an unbalanced distribution system by the phase-swapping concept-based load balancing. The shortest path algorithm (SPA) and the genetic algorithm (GA) for optimal feeder routing and phase balancing separately in the MV unbalanced distribution network are proposed. First, the relevant data for the system is collected. These data include substation coordinates (X, Y), active and reactive power (P, Q), phase connections, and lines’ impedance (Z). secondly, the performance of the existing configuration of the test system with numerous indications is presented. Finally, the proposed method is performed to minimize the length and power losses. The real 47-bus test system in Cambodia is chosen to demonstrate the proposed method. In this study, overall power losses, the maximum voltage imbalance, and voltage regulation are computed by the backward/forward sweep load flow. The results based on the simulation indicate the importance of the proposed approach, especially for distribution system designers and operators.

Optimal capacitor bank placement and sizing using particle swarm optimization for power loss minimization in distribution network

This study delves into the issues concerning power quality in distribution systems, which commonly experience substantial losses, voltage fluctuations, and instability in bus voltages. More specifically, this paper centered on optimizing the Distribution Static Compensator (DSTATCOM) to tackle these challenges. To achieve this objective, we employ the Backward/Forward Sweep (BFS) method for load flow analysis and the Particle Swarm Optimization (PSO) algorithm to determine the ideal size and placement of the DSTATCOM. The study evaluates three different scenarios: the first scenario considers a 50-bus system without DSTATCOM, while the second and third scenarios incorporate the use of PSO to identify the optimal location and size of fixed and switched DSTATCOM. The aim is to reduce active and reactive power losses, enhance the voltage profile, and minimize system costs. The DSTATCOM integration significantly improved the distribution system by raising the minimum bus voltage from 0.817 p.u. to 0.95 p.u. Case 1 and Case 2 experienced notable reductions in active and reactive power losses, with percentages ranging from 58.72% to an impressive 96.69%. Economically, both cases demonstrated substantial net savings of 58.85% and 58.71%. The results demonstrate that employing PSO to allocate and size DSTATCOM can significantly decrease distribution system losses.

Analysis of Power and Voltage Losses in Electric Submersible Pump Motor Installations

In area mining are quite extreme, where the level of safety from high temperatures and toxic gases which are explosive as well as well flow pressure is also high and can damage production equipment. Therefore, it is very necessary to install reliable electrical power, starting from analyzing the selection of cable types that used, voltage drop, power losses and transformer selection. The problems mentioned previously, this research carried out an analysis of improvements to voltage drops and power losses that occurred in the ESP motor installation system. The method used is to replace the type of cable used in three scenarios with three different types of cable. The installation system data obtained from this company was then processed using software which was then validated with theoretical calculation results. The result of voltage drops and power losses in ESP cables according to standards using scenario 3, replacing AWG 2/0 type with a voltage rating of 5 kV, diameter of 11.709 mm and has a KHA of up to 210 A. The voltage drop value after repairs are carried out based on theoretical calculation results has an average percentage index value of 4.5% and power losses of 4.6%. This shows that in the condition after repairs, both the results of simulation calculations and theoretical values have met the IEEE std 141-1993 standard which states that the value of voltage drop and power losses in industrial plan distribution systems must be below 5%.

Dynamic optimisation of unbalanced distribution network management by model predictive control with Markov reward processes

In this work, a two-level control system is used to minimize the total active power losses of an active distribution system connected to the external grid and composed of a wind turbine, two photovoltaic power sources, and two batteries. At the first control level, a model-based predictive control (MPC) is run, using non-homogeneous Markov reward models for wind power prediction and homogeneous Markov reward models for photovoltaic power. At the second level, an algorithm is run for optimal management of voltage control assets, such as voltage regulating transformers, to minimize losses. Different scenarios have been considered, highlighting the advantages of using an MPC framework. This results in an optimization process that can be influenced by different time horizons depending on whether or not the MPC is applied. The predictions allow considering a long-horizon stepwise optimization process that leads to an increasing number of variables along with the decrease of total active power losses. When the MPC is not applied, a short-horizon analysis is performed with a decrease in both the number of variables and the quality of the results. Different cases are considered in which the nominal power of a photovoltaic unit and the battery capacity are modified.

