Distribution Network Losses Research Articles

Enhancing efficiency in electrical distribution systems: A novel approach via modified genetic optimization algorithm for loss reduction in optimal network distribution

The distribution system plays a pivotal role in connecting power generation sources to vital facilities like nuclear reactors. In this intricate network, losses occur while supplying electricity, demanding a reduction for enhanced performance. The quality of power reaching the nuclear plant is imperative due to the susceptibility of sensitive equipment to poor power conditions. This study presents a reconfiguration strategy to bolster dependability and curtail power losses in distribution networks. Leveraging the Modified Genetic Optimization Algorithm (MGOA), the reconfiguration conundrum is tactfully addressed to determine optimal switch operation schemes. The MGOA-based reconfiguration not only minimizes energy wastage but also refines voltage profiles, elevating operational efficiency. The effectiveness of this approach is substantiated through its successful application to radial distribution systems comprising 33, 69, and 136 buses. Embracing diverse scenarios encompassing normal and abnormal operating states, as well as varying loads, the method’s robustness is showcased. The validity of the proposed methodology is reinforced by comprehensive simulation results, underscoring its reliability and potential for real-world implementation.

Reduction of medium voltage distribution network losses through the reactive power generation in PV systems

With inevitable increase in numbers of distributed generation units connected within the distribution network (DN), different aspects of their impact on DN operation must be evaluated. This paper deals with the problem of reactive power generation from photovoltaic (PV) systems, connected to the DN, and technical and economic benefits that can be achieved on DN operation with its optimal generation. Detailed consideration of four existing medium voltage DNs with their time-dependent loading and PV generation profiles, allowed the evaluation of annual losses of electric energy, for different scenarios of reactive power generation. Furthermore, the resulting financial savings were assessed as well. Results show that with reactive power generation from installed PV units, meeting the actual needs of the network, losses can be significantly reduced and financial savings achieved.

Allocation of power losses and energy in the distribution network

The goal is to determine methods for calculating power losses in a three-phase four-wire low voltage distribution network using measurements of a balance smart meter and consumer smart meters, and to establish the factors influencing the power losses and their allocation among individual network wires, loads, and consumers. The study involved examining three methods for determining power losses for current measurement snapshot. The first method suggests calculating losses as the difference between the power supplied to the network and the total power consumed. The second method calculates power losses using the contribution method. The third method, which in addition to measurement information requires knowledge of the topology and parameters of the network components, determines power losses based on the results of the state estimation method. The research proposes an algorithm for transition from a four-wire distribution network modeling to a three-wire one. The algorithm allocates power losses of the neutral wire among the phase wires. The findings indicate that the negative losses in the network with unbalanced phase loads are caused by the presence at the nodes of the least loaded phase of higher voltage than the voltage at the power supply node. The reason for higher losses in phases with minimal load is the uneven allocation of loads in the phases. In addition, the study reveals that the power loss values obtained by the contribution method, i.e. directly from the measurements of smart meters, are closer to the losses determined from the readings of the balance meter and consumer meters, compared to the losses found from the state estimation results. The considered methods for calculation and allocation of power losses are illustrated by an example of a real-world distribution network equipped with smart meters. The paper demonstrates the examples of allocating total power losses between phase wires and a neutral wire, among phase wires only, and between total loads at phase nodes and individual consumers in phases.

Performance of the distribution network by connecting solar and wind DGs

The operation of the distribution network (DN) is difficult due to the voltage stability when connecting multiple distributed generations. This paper explains the performance of a distribution network by connecting solar and wind Distributed Generation (DG). The distribution network is stable when the voltages are within the boundary limits. The voltage boundary limits are 0.95< 1 < 1.05 per unit. The voltages and power loss of the IEEE-85 and 25 bus radial distribution networks are evaluated by connecting Solar Distributed Generation (SDG) with variable power supply due to changes in the irradiation of solar panels. The voltages and power loss of the IEEE-85 bus distribution network are evaluated by connecting Wind-Distributed Generation (WDG) with variable power supply due to wind speed changes, and voltages and power loss are evaluated with load changes in the presence of WDG. By connecting both solar and wind-distributed generations, the voltages and power loss of the IEEE-85 bus DN are evaluated. The Multi-Objective Slime Mould Algorithm (MOSMA) is used to connect solar and wind DGs at optimal locations and sizes in the DN. The MOSMA has been applied to the IEEE-85 bus and 25 bus DN in MATLAB.

