Low Voltage Electrical Distribution Research Articles

Flexible Energy Storage for Sustainable Load Leveling in Low-Voltage Electricity Distribution Grids with Prosumers

The sustainability of the energy sector is linked today with the diminishing of the reliance on fossil fuels and on the large-scale adoption of renewable generation. Medium- and low-voltage electricity distribution grids see the proliferation of microgrids that supply consumers able to generate electricity with local installations of PV panels. These consuming and generating entities, called prosumers, use the local generation for their own consumption needs and are exporting the surplus in the grid, modifying the typical steady state operation conditions. For mitigating this inconvenience, local storage equipment can be used, which also helps the prosumers to reduce their costs and preserve the sustainable operation of the distribution infrastructure. The literature shows that by optimally using storage in microgrids, the deterioration in quality and security of supply can be minimized in the presence of prosumers. This paper presents a study regarding local storage management in prosumer-enabled microgrids, seeking to find the optimal configuration of community (shared) storage systems that charge batteries overnight, during low consumption hours, providing load leveling opportunities and energy loss minimization. A study case performed on a real low-voltage electricity distribution network (LVEDN) shows the performance of the proposed optimization.

A Model-Free Deep Reinforcement Learning-Based Approach for Assessment of Real-Time PV Hosting Capacity

Assessments of the hosting capacity of electricity distribution networks are of paramount importance, as they facilitate the seamless integration of rooftop photovoltaic systems into the grid, accelerating the transition towards a more carbon neutral and sustainable system. This paper employs a deep reinforcement learning-based approach to evaluate the real-time hosting capacity of low voltage distribution networks in a model-free manner. The proposed approach only requires real-time customer voltage data and solar irradiation data to provide a fast and accurate estimate of real-time hosting capacity at each customer connection point. This study addresses the imperative for accurate electrical models, which are frequently unavailable, in evaluating the hosting capacity of electricity distribution networks. To meet this challenge, the proposed approach utilizes a deep neural network-based, data-driven model of a low-voltage electricity distribution network. This proposed methodology incorporates model-free elements, enhancing its adaptability and robustness. In addition, a comparative analysis between model-based and model-free hosting capacity assessment methods is presented, highlighting their respective strengths and weaknesses. The utilization of the proposed hosting capacity estimation model enables distribution network service providers to make well-informed decisions regarding grid planning, leading to cost minimization.

Low voltage electric distribution network planning with demand control

Low voltage electric distribution network planning with demand control

Expert System Integrating Rule-Based Reasoning to Voltage Control in Photovoltaic-Systems-Rich Low Voltage Electric Distribution Networks: A Review and Results of a Case Study

Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots.

A Hybrid Approach for Low-Voltage AC Series Arc Fault Detection

In a low-voltage electric distribution network, arc fault presents a high energy density electricity-discharging phenomenon between conductors, which is often caused by aging of electric facilities, loose contacts and terminals, or insulation failure due to internal and external destructions. A large amount of heat may be created during this discharging, which will further cause the risk of fire hazards to mitigate in the residential environment. Currently, many utility grid operators and electricity users are still devoted to seeking effective detection technology for arc fault protection. This paper proposes a hybrid approach that combines discrete wavelet transform (DWT), empirical mode decomposition (EMD), and dynamic time warping (DTW) methods for low-voltage AC series arc fault detection. In DWT, it uses time–frequency domain characteristics of the arc current signal to extract the occurrence of arc fault. In EMD, it decomposes the complex arc fault current signal into a finite intrinsic mode (IMF) signal; then, instantaneous amplitude of IMF signal is obtained by Hilbert–Huang transform (HHT) as a feature for arc fault identification. Firstly, the results of arc fault detections depend on the results from DWT and EMD. When both two methods detect different results, DTW method will be activated, using the similarity measurements between normal and arc fault current waveforms as an assistant measure to determine the occurrence of arc fault. The performance of the proposed approach is tested and validated using various electric appliances, and the results show that the proposed approach can effectively detect low-voltage AC series arc fault.