Multiplexing Power Converters for Cost-Effective and Flexible Soft Open Points

The feasible set of real powers that can be transferred by a three-terminal Soft Open Point (SOP) can be increased by selecting non-uniform power ratings for each of the three ac/dc legs of the SOP, then connecting a multi-terminal switch (multiplexer) to the ac side of each of those converters to facilitate reconfiguration. This paper generalizes this concept, considering the real and reactive power that n multiplexed ac/dc converters can transfer at an m-feeder bus. The performance of the device is studied numerically for a number of ac/dc sizing strategies through the volume of the feasible set of power transfers (the `capability chart volume', CCV) and distribution system loss reduction benefits (as an exemplar network service). Upper bounds on device performance are defined by considering the performance of a novel, idealised SOP consisting of a continuum of infinitesimal reconfigurable converters. Results demonstrate that the CCV can be more than doubled, with 99% of the relative performance improvement of the idealised converter achieved with designs consisting of as few as four converters. SOP equipment costs reductions of 24% are reported, with it concluded that reconfigurable, judiciously sized ac/dc legs can yield flexible and lower cost SOPs than conventional, hard-wired approaches.

Leveraging Transfer Learning in LSTM Neural Networks for Data-Efficient Burst Detection in Water Distribution Systems

Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new sensor configuration for training. To overcome these issues, this study presents a novel approach based on Long Short-Term Memory neural networks (NNs) that leverages transfer learning to manage a varying number of sensors and retain good detection performance with limited training data. The proposed detection model first learns to reproduce the normal behavior of the system on a dataset obtained in burst-free conditions. The training process involves predicting flow and pressure one-time step ahead using historical data and time-related features as inputs. During testing, a post-prediction step flags potential bursts based on the comparison between the observations and model predictions using a time-varied error threshold. When adding new sensors, we implement transfer learning by replicating the weights of existing channels and then fine-tune the augmented NN. We evaluate the robustness of the methodology on simulated fire hydrant bursts and real-bursts in 10 district metered areas (DMAs) of the UK. For real bursts, we perform a sensitivity analysis to understand the impact of data resolution and error threshold on burst detection performance. The results obtained demonstrate that this ML-based methodology can achieve Precision of up to 98.1% in real-life settings and can identify bursts, even in data scarce conditions.

Overcurrent and ground fault relay protection settings at tranformator-1 150kV/20kV Braga substation

The occurrence of a malfunction at the substation results in power outages and losses in the electrical energy distribution system to consumers. Many tests are carried out to see the performance of the protection system, including the parameters of the over current relay (OCR) and ground fault relay (GFR) in the electrical energy distribution system. This research aims to analyze OCR and GFR values, analyze OCR setting, drop-off, and pick-up values, and analyze OCR time characteristics using DigSilent Power Factory 15.1 software based on existing equipment specification data at the Braga substation. The results show an OCR accuracy level of around 94% on the 20 kV and 150 kV sides. Meanwhile, 92.39% on the 20 kV GFR side and 94.87% on the 150 kV side. The setting value for the pick-up current is 0.92 A on the 20 kV side of the GFR and the drop-off current is 0.85 A on the 150 kV side with a pick-up current of 0.39 A and a drop-up current of 0.37 A. Setting a value on the 20kV side is greater than on the 150 kV side due to the difference in current transformer ratio values. The simulation results show that the OCR and GFR characteristic curves on both sides meet the criteria for a protection system with good performance.

