Power line parameter identification based on a binary nonlinear regression algorithm

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Hybrid data-driven method for distribution network topology and line parameters joint estimation under small data sets

Accurate line parameters are an important foundation for refined regulation and protection setting of distribution networks. In recent years, the topology of the circular distribution network, which has gained practical promotion, is complex and the direction of power flow is variable, making it difficult to apply the traditional radial network method for identifying line parameters. In this paper, a "time plane" based algorithm for identifying distribution network line parameters is proposed. In response to the situation where some distribution networks cannot collect voltage phase angle information from all nodes, it is proposed to analyze the power and voltage data that can be obtained by existing measurement equipment in the distribution network, and use a digital way to reflect the physical system to achieve visualization of the distribution network topology structure and line parameters. To achieve this goal, firstly, based on multiple sets of measurement data under time cross-sections, a linear regression topology and line parameter identification model is established according to the power flow equation, and preliminary calculations are made; Secondly, based on the concept of "electricity consumption", the line loss is used to infer the line parameters for each segment; Finally, the Adaboost algorithm was used to fuse the parameter identification results of the "time plane" and obtain the final distribution network parameter identification results. The feasibility of this method was verified using an IEEE 33 node example.

Active Distribution Networks (ADNs) are modern and intelligent power distribution systems that integrate renewable energy sources and advanced control technologies to provide reliable, secure, and efficient electricity supply. The traditional power distribution networks are designed to deliver electricity in a one-way flow from the transmission system to the customers. In contrast, ADN enables two-way power flow between the distribution network and customers, allowing them to become active participants in the electricity system. The key technology behind ADN includes advanced metering infrastructure (AMI), Distribution Automation (DA), and energy storage systems (ESS). AMI provides real-time data on electricity consumption, generation, and distribution, enabling efficient load management and demand response. Other key technologies of ADN include renewable energy sources such as solar photovoltaic (PV), Wind turbines and small-scale hydroelectricity. These sources are connected to the distribution network through power electronic interfaces that convert the DC output of the renewable sources into AC for distribution. Smart grid technologies such as microgrids, virtual power plants, and energy management systems are also integrated into ADN to improve grid stability and resilience. ADNs have the potential to transform the electricity system by enabling more efficient, sustainable, and reliable energy systems that can better serve the needs of consumers and society. Thus, ADN is expected to become a critical technology in achieving a cleaner and more sustainable energy future.

This paper presents the assessment of an enhanced line parameter estimation technique for modern distribution networks. The estimation method takes advantage of the use of Phasor Measurement Units or, more in general of synchronized phasor measurements. A comprehensive modeling of the uncertainty of synchronized data permits performing an accurate estimation. The validity of the estimation technique has been tested on a portion of the digital twin of the Forschungszentrum Jülich (FZJ) campus, a self-managed distribution network with more than 100 nodes. Realistic measurement assumptions have been considered by taking into account the accuracy of a measurement chain (instrument transformer and measurement device) for distribution networks. Furthermore, the presence of distributed generation has been also taken into account. The results will show that the parameter estimation in these challenging conditions is successful, and the technique can be applied for the analysis of real distribution networks.

Influence of frequency characteristics of soil parameters on ground-return transmission line parameters

Especially influenced by the rising number of renewable and distributed power generation plants and so-called unbundling, the controllability and protection of power supply systems are becoming ever more complex as these systems are developed further. To securely meet these challenges a reliable observability of the power system is needed. Novel digital measurement equipment such as phasor measurement units (PMU) in transmission and distribution networks and smart meters in low voltage grids deliver the system parameters needed to perform a system state estimation analysis. This paper discusses the use of PMUs to support the operation of virtual power plants (VPP). It additionally presents methods, which have already been tested in different simulations, to optimally select the locations of measurement units to ensure system observability.

The complexity of transient processes during travelling-wave propagation in extra high voltage overhead lines is deter-mined by the fact that many frequency components are presented in the electromagnetic wave front. For the correct analysis of the aforementioned transient processes and for further development of travelling-wave-based relay protec-tion and fault location devices, it is necessary to take into account the parameters of the environment where electromagnetic wave propagation occurs. For the transmission line, these parameters are longitudinal inductance, longitudinal resistance, shunt capacitance and shunt resistive conductance. It is worth mentioning that for a variety of reasons unit-area longitudinal inductance and resistance are the parameters which depend on frequency, thus travelling wave velocity is different for different frequency components of the electromagnetic wave front. The popular researches which address this problem either fail to consider the dependence of overhead line inductance and resistance on frequency or this dependence is considered approximately for the high-frequency range, which can cause significant errors in the transient processes analysis during travelling wave propagation. In view of this, the development of the approach to overhead transmission lines simulation, which will allow both determining the line parameters in a wide frequency range and evaluating steady-state behaviour and transient processes in long-distance transmission lines, arrears relevant. The main research method to establish extra-high voltage transmission line parameters employs the simulation study in COMSOL Multiphysics. A number of assumptions were made in the simulation process: homogeneous soil layer, entire transmission line section and absence of transmission line conductor sag. The usage of finite elements method (FEM) for differential equation solution in the above-mentioned software is also seen as an assumption. The approach to extra-high voltage transmission lines simulation has been offered. This approach consists of the usage of Maxwell’s equations in combination with numerical integration with finite elements method (FEM). Frequency response for transmission line parameters and travelling-wave propagation velocity rate for different frequency components have been obtained. The results obtained can be used in updating of electrical power system models for further research in the relay protection field. The suggested approach will allow evaluating line parameters of other voltage types and obtaining more accurate values of transmission line parameters and travelling wave propagation speed along transmission lines for high-frequency range. The use of these transmission line models will enable to formulate approaches to improve the existing algorithms of travelling-wave-based relay protection and fault location devices.