CHARACTERISTICS OF REFUSALS IN LOW-VOLTAGE DISTRIBUTION SYSTEMS

This paper focuses on the determination of the characteristics of refusals in low voltage electrical distribution systems. In order to solve this problem, the phenomena of occurrence of refusals in low-voltage electrical distribution systems, conditioned by different influencing factors, processed and mathematically modelled. The main results of the research consist in establishing the static characteristics of the refusals, the mathematical models that determine the occurrence of the cause phenomena and the parameters that characterize the distributions of the refusals, depending on the occurrence per system, depending on the occurrence per season, depending of interruptions duration and the number of affected consumers. The significance of the results obtained consists in solving a number of problems faced by the operating services of electrical distribution systems, concerning the assurance of reliability of operation, providing the possibility of forecasting and preventing the occurrence of the phenomena of occurrence of refusals, which enable the justified planning of prophylactic measures and ensuring the reliability level.

Aging aware adaptive control of Li-ion battery energy storage system for flexibility services provision

Battery energy storage systems (BESSs) play a major role as flexible energy resource (FER) in active network management (ANM) schemes by bridging gaps between non-concurrent renewable energy sources (RES)-based power generation and demand in the medium-voltage (MV) and low-voltage (LV) electricity distribution networks. However, Lithium-ion battery energy storage systems (Li-ion BESS) are prone to aging resulting in decreasing performance, particularly its reduced peak power output and capacity. BESS controllers when employed for providing technical ancillary i.e. flexibility services to distribution (e.g. through ANM) or transmission networks must be aware of changing battery characteristics due to aging. Particularly of importance is BESSs' peak power changes aiding in protection of the Li-ion BESS by restricting its operation limits of it for safety reasons and improving its lifetime in the long run. In this paper, firstly an architecture for ANM scheme is designed considering Li-ion BESSs as one of the FERs in an existing smart grid pilot (Sundom Smart Grid, SSG) in Vaasa, Finland. Further, Li-ion BESS controllers are designed to be adaptive in nature to include its aging characteristics, i.e. tracking the changing peak power as the aging parameter, when utilised for ANM operation in the power grid. Peak power capability of the Li-ion nickel‑manganese‑cobalt (NMC) chemistry-based battery cell has been calculated with the experimental data gathered from accelerated aging tests performed in the laboratory. Impact of such aging aware and adaptive Li-ion BESS controllers on the flexibility services provision for power system operators needs will be analysed by means of real-time simulation studies in an existing SSG pilot.

Phase Balance Optimization of Customers and Electric Vehicles in a Real Low Voltage Electricity Distribution Network

Abstract Phase unbalance is a common issue encountered in LV electricity distribution networks, caused by uneven allocation of single-phase loads among phases. This paper analyses a part of a real LV distribution network, situated in Bosnia and Herzegovina. The impact of single-phase customers and single-phase charging of electric vehicles was analysed. To reduce unbalance and improve the voltage profiles, Phase Balance Optimization in DIgSILENT PowerFactory software was performed in six scenarios with different customer and electric vehicle unbalance. The goal was to find a method with the least number of changes in the customer and electric vehicle phase connection that fits within defined limits of voltage variations and voltage unbalance of a European norm for power quality (EN 50160). Results showed that all analysed scenarios were improved, with reference to voltage variation and voltage unbalance values, and were found acceptable by the limits from standard EN 50160.

Planning of Low Voltage Electricity Distribution at Griya Arjuna Kejuden Housing

In a low-voltage power distribution system, there are often disturbances that result in disruption of electricity distribution to customers, resulting in losses for customers and PLN. The problem that often occurs is the occurrence of voltage drops and power losses so that in planning the construction of a low-voltage electric power distribution network, it is necessary to anticipate the occurrence of these problems. This research is expected to be used as a lesson for the creation of a low-voltage electric power distribution network with suitable and environmentally friendly construction and with low investment costs. collected data by visiting the location to conduct a survey and obtain accurate data related to the state of the research location. The stages in planning the Low Voltage Electricity Distribution Network begin with a field survey to obtain the required data. The installed power for each unit is 1.300 VA, so the total installed power is 122,200 VA and the spare power is 5% of the installed power so that the total installed power is 128.310 VA. during peak load times it is estimated that power consumption will only absorb 80% or 97,760VA. The required substation is a Portal Type Pole with a transformator capacity is 160kVA. The total breakdown of the electricity distribution network budget at the Griya Arjuna Kejuden is IDR 382,333,141.

