Statistical Impact Analysis of Underground Medium Voltage Network Switching Through Applied Load Flow Model

The distribution system is highly penetrating with the Electric Vehicle charging stations for increasing Electric Vehicle demand for a sustainable future. The impact of this large-scale integration into the distribution network at a medium voltage level has to be analyzed before dealing with the optimization problem of Electric Vehicles. This article elucidates the modeling of Electric Vehicle charging behavior using a measurement dataset whose aggregation integrated into the medium voltage network is analyzed to study their impact on the power network using probabilistic load flow simulation. The medium voltage network selected is the 69 bus test network to which Electric Vehicle aggregation is imposed as PQ load, and the voltage distribution and the voltage unbalance factor for such integration are discussed in the article at three different time windows i.e., morning, midday and evening.

This paper studies the scenario of multi-energy complementary system accessing medium-voltage distribution network, and quantitatively evaluates the impact of multi-energy complementary system (M-E) on the reliability of energy supply of medium-voltage distribution network (DN). Considering that M-E integrates a variety of energy coupling components with energy conversion functions, this undoubtedly greatly increases the reliability of energy supply. In this paper, the connotation of energy supply reliability is extended from a single grid to a thermo-electric coupling network, and the influence of network operation constraints formed by coupling on solving energy flow is fully considered. Based on the network operation constraints of the electro-thermal-gas coupling network, the cogeneration unit is used as the coupling node, and finally the reliability level under different wiring modes when accessing M-E is quantified. The results show that the M-E has a significant improvement in the reliability of the integrated energy system (IES).

Optimal planning of photovoltaic and distribution static compensators in medium-voltage networks via the GNDO approach

The paper describes the development of a new form of check synchronizing unit, for use during the paralleling of an a.c. machine on to live busbars, to ensure that the circuit breaker controlling the incoming machine is closed only when the correct degree of voltage, phase and frequency matching has been attained. For its action it depends essentially on the production of a series of unidirectional voltage pulses of rectangular waveform and constant amplitude, whose duration is determined jointly by the phase and frequency of the incoming machine relative to those of the busbars. The duration, and therefore the mean value, of the pulse voltage, is used as the criterion by which the correctness of phase and frequency matching is assessed; separate provision is made for ensuring that the magnitudes of the two voltages are sufficiently closely matched. As soon as correct conditions have been attained in all respects, the check synchronizer operates automatically to close the circuit breaker and connect the machine to the busbars.Features of interest, in the unit here described, are that since the settings of the majority of the relays are far from critical, they can conveniently be of the standard telephone type, their time delays, when required, being provided by simple combinations of resistance and capacitance connected in the relay operating-coil circuit. The check on frequency and phase matching is performed separately from that on voltage matching, and, over a wide range, is independent of variations in voltage magnitude.

In modern power systems, the increasing complexity of medium voltage (MV) distribution networks and rising environmental risks necessitate accurate and timely outage forecasting. This paper proposes a hybrid data driven framework that combines grey prediction modelling and support vector machine (SVM) classification for multi scale outage prediction. Annual and monthly outage counts are estimated using an optimized Grey Model GM (1,1) enhanced by Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). For day-ahead prediction, SVM is employed to classify outage risks using historical weather and fault data. The proposed method is validated using real operational data from the Italian distribution grid between 2008 and 2017. Experimental results demonstrate that the hybrid approach significantly improves prediction accuracy and supports proactive maintenance and resource allocation in MV networks.

Reducing power losses in energy distribution is forced by mandatory law. Optimization of network reconfiguration can lead to reducing power losses by even a dozen or so percent. Two methods of network reconfiguration optimization are presented in the paper: the heuristic method and a method based on genetic algorithms. The presented solutions offer the opportunity to optimize medium voltage and low voltage distribution networks at the same time. Calculation results for real distribution network are presented. The presented results indicate a high efficiency of network reconfiguration optimization. DOI: 10.12736/issn.2300-3022.2014407

The report presents a study of the costs for ensuring the quality of electrical energy and power supply in medium voltage and low voltage distribution networks. An analysis of the cost evaluation indicators for ensuring the quality of electrical energy covering a five-year period was made.

The allocation of emission limits is based on assumptions on the distribution of customer installations to the different voltage levels. Recent measurements indicate that the present used assumptions might lead to an under-utilization of the distribution networks, in particular regarding harmonics and unbalance. This paper verifies the validity of the assumptions for public medium voltage and low voltage distribution networks based on a comprehensive survey among network operators in Austria, Czech Republic, Germany and Switzerland. Based on the survey results recommendations are provided for future revisions of the relevant guidelines and reports in order to improve the utilization of distribution networks, in particular for harmonics.