A fault location method for DC transmission line based on the distributed parameter model considering line parameter uncertainty

Phasor measurement units (PMUs) and wide area monitoring systems (WAMS) are undoubtedly the important technologies in power systems [1]. One of their implementations is online parameter identification using current and voltage phasor vectors from sending and receiving ends [2]. Transmission line (TL) parameters online updating could help to solve different tasks, such as state estimation, power flow analysis, and Q/V optimization. The updated TL parameters could provide the data to identify the fault localization. Using FACTS devices gives a possibility to automatic control the operating voltage along the TL [3]. For the task of Q/V optimization not only active resistance updating is required but also renewing the corona losses (CL) value and the dependence between CL and operating voltage (OV). It is well known that instant CL value depends heavily on the weather conditions (wind velocity, air humidity, ambient temperature, precipitation, etc.) along the TL and on the voltage profile along the line. Due to the challenge in commercially installing weather stations along the TL, TL parameters identification based on PMU measurements is the most viable and effective solution. There are some papers considering CL and OV relation as a quadratic function due to a pi-circuit [2], [4]. These papers suggest defining CL from TL conductance. It has been established that real dependence between CL and OV constitutes the 4-8 order polynomial [5]. Given that, the better the weather is, the higher the order is observed.

Estimating the line parameters of a two-terminal transmission line from synchrophasor measurements is useful for accurate representation of transmission lines in power system simulation studies. This paper evaluates three such methods, namely, a pointwise method, a least-square estimation method and a new mean-filter based method for estimation of two-terminal transmission line parameters. It presents the application and test results of these methods for archived field measurements in Southern California.

A large number of distributed power sources are injected to the distribution network, which can cause island operation in planned or unplanned situations. The islanded operation caused by the fault will cause the inverter to go off the grid in serious fault conditions such as short circuit between phases and disconnection. After the island is formed, if the common connection point before the island exchanges more power, a sudden change in the voltage within the island occurs. The frequency and phase angle changes of the voltage in the island are closely related to the characteristics of the inverter phase-locked loop, and the frequency mutation generally does not cause sudden changes in frequency due to a certain inertia of the phase-locked loop. Due to sudden changes in load power angle, input fault ride-through, etc., sudden changes in the phase angle of voltage in islands may occur. In order to solve the possible problems of power quality deterioration in islands, passive, active, and remote islanding detection schemes can be adopted, and the three schemes have their own advantages and disadvantages. In actual operation, it is necessary to consider the cooperation relationship between island detection, protection, safe automatic control and fault ride through.

With the rapid development of intelligent distribution network, a large number of distributed generation (DG) penetrated into the distribution network, changing the original unidirectional current flow direction of the distribution network, which made the direction of the flow is bidirectional or multi-end flow. When a fault occurs, the traditional centralized feeder automation and in-situ feeder automation solutions have not been able to satisfy fast accuracy requirements and have presented severe challenges to fault self-healing. In view of the existing problems, a control method based on quick-acting faults distributed FA is researched. It uses stacked topology recognition. After detecting current and interacting with the peer-to-peer through GOOSE communication, the smart terminal determines the fault area and jump on the local monitoring switch on the spot. After the fault is isolated, the power supply recovery operation is initiated. Taking a typical distributed power distribution network as an example, the different faults are studied. The experimental finally results show that the scheme can adapt to faults in various situations, and the entire fault self-healing process is controlled within 200 ms.

T-type transmission lines have been increasingly used in distribution networks because of the distributed generation integration, but inaccurate line parameters will cause significant error in the results of most existing fault location algorithms for this kind of line. In order to improve the precision, this paper proposes a new fault location algorithm taking line parameters as unknowns. The fault is assumed to occur on each section, and corresponding ranging equations can be built based on one set of three-terminal post-fault synchronous measurements, without using line parameters as inputs. Then, more sets of measurements are utilized to increase the redundancy of equations to resist the influence of data error. The reliable trust-region algorithm is used to solve each group of equations, but only equations of the assumed faulty section with the actual fault point can give the reasonable solutions, accordingly identifying the fault point. The performance of the proposed method is thoroughly investigated with MATLAB/Simulink. The results indicate that the algorithm has a high accuracy and is basically unaffected by fault position, fault resistance, unbalanced fault type, line parameter, and data error.

The large-scale integration of distributed photovoltaics (PV) can cause reverse power flow due to an imbalance between load and PV generation, altering the voltage profile in traditional distribution networks. The uncertainties in PV output can also cause voltage violations in the distribution network. Conventional methods for assessing static stability in voltage within such systems utilize continuous power flow techniques to calculate the load margin index, which provides a measure of how stable the voltage is in the distribution network. Nevertheless, the frequent load margin calculations in such methods result in significant computational costs, rendering them impractical for networks with distributed generators (DGs). Conventional static voltage stability assessment methods typically use continuation power flow (CPF) to calculate load margins but face significant computational bottlenecks in active distribution networks with distributed generation. For instance, even with improved power flow algorithms, a 33-bus system requires 58 iterations and about 0.3–0.5 seconds per analysis; in large-scale systems with tens of thousands of buses, total evaluation time can exceed 10 minutes. This paper introduces the holomorphic embedding load flow method (HELM), which accommodates different bus types (PI, PQ, PV) in active distribution networks. Building on HELM, a voltage partial sensitivity method is proposed, providing a criterion for evaluating the voltage stability in distribution networks. The sensitivity-based stability criteria using holomorphic embedding functions consider various DG operating conditions without requiring maximum load margin computation. The efficient calculation of these indexes makes the approach ideal for managing voltage in systems that include distribution networks with DGs. Finally, these indexes are used to manage voltage in active distribution networks, and the effectiveness of the method is confirmed through comprehensive numerical examples.