Design of a Smart Distribution Panelboard Using IoT Connectivity and Machine Learning Techniques

Electric load management through continuous monitoring and intelligent controlling has become a pressing requirement, particularly in light of rising electrical energy costs. The main purpose of this work is to realize a low-voltage electrical distribution panelboard that allows for real-time load monitoring and that provides a load forecasting feature at the household level. In this regard, we demonstrate the design and the implementation details of an IoT-enabled panelboard with smart features. An IoT dashboard was used to display the most significant information in terms of voltage, current, real power, reactive power, apparent power, power factor, and energy consumption. Additionally, the panel system offers visualization capabilities that were integrated into a cloud-based machine learning modeling. Among several algorithms used, the Gaussian SVM regression exhibited the best training and validation results for the load forecasting feature. It is possible for the proposed design to be simply developed to add more smart features such as fault detection and identification. This assists in an efficient management of energy demand at the consumer level.

A Mixed-integer Linear Programming Model for the Plug-in Electric Vehicle Charging Problem in Unbalanced Low Voltage Electrical Distribution Systems Considering Neutral Conductor

The increasing penetration of plug-in hybrid electric vehicles (PHEVs) imposes new challenges in low voltage distribution networks (LVDNs), due to worsening load imbalance, power losses, and increased probability of blackouts because of the overloads. To overcome these issues, PHEV charging must be performed in a coordinated fashion. In this context, there are several coordinated charging methods in the literature, none of which considers modeling neutral conductors of LVDN.This paper aims to present a mixed-integer linear programming model (MILP) for the PHEV charging problem in unbalanced LVDNs, considering the neutral conductor. In this regard, the main parameters of unbalanced LVDN, such as voltage profile and power loss, are examined with and without modeling the neutral conductor. The results indicate that it is required to consider the neutral conductor to achieve realistic values of the LVDN's parameters. The proposed model is applied to a 449-nodes smart distribution grid consisting of 31 nodes at a medium voltage (MV) level and 418 nodes at a low voltage (LV) level. To verify the performance of the proposed model, it is compared with two uncoordinated charging methods. The results show the effectiveness of the proposed strategy.

Power Quality Analysis Based on Machine Learning Methods for Low Voltage Electrical Distribution Lines

Power Quality Analysis Based on Machine Learning Methods for Low Voltage Electrical Distribution Lines

Developing Novel Technologies and Services for Intelligent Low Voltage Electricity Grids: Cost–Benefit Analysis and Policy Implications

The paper presents a set of prototype smart grid technologies and services and validates the economic viability of the proposed solution using cost–benefit analysis (CBA). The study considered the EU-funded project called RESOLVD and implemented the technologies and services in a real-life pilot. The paper focuses on the analysis of technological solutions which enhance the operational efficiency and the hosting capacity of low-voltage electricity distribution grids. The solutions provided better integration of a hybrid battery storage system, with the grid interfacing power electronics, smart gateways for the interconnection of assets at the grid edge, and sensors enhancing infrastructure observability and control. The result from the CBA indicates the economic viability of the project, high scalability, and replicability. The economic benefits were realized with the breakeven value of eight secondary substations (SS) and 16 feeders. The scenario test on the DSO’s willingness to pay for the software as a service (SaaS) revealed that the payback period can further be reduced by almost half with a higher internal rate of return (IRR) and net present value (NPV). Both the CBA and scenario tests showed RESOLVD solution can become more economically viable when deployed in largescale. Moreover, the CBA results provide evidence to the energy policy by allowing DSOs to consider both CAPEX and OPEX for better investment decisions. Further, the paper proposes an alternative business approach that shifts from grid reinforcement to service provision. The paper also discusses the research implications on energy policy and business.