High penetration PV active distribution network power flow optimization and loss reduction based on flexible interconnection technology

High penetration PV active distribution network power flow optimization and loss reduction based on flexible interconnection technology

Direct Load Control Scheme for Flexible Loads under Automated Demand Response Program for Peak Demand Management, Loss Minimization, Asset Management, and Sustainable Development

Background: Nowadays implementation of Demand Response (DR) programs in the distribution grid is a necessary planning criterion for distribution utility. Implemented DR programs should be automated, intelligent, well-educated, and more competent than the conventional augmentation techniques to resolve Distribution Network (DN) constraints. Peak demand causes DN to approach its maximum capacities. Peak demand also exceeds the sustainable limit of the DN resulting disruption in electric supply, failures of various assets like transformers, feeders, etc. Objective: In this paper, a Direct Load Control (DLC) scheme for Flexible Loads (FLs) is modeled &amp; implemented under Automated Demand Response (ADR) program and tested on real 54-bus DN. Methods: This ADR program is implemented through Demand Response Aggregator (DRA) and ADR Technology Solution Enablers (ADRTSE) to curtail the peak demand on the DN ADR is a recent technology that may put off new generation (conventional- and non-conventional both). Results: It also enables the distribution utility to curtail the peak demand &amp; its period ensuring reliability of supply without restructuring, augmentation of existing infrastructure, and development of new infrastructure. Conclusion: The result validates the effectiveness of ADR program for peak demand curtailment, asset management, distribution network losses minimization, and for sustainable development of environment.

Construction and Optimization of Dynamic Assessment Indicators for Distribution Grid Carrying Capacity with High Proportion of Distributed Resource Connections

Abstract In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation employs a fuzzy comprehensive evaluation (FCE) method, wherein we construct FCE indices for factors influencing the distribution network’s carrying capacity. These indices involve calculating weight coefficients and establishing an affiliation function, culminating in the output of the final fuzzy evaluation result vector. The analysis identifies three nodes—11, 18, and 31—within the IEEE 33-node system for decentralized DR installation. Based on initial scenario data, the maximum carrying capacity of the distribution network is determined to be 40.68 MW. The analysis further reveals that the utilization rate of distributed resources reaches 100% at specific times, specifically at 2:00 AM and 6:00 AM. During the 3:00 to 5:00 AM interval, both the system voltage excursion index and the composite score for distribution network losses are calculated to be low. These findings suggest the feasibility of integrating a single regional distribution network with other energy networks, thereby facilitating multi-regional resource interconnection and enhancing the flexibility of system operations. This approach offers significant implications for improving the robustness and efficiency of electrical distribution systems.

Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks

The objective of the presented paper is to verify economically justified levels of reactive energy compensation in the distribution network in the new market conditions, including the extensive use of smart metering systems, new types of load, or distributed generation. The proposed methodology is based on the minimization of annual costs of losses caused by the flow of reactive energy to the supplied loads through the equivalent resistance of the distribution system determined on the basis of statistical energy losses in this network. The costs of losses are compared to the costs of using compensating devices expressed by the levelized costs of reactive energy generation. The results are the relations describing the optimal annual average value of the tgφ factor to be maintained by customers to optimize the cost of loss of the distribution network caused by reactive energy flows. The dependence of the optimal tgφ value on the analyzed load and network parameters is also discussed. The resulting optimal tgφ levels should be considered in the tariffication process of services offered by distribution system operators to improve capacity and limit the costs of power network operation due to reactive energy transmission.

Analisis Ketidakstabilan Beban Arus Netral dan Rugi-Rugi Daya Pada Trafo Distribusi Penyulang Pas 21 PT. PLN UPB Banda Aceh

This research focuses on analyzing power losses due to load imbalance in the medium-voltage distribution network in Pasar Aceh. The aim is to determine the magnitude of power losses that occur at the distribution substation in Pasar Aceh. The research method involves analysis, calculations, and simulations using the ETAP 12.6 software. The results of the analysis indicate that load imbalance in the Pasar Aceh substation leads to power losses. The Trafo Samping Pasar Aceh experiences power losses of 0.77% with a load imbalance of 16.33%. The second transformer in the BNI 46 area incurs power losses of 0.98% with a load imbalance of 30.33%, and the transformer in the BLKG KOTTY area has power losses of 1.17% with a load imbalance of 50.33%. These findings affirm that the greater the load imbalance, the higher the resulting power losses in the electrical distribution network.

Research on line loss analysis and intelligent diagnosis of abnormal causes in distribution networks: artificial intelligence based method.