The great advantages and huge amount of profits that broadband PLC (power line communication) brought are becoming more and more attractive to us. MV (medium voltage) and LV (low voltage) broadband PLC system built on MV and LV power distribution network, which sufficiently use power grids resources and save investment spent during information construction, become powerful competitor of traditional network such as optical fiber, xDSL and so on. In this paper, we take Broadband PLC system produced by TaiYuan ZhongBo information scientific institution for example, and discuss the development, system structure, characteristics and application of MV and LV broadband PLC system in detail. (6 pages)

Underground cables are being increasingly constructed in modern power distribution networks, however overhead lines are still present, making the system more exposed to faults. Faults from medium voltage networks propagate throughout the network and then experienced by low-voltage customers as voltage sags. Voltage sags have become increasingly important when considering the various power quality issues that cause inconvenience to customers. For some customers voltage sags cause, especially high costs. In this paper, different fault types at the medium voltage level and the sag propagated throughout the network are analyzed. Asymmetrical faults can cause problems for protection devices since they propagate differently throughout the distribution network, and distort the phase to ground voltages on the different voltage levels. Experimental results obtained from the Bosnia and Herzegovina distribution system show the significance of appropriate voltage sag propagation understanding. The power distribution companies should understand the voltage sags experienced in their networks and develop strategies for decreasing the influence of voltage sags. Thus, voltage sags analysis should be an important part of power distribution planning and an important element in a comprehensive power system analysis.

Using a 300kV puffer-type gas circuit breaker (GCB) combined with a 275kV-150MVA shunt reactor or a test air core reactor at a laboratory, the authors measured surges during reactor current interruption. Such surges as chopping current, single reignition, and multireignition surges were observed. To explain the mechanisms of these surges, the authors measured precisely high-frequency reignition currents with the help of an optical device. Multireignition surges seem unlikely to occur in actual fields.

Low-voltage (LV) feeder voltage magnitude and unbalance are often the constraining factors on a feeder's capacity to absorb rooftop photovoltaic (PV) generation. This paper presents a new probabilistic method for voltage management in distribution networks through the placement of distribution static compensators (dSTATCOMs) and on-load tap changers (OLTCs) considering the reactive capability of PV inverters in multiple LV and medium-voltage distribution networks. The method uses a modified particle swarm optimization. In this paper, several scenarios for the placements of multiple dSTATCOMs with and without embedded energy storage systems using both reactive and real power compensation are investigated in combination with an OLTC equipped with independent per-phase tap-changing control. The voltage constraints in the proposed method are statistically defined using three duration curves. These are the voltage unbalance, maximum voltage, and minimum voltage duration curves. The method is comprehensively tested for varying load and PV generation based on data from a real Australian distribution network with considerable unbalance and distributed PV generation. The results show that PV hosting capacity increases where the proposed approach is applied.

During martial law in Ukraine, accounting for fixed assets faces significant challenges due to the ongoing war. Key issues include the destruction or damage of assets, making it difficult to assess their value and determine impairment losses. Businesses often face disruptions in operations, leading to challenges in tracking asset usage, depreciation, and maintenance. The conflict complicates asset verification, as physical inspections may be impossible due to restricted access or destroyed records. Impairment of assets is a major concern, as companies must evaluate the reduced value or functionality of assets, often without access to reliable data. Additionally, relocation of assets to safer regions complicates tracking and valuation, while regulatory uncertainty around tax and depreciation rules adds further complexity. Businesses also face inflation and currency devaluation, making asset valuation even more challenging. Legal issues, such as asset seizure or expropriation, present further complications, particularly in determining ownership and potential compensation. The lack of clear guidelines on accounting for war-damaged assets, combined with the displacement of accounting personnel, exacerbates these problems. Overall, businesses must adapt their accounting practices to navigate the unpredictable environment while maintaining compliance and transparency.

A practical PMU configuration method based on weak voltage area monitoring and incomplete observability is proposed. Firstly, SNB curves of all buses are calculated by CPF. Then voltage magnitude variation is adopted to find weak voltage buses under the same load variation rate. The buses, which have bigger normalized /spl Delta/V , are chosen as weak voltage ones. We use the rate of voltage magnitude variation as grouping standard and present two indices (in time domain and frequency domain) for weak voltage buses group similarity. A fuzzy maximal tree is constructed to group the weak voltage buses according to their similarities and in consideration of the geographic factors. To locate the PMUs equally and sparsely, we introduce incomplete observability for PMU configuration as well as the placement rule. Finally, the whole PMU configuration flow chart is proposed and the simulations on IEEE 118 bus system show our configuration method is effective.

In the next decades, many public infrastructure assets will reach the end of their life that they were originally designed for. Replacement costs are high, and therefore increasing effort is put into lifetime-extending maintenance, including major overhauls and renovations. A key question is whether the investments in lifetime-extending maintenance justify the postponement of a full replacement. This question becomes more complicated when future life cycle cash flows are non-repeatable. Differential inflation and technological change, including multiple intervention strategies to maintain a desired functionality, cause such non-repeatability. In this case, classic replacement analysis techniques will not suffice in answering this question. Literature demonstrates that case-specific modelling with dynamic or linear programming techniques is required to find economic optimisation. However, such literature primarily addresses replacement interval optimisation of new investments within relative short time horizons, whereas the current research develops a nested dynamic programming (DP) approach for typical ageing infrastructure assets over long service life periods. The model can deal with multiple and various successive intervention strategies and addresses differential inflation and age-related cost increases. Finally, it is shown in an infrastructure case study that this DP approach leads to a better decision in comparison to the application of classical replacement techniques.