Non-technical losses in an electrical distribution system. Energy efficiency as a continuous process

This work analyzes the problem of non-technical losses in a low-voltage electrical power distribution system with an artificial intelligence model. The problem focuses on the use of a backpropagation multilayer perceptron neural network, which will quantitatively determine these losses from the manipulation of the current profile and the voltage drop expressed as percentages of their nominal values. These two magnitudes considered, will allow obtaining from the identification of patterns with large variations a technical assessment or quantification to approach the analysis from a different perspective, differing in the methodological determination of non-technical losses currently considered as a percentage of total losses. The results obtained will allow to form a basis for the correct determination of the non-supplied energy, its influence on distribution costs and energy efficiency for the future insertion of distributed generation.

Series FACTS controllers in industrial low voltage electrical distribution networks for reducing fault current levels

In this paper, series FACTS devices like Thyristor control series capacitor(TCSC)and Static synchronous series compensator (SSSC) with designed control logic used to reduce the fault current located in LV distribution network at the LV busbar. The electrical distribution network in small and medium scale industries such as steel plants, process and power plants is through low voltage switchgear (LVS) fed from motor control centre (MCC) switchgear through step down transformer of 11kV or 33kV /415V. The designed switchgear in the LV side for these utilities usually is at 50kA. However, the process loads are continuously increasing and sustained with additional feeders with the existing switchgear. Consequently, the fault current at the busbar of the switchgear increases which may require the replacement of entire switchgear to the new design fault current. However, upgrading the existing switchgear is not an economical solution to the industries. Alternatively reducing the fault current at the busbar is feasible. Controller design implemented for reducing the short circuit current with series FACTS devices. A study carried on 800 MW Thermal power plant Ash handling LVS in ETAP and Matlab. It is observed that the results are encouraging to use series FACTS devices effectively in the LVS.

Analyzing the returns and rate of return regulation of Finnish electricity distribution system operators 2015–2019

Electricity distribution prices have steeply increased in Finland since 2015. This research investigates the returns from the Finnish low-voltage electricity distribution business and compares them to returns from three European industry indices. The within-industry distribution of returns is also studied. The Finnish rate of return regulation model used is presented together with the level of allowed returns by the model, four changes to the model are proposed, and the effect of the four proposed changes on the returns allowed by the model are investigated.The results show that the returns of the Finnish DSOs are very high absolutely and comparatively. There is a ca. ten percent segment of the industry that is not very profitable, while ninety percent of the Finnish DSOs have high or very high returns. The proposed changes to the regulation model are shown to have a remarkable effect on the return level. A change limiting the return for equity only would bring down the return to a level that can typically be expected of a return from a natural monopoly company.The results are relevant to the ongoing process of legal and regulatory changes taking place in Finland and for decision-makers and regulators everywhere.

Statistical Analysis of Electric Power Distribution Grid Outages

Power systems in general supply consumers with electrical energy as economically and reliably as possible. Reliable electric power systems serve customer loads without interruptions in supply voltage. Electric power generation facilities must produce enough power to meet customer demand. Electrical energy produced and delivered to customers through generation, transmission and distribution systems, constitutes one of the largest consumers markets the world over. The benefits of electric power systems are integrated into the much faster modern life in such extent that it is impossible to imagine the society without the electrical energy. The rapid growth of electric power distribution grids over the past few decades has resulted in a large increment in the number of grid lines in operation and their total length. These grid lines are exposed to faults as a result of lightning, short circuits, faulty equipment, mis-operation, human errors, overload, and aging among others. A fault implies any abnormal condition which causes a reduction in the basic insulation strength between phase conductors or phase conductors and earth, or any earthed screens surrounding the conductors. In this paper, different types of faults that affected the electric power distribution grid of selected operational districts of Electricity Company of Ghana (ECG) in the Western region of Ghana was analyzed and the results presented. Outages due to bad weather and load shedding contributed significantly to the unplanned outages that occurred in the medium voltage (MV) distribution grid. Blown fuse and loose contact faults were the major contributor to unplanned outages in the low voltage (LV) electric power distribution grid.