Comparison of Optimal DG Placement Using GA, PSO and BA for Minimum Real Power Loss in Radial Distribution System

The below paper concentrates on the efficient integration of Renewable Energy Systems as Distributed Generators (DGs) within the distribution sector, aiming to minimize losses occurring from their presence in the system. To achieve this objective, the study proposes the strategic placing and sizing of DGs at optimal locations within the distribution network. To tackle this challenge, four heuristic search-based methods have been carefully selected and applied. The primary objectives of the paper are twofold: Firstly, it seeks to find the ideal location and sizing of DGs by loss minimization criteria. Secondly, the study aims to compare the performance of four chosen heuristic search-based methods TO achieve the loss reduction goals. By evaluating these methods' outcomes, researchers can identify the most effective method for DG placement and its sizing in the radial network. For the analysis, the IEEE 33 radial bus test system is utilized as a representative distribution system.

Improving estimation process of technical losses in electrical distribution system considering repairing periods

Recently, few studies were presented to include the effect of repairing periods in the estimation process of technical loss of either radial or ring medium voltage feeders in distribution networks. The previously presented studies are classified into traditional methods or using deduced formulas that need repeating the calculations many times with different operating conditions, i.e., normal operating periods (NOP) or repairing time (RT). The calculations using the previous methods seem to be repetitive and, furthermore, their equations parameters have to be calculated separately for each distribution network and/or for each loading level. In this paper, an improved formula is suggested to be applied for considering the effect of repairing periods when calculating technical energy losses (TELs). The improved formula includes a new term representing the ratio of repairing hours to the total operation periods. By applying the improved formula, there will be no need for repeating load flow calculations many times for each loading condition as in the previous studies. The proposed formula is validated through applying the improved formula for IEEE-16 bus distribution system. Electrical transient and analysis program (ETAP) version 12.6 was used for a load flow analysis of the case studies.

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits

In this research, a meta-heuristic-based hybrid algorithm was used to optimize the power dispatch of numerous Distributed Generators (DGs) in a Radial Distribution System (RDS) for hourly fluctuating seasonal loads in order to reduce losses and voltage variations while also saving money. With hourly seasonal load changes, renewable DGs like PV, Wind, and Hybrid (PV+Wind) were used. The HA is proposed in this paper as a way to achieve successful outcomes by merging two meta-heuristic algorithms. The findings of the HA are compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Shuffled Frog Leap Algorithm (SFLA), and Jaya Algorithm (JA) when they are applied to a standard IEEE 33 bus RDS and PG&E 69 bus RDS. According to the test findings simulated in the MATLAB environment, Hybrid Algorithm (HA) beat GA, PSO, SFLA, and JA in terms of optimal power dispatch of numerous DGs to minimise losses and voltage variations, as well as the cost-benefit analysis of renewable DGs energy generation.

Improvement of Power Quality in Primary Distribution Systems Based on Static-Var Compensators