The primary source of energy losses in distribution networks (DNs) is rooted in line losses, which is crucial to conduct a thorough and reasonable examination of any unusual sources of line losses to guarantee the power supply in a timely and safe manner. In recent studies, identifying and analyzing abnormal line losses in DNs has been a widely and challenging research subject. This article investigates a key technology for the line loss analyses of DNs and intelligent diagnosis of abnormal causes by implementing artificial intelligence (AI), resulting in several prominent results. The proposed algorithm optimizes the parameters of the support vector machine (SVM) and suggests an intelligent diagnosis algorithm called the Improved Sparrow Search Algorithm and Support Vector Machine (ISSA-SVM). The ISSA-SVM algorithm is trained to calculate the data anomalies of line losses when changing loads and exhibiting exceptional performance to identify abnormal line losses. The accuracy of abnormality identification employing the ISSA-SVM algorithm reaches an impressive 98%, surpassing the performances of other available algorithms. Moreover, the practical performance of the proposed approach for analyzing large volumes of abnormal line loss data daily in DNs is also noteworthy. The ISSA-SVM accurately identifies the root causes of abnormal line losses and lowers the error in calculating abnormal line loss data. By combining different types of power operation data and creating a multidimensional feature traceability model, the study successfully determines the factors contributing to abnormal line losses. The relationship between transformers and voltage among various lines is determined by using the Pearson correlation, which provides valuable insights into the relationship between these variables and line losses. The algorithm's reliability and its potential to be applied to real-world scenarios bring an opportunity to improve the efficiency and safety of power supply systems. The ISSA that incorporates advanced techniques such as the Sobol sequence, golden sine algorithm, and Gaussian difference mutation appears to be a promising tool.

Optimizing Technical Losses of the PLN Distribution Network with Changes in Operational Patterns in 2023 at PLN ULP Lhokseumawe

Technical shrinkage is shrinkage caused by impedance in generation equipment or transmission equipment to the distribution network so that there is energy loss. There are several technical shrinkage problems at PT. Perusahaan Listrik Negara (PLN) especially in Customer Service Unit (ULP) Lhokseumawe City and for now the cause is still unsolved, because this technical shrinkage problem will harm and have an impact on consumers and PLN itself. The purpose of the study was to optimize technical shrinkage in the distribution network to reduce energy losses that occurred during the electrical power distribution process in the distribution network of PT. PLN (Persero) ULP Lhokseumawe City. This study uses the help of Electrical Transient Analyzer Program (ETAP) software to simulate the power flow so that the depreciation value that occurs is obtained, then re-load adjustment is carried out to simulate again to determine the change in the depreciation value obtained after load adjustment. The results of the ETAP simulation show the depreciation value that occurred before the load adjustment was made by 76.7 kW after the depreciation load adjustment was adjusted to 59.6 kW. This means that this technical shrinkage can be suppressed by changing the feeder operation pattern and voltage drop value in accordance with the limitation provisions set in SPLN 72:1987.

Optimal Location of Electric Vehicle Charging Station in Reconfigured Radial Distribution Network

Electric vehicles are becoming increasingly popular because they are cleaner-burning and more efficient than combustion-engine automobiles. Due to the diminishing availability of fossil fuels and the carbon emissions produced by cars, electric vehicles (EV) have become a need for mobility in the near future. Electric car charging stations were established as a consequence of the increase in EVs. Electric car charging lowers voltage and increases real power loss in the radial distribution network. In order to mitigate real power loss and provide a stable voltage profile, the charging station has to be placed as efficiently as possible. The current research examines and elucidates the influence of electric vehicle charging stations (EVCS) on the balanced radial distribution network (BRDN) using particle swarm optimization (PSO). There are two steps involved in the planning process. The optimal placement for EVCS [1] in BRDN is identified in the first stage using PSO. The second stage uses reconfiguration to ensure higher EVCS stability. This two-step technique's main goal is to decrease the real power loss due to the placement of charging stations in the radial distribution network (RDN). The correctness of the suggested approach is expounded upon in four different cases. The second, third, and fourth cases use a two-step procedure, which is then compared to the base case. In the base case EVCS is ideally located in BRDN using PSO. The fourth case employs a concurrent two-step optimization approach and demonstrates superior performance compared to other cases. The suggested approach is implemented and evaluated on the IEEE 69 bus BRDN using the MATLAB software.