Statistical Analysis of Electric Power Distribution Grid Outages

Power systems in general supply consumers with electrical energy as economically and reliably as possible. Reliable electric power systems serve customer loads without interruptions in supply voltage. Electric power generation facilities must produce enough power to meet customer demand. Electrical energy produced and delivered to customers through generation, transmission and distribution systems, constitutes one of the largest consumers markets the world over. The benefits of electric power systems are integrated into the much faster modern life in such extent that it is impossible to imagine the society without the electrical energy. The rapid growth of electric power distribution grids over the past few decades has resulted in a large increment in the number of grid lines in operation and their total length. These grid lines are exposed to faults as a result of lightning, short circuits, faulty equipment, mis-operation, human errors, overload, and aging among others. A fault implies any abnormal condition which causes a reduction in the basic insulation strength between phase conductors or phase conductors and earth, or any earthed screens surrounding the conductors. In this paper, different types of faults that affected the electric power distribution grid of selected operational districts of Electricity Company of Ghana (ECG) in the Western region of Ghana was analyzed and the results presented. Outages due to bad weather and load shedding contributed significantly to the unplanned outages that occurred in the medium voltage (MV) distribution grid. Blown fuse and loose contact faults were the major contributor to unplanned outages in the low voltage (LV) electric power distribution grid.

Evolutionary Approaches to Fog Node Placement in LV Distribution Networks

Smart grids merge intelligent computing technologies and electrical grid networks for better monitoring, control and management of electrical energy and facilities. The maturity of cloud computing has been the major driving factor for its adoption in smart grid deployments. Despite the elasticity of cloud resources, centrality and long distances to remote data centers cause high latency, high bandwidth consumptions and unstable connectivity, which are undesirable for IoT-based smart grid applications. Fog computing as an extension of cloud computing services to the edges of the network overcomes these challenges and perfectly suit the distributed nature of the low voltage (LV) electrical distribution networks as part of smart grid. The pressing issues with the adoption of fog computing for smart grid applications are finding the best placement plan for fog node locations in LV distribution networks to enhance monitoring and control. The main goal of this work is to present a mathematical model to address the aforementioned issues focusing on minimizing deployment cost and network delay. In addressing this multi-objective problem, a new algorithm, namely Future Search Particle Swarm Non-dominated Sorting Genetic Algorithm (FPNSGA), is proposed based on the combination of the best features of the NSGA-II, SMPSO, and a recently formed algorithm, Future Search. The effectiveness of the algorithm is evaluated based on the benchmarking technique (Weighted Sum approach), the convergence and diversification of the solutions using HV indicators and CPU time. The results from simulations show that the proposed mechanism is very competitive and outperforms other fog planning network schemes.

Improved Procedure for Earth Fault Loop Impedance Measurement in TN Low-Voltage Network

The difficulties and uncertainties related to earth fault loop impedance measurement are addressed in this paper. Based on the presentation of the measurement procedure implemented in the test equipment (diagrams and measured quantities, respectively, interpretation of results), the shortcomings and errors that accompany it are highlighted. The position in the power system, the influence of power transformers, and the use of effective quantities instead of phasors are important sources of errors, but, as will be seen, the switching of loads at the consumer sides and/or the occurrence of fault regimes during measurements can lead to the most serious impairment of the accuracy in the impedance assessment. The clarification of these aspects is achieved, both starting from the equivalent diagrams of the measurement circuits and the analytical interpretation of the phenomena associated with the measurements, as well as based on the modeling and simulation of TN low-voltage electrical distribution networks, in a specialized program, Eaton xSpider, which allows the complete and complex analysis of a large number of scenarios. Thus, essential conclusions were drawn regarding the level of errors and their causes, obviously, with the research coming with solutions to be implemented at the level of the measurement protocols of the devices used.