A flexible AC Transmission Systems (FACTS) is a new technology offers a fast and reliable control over the transmission and distribution parameters like voltage and phase angle between the sending end voltage and receiving end voltage. Distribution static synchronous compensator (DSTATCOM) is a second generation member of the (FACTS) controllers. Reactive power compensation is an important aspect in the control of distribution systems. Reactive current in addition to increasing the distribution system losses, introduces voltage drop at lead point and finally it causes poor power quality in power systems. Primary radial distribution feeders have high resistance to reactance ratio, which causes voltage drop and high power loss in radial distribution systems. providing high demanding power to entire load while maintaining voltage magnitude at acceptable range is one of the major system constraints, using of capacitor banks to improve the reactive power have not quite enough at high reactive power feeder, because it have more slow in step by step response and have not capable to generate continuously variable reactive power. In some primary distribution feeders at the state of Khartoum, it is observed that there are some appropriate drops in voltage and quality service at high reactive power loads although some individual capacitor banks have been connected at these feeders, from here we researched for a new technology to overcome this problem. A steady-state model of (DSTATCOM) is proposed and developed to compensate the reactive power by using a Voltage Source Converter (VSC) with Pulse Width Modulation (PWM) and cascade control of four direct proportional integral controllers (PI) in synchronous reference frame. The detailed modeling and control design of (DSTATCOM) with specific typical radial primary distribution feeders (industrial, commercial, residential) are presented and implemented along necessary mathematical model equations in the Matlab software. Simulation schemes of (DSTATCOM) are done with help of control block diagrams and stability analysis. Load flow is an important method for analysis, operation and planning studies of any power system in a steady-state condition. In this research backward forward sweeps load flow method (Kirchhoff’s Laws) has been proposed rather than Newton-Raphson and Fast decoupled methods because the distribution feeders have a high R/X ratio which make the systems are ill-conditioned iterations analysis. (DSTATCOM) was installed on specific typical radial feeders at the (DSTATCOM) which using for distribution lines and load compensation has been the subject of considerable interest beside it is a new technology for a good power quality solution. Keywords: Power System, Flexible AC Transmission Systems (FACTS) Devices, STATCOM, PI Controller DOI: 10.7176/ISDE/13-1-05 Publication date: May 31 st 2023

Analyzing Power Losses in Ghazni City's Electricity Distribution Network and Strategies for Minimizing Them

Electricity is a vital source of energy that plays a crucial role in the economic and social development of a country. However, the distribution of electricity from power plants to consumers is a complex process that involves a network of electricity transmission and distribution systems. These systems are susceptible to losses that occur at various stages of the distribution process, such as transmission, conversion, and distribution. Power losses in distribution systems can be caused by technical and non-technical factors. Technical factors include conductor resistance, voltage drops, and transformer losses, while non-technical factors include theft and defective equipment. These losses can have significant economic consequences, such as lower reliability, higher costs, and lower revenues for utilities. Therefore, it is important to study and analyze the causes of power losses in distribution systems and develop strategies to reduce them. In this research, real field data of Ghazni Breshna Company was used to calculate electricity losses. In the case of Ghazni city electricity distribution network, the research shows that there is an energy loss of 11.7%, which amounts to 1,093,736 kWh per year. This energy loss results in a financial loss of 6,835,850 Afghanis for Barshna Company. The real field data obtained from Ghazni Breshna Company was used for the energy loss calculations. Several strategies can be used to reduce power losses, including reducing technical losses by improving equipment and maintenance practices, reducing non-technical losses by combating theft and illegal connections, and increasing the efficiency of the distribution network. In addition, improving energy management practices such as demand response, load balancing, and power factor correction can also help reduce power losses. Reducing power losses in the electric distribution system is critical to improving electric power reliability and quality and minimizing economic losses for utilities. In addition, high investment in this area can contribute to the growth of the nation's economy. The results of this study demonstrate the importance of understanding power losses in distribution systems and the need for effective measures to minimize these losses.

Weighted shapley value: A cooperative game theory for loss allocation in distribution systems

This paper proposes a new method for assigning distribution system (DS) losses to consumers and distributed generations in the framework of a liberalized energy market. The architecture of the proposed method is based on a synthesis of electrical network analytical theory and cooperative game theory (CGT). Weighted shapely value (WSV) is a solution idea that is regarded to be efficient in CGT for n-player games with characteristic function form. By retaining the notion of electrical networks, the axioms of game theory will be preserved while employing the WSV in loss allocation theory. To allocate system losses, the proposed method estimates the average marginal contribution of each participant to all conceivable coalitions and also determines the weight of the marginal contribution of each participant based on its power rating. Rather than a sequential branch-oriented approach, the proposed methodology is node-oriented. Additionally, a majority rule game is used to constrain the population of a coalition without jeopardizing the efficacy of the solutions to achieve a fair allocation of losses. The results of the proposed method are presented and contrasted with those obtained using the conventional pro-rata method and the well-known Shapley value solution concept in CGT.