Comprehensive energy efficiency optimization algorithm for steel load considering network reconstruction and demand response

Industrial loads are usually energy intensive and inefficient. The optimization of energy efficiency management in steel plants is still in the early stage of development. Considering the topology of power grid, it is an urgent problem to improve the operation economy and load side energy efficiency of steel plants. In this paper, a two-level collaborative optimization method is proposed, which takes into account the dynamic reconstruction cost, transmission loss cost, energy cost and demand response benefit. The upper level objective is the optimization of topology in the grid structure to optimize the power loss and dynamic reconstruction costs of the grid. The lower level is the energy cost considering demand response, real time price and dynamic demand response price. Firstly, the mathematical models of stable load, impact load and the steel production line load are built. The key parameters are identified by the Back Propagation neural network algorithm according to the actual production data. Secondly, considering the constraints of grid structure and load operation capacity, the impact of dynamic grid loss and real-time dynamic electricity price on the energy efficiency of the whole grid are analyzed in depth. The optimal operation model considering the dynamic reconfiguration and grid tramission loss of distribution network is built. Taking a steel plant park in Northeast China as an example, it is proved that the optimization model can improve energy efficiency on the load side by optimizing energy consumption and demand response participation time on load side. The energy cost is reduced by 17.77% on the load side, the network loss is reduced by 1.8%, and the operating cost of the power grid is reduced by 26.2%, which has a positive effect on improving energy utilization efficiency, reducing distribution network loss, and improving overall economic efficiency.

Integrated dynamic multi-threshold pattern recognition with graph attention long short-term neural memory network for water distribution network losses prediction: An automated expert system

Water loss is a common and critical problem in water distribution networks, resulting in a decrease in wastewater and user experience. In this research, prediction-classification framework based on deep learning (i.e., graph attention long short-term neural memory network (GA-LSTM)) is proposed. Dynamic multi-threshold pattern recognition (DMTPR) was developed to identify and classify losses. To improve the model's reliability, we performed hyperparameter optimisation, trained and verified using one year's operation data of a real pipe network, and compared it with the previous methods. In addition, the influence of different aggregation ranges on the accuracy and stability of the model was analysed. The results showed that the GA-LSTM-DMTPR framework can be used as a reliable tool for practical applications because it provides high-precision and high-stability water demand prediction and realises accurate loss identification and classification. This is owing the potential of the model to aggregate the spatial and temporal multi-dimensional information.

Algorithm for phase distribution in power supply systems of single-phase electric receivers according to the criterion of minimization of the coefficient of load ununiformity of the phases used at the design stage

RELEVANCE. Unbalance of loads adversely affects both the work of consumers and the electrical network itself. This phenomenon leads to a decrease in the efficiency of the processes of transmission and distribution of electrical energy due to the appearance of additional losses. Balancing of loads in electrical networks of 0.4 kV is carried out both at the design stage of networks and during their operation. At the design stage, they try to evenly distribute the loads across the phases. The authors of the article solve the actual problem of distributing single-phase electrical consumers at the stage of designing a power supply system to analyze the total share of additional losses from unbalance in the structure of total losses in distribution networks of 0.4 kV.THE PURPOSE. To consider the problem of unbalance of loads in electrical 0.4 kV networks, causing additional losses of electricity. To analyze the existing methods of balancing when distributing the phases of the lines L1, L2, L3 of single-phase power receivers at the stage of designing electrical networks. Develop an algorithm for single-phase power consumer distribution, using arrays of instantaneous values of the current strength of individual electrical receivers as initial data. It stipulates calculating the best distribution of power consumers across the phases of lines L1, L2, L3 using the minimization of the load unbalance impact on the losses in power grid elements used for the electric power transfer.METHODS. To solve this problem, the authors employed the complete enumeration method implemented with a tertiary numerical system used to code power consumer distribution across the power supply grid phases. The coefficient accounting for the unbalance of load distribution across power grid phases is used as the target function.RESULTS. The developed algorithm can be applied as an external plug-in for the design software package to distribute the power consumers of one of the rooms in a BIM office building. The developed algorithm is compared to the existing widely-used approaches to single-phase power consumer distribution in power grids.CONCLUSION. The developed algorithm allowed producing brand-new engineering solutions while developing a design document for the power supply grid (design and detailed documentation stage). They help improve the efficiency of electric power transmission by reducing additional losses caused by unbalanced loads.

Detection of Pipes Causing Pressure Loss in Water Distribution Networks via Artificial Immune Systems

This paper proposes the optimization model using Artificial Immune Systems, depending on a model calibration, in order to determine worn out pipes with low Hazen-Williams roughness coefficient causing pressure loss in the water distribution networks. The modified Clonal Selection Algorithm, a type of Artificial Immune Systems, was used as a heuristic optimization method. In order to evaluate its performance, the model was implemented to the four-loop hypothetical water distribution network under steady-state conditions. According to the results, the model appeared to be promising in the detection of old pipes causing high pressure losses in the water distribution networks

Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis.

Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber's outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.

Analysis of Radial Distribution Systems by using Particle Swarm Optimization under Uncertain Conditions

Abstract: Losses in the network are one of the most important parts of a power distribution network, and work should be done to lower their value. The research used the Particle Swarm Optimisation (PSO) metaheuristic algorithm to investigate the impact of concurrently optimising phase balance and conductor size on the planning issues and objective functions of an imbalanced distribution system. These objective functions include power loss, voltage unbalance, total neutral current, and complicated power unbalance. Firstly, the optimisation process is applied to each goal function. Then, they are put together with weights to form a multi-objective optimisation problem. In this study, it was tried to find out how to minimise losses in electrical power distribution networks that aren't fair. Power flow and optimal DG placement are two PSO techniques that may be used to reduce losses. These changes may be applied to existing distribution systems using an effective load-flow method for a three-phase imbalanced radial distribution network. Knowing the node voltage, angle, branch current, actual power loss, wattles power loss, branch losses, etc. helps determine the network's true state. Simple formulae may be used to describe the relationship between the voltage at one end of the distribution system, the voltage at the other end, and the voltage drops throughout the whole system. An approach is developed to identify the relevant variables. The voltage's angle at the target is calculated with its magnitude. It's a process that requires time and effort. From the substation to each terminal node, the constant voltage of 1p.u. is considered. Voltage magnitude and phase angle are varied between repetitions, and voltage reductions are computed using the new parameters. The suggested approach has been applied to 19- and 25-node networks with unequal distribution. To demonstrate its efficacy, the recommended approach's speed requirements were compared to those of another recently developed technology. Good outcomes are achieved, and DG proves to be a viable option for reducing costs and improving performance.

Energy efficiency evaluation and optimization of active distribution networks with building integrated photovoltaic systems

With the rapid development of building integrated photovoltaic (BIPV) technology, rooftop PV grid-connected systems face challenges in operation. When the consumption rate of BIPV systems is low, power reverse increases distribution network losses and decreases power supply quality. Traditional energy efficiency evaluations for distribution networks do not consider the impact of low BIPV consumption rates on network losses. This paper establishes an energy efficiency evaluation model for distribution networks with BIPV systems based on adversarial interpretive structural modeling and proposes an energy efficiency indicator system applicable to distribution networks with BIPV systems. The method was applied to eight distribution networks with BIPV systems, achieving accurate energy efficiency level rankings. Through single-factor sensitivity analysis of the indicator system, the primary factors affecting distribution networks with BIPV systems energy efficiency were identified. A reactive power optimization model based on multi-objective particle swarm optimization algorithm was established. After optimization, network losses decreased by 153 kW, PV consumption rate increased by 73 %, and node voltage drift was significantly enhanced. Corresponding loss reduction strategies were proposed for other indicators. This paper provides valuable references for planning and renovating distribution networks with BIPV systems.

Inverter reliability-constrained Volt/Var optimization control of distribution network with high-level PV-storage generation

The involvement of renewable energy inverters in regulating the reactive voltage of the distribution network is an efficient approach to enhance the operational security and reliability of high-penetration renewable energy distribution networks. Nonetheless, the reactive power assistance offered by renewable energy inverters leads to an elevation in the maximum junction temperature of photovoltaic inverters and intensifies temperature fluctuations, which will subsequently impact the reliable and secure operation of both the inverters and the distribution network. In order to address this issue, this paper introduces a control strategy for optimizing reactive power and voltage in photovoltaic-storage (PV-storage) distribution networks with significant penetration, taking into account the constraint of IGBT junction temperature. Firstly, the IGBT junction temperature is calculated by the CatBoost algorithm, which improves the efficiency of IGBT junction temperature calculation and avoids the dependence of the traditional junction temperature algorithm on IGBT thermal model parameters. Then, a multi-objective reactive power optimization model of an active distribution network considering IGBT junction temperature constraint is established. The maximum output power of PV-storage power supply under IGBT junction temperature constraint is solved by dichotomy, so the transformation from IGBT junction temperature constraint to output apparent power second-order cone constraint is realized. Finally, the efficiency of the suggested approach is validated using the IEEE 33-bus typical distribution system. At the same time, the setting principle of IGBT junction temperature limit of PV-storage power supply considering the network loss of distribution network and the reliability of PV-storage power supply is proposed.