Measurements of the frequency-dependent network impedance in the frequency range 20-150 kHz have been carried out on points of common coupling in residential areas, office buildings, street cabinets, transformers, individual residence metering cabinets, and the Per Högström laboratory in Luleå University, located in the North of Sweden. The results of the measurements are presented. A method for representing the network impedance in the form of a finite number of lumped R-L C elements is proposed in this paper, based on measurements. Based on the measurements and lumped parameters, the emission limits in the frequency range 20-150 kHz have been identified and presented in this paper. In the absence of measurements, a method for identifying emission limits based on the extended IEC 61000 4-7 reference impedance using Monte Carlo analysis has been presented. As EV charging assumes prevalence in terms of loads on the grid, a comparative analysis of the change in grid impedance with the introduction of EVs on the grid is presented.

Harnessing demand-side flexibility for system-wide flexibility services is becoming increasingly popular. The effect of such services on distribution grid parameters, such as harmonic distortion, has remained underexplored. This paper describes a Monte Carlo simulation-based stochastic harmonic distortion assessment with segmented Gaussian mixture model (GMM) based harmonic injection models. The proposed method is capable of capturing uncertainties and temporal changes of the load behavior and operation when providing flexibility services. The study is carried out considering aggregated electric vehicle (EV) charging for manual frequency restoration reserve (mFRR) activation market-based balancing flexibility provision. Two real low-voltage (LV) networks, representing residential and mixed customer loads were used for the analysis. The analysis focused on the hourly variation of harmonic voltage distortion at the LV side of the transformer and customer connection points. The variation of transformer loss factors for non-sinusoidal currents introduced in IEEE std C57.110-2018 is also analyzed. Results show a significant increment in considered LV grid parameters between highly available flexible hours and non-flexible hours in flexible charging. The daily maximum and 95^th percentile values were seen to be increased in flexibility provision-based charging compared to the baseline. The total harmonic distortion (THD) voltage increment during the day, for an average residential supply in the charging baseline was 11.25%, which was increased to 40.12% in the flexibility provision. In conclusion, distribution system operators should be aware of the possible risk of flexibility-induced harmonic distortion increment when the distributed energy resources are allocated for system-wide flexibility services.

This paper presents a comprehensive framework for wide-area modeling and harmonic resonance assessment in the AC single-phase Swedish electric railway power system (ERPS). The methodology integrates the modeling of key elements of the catenary system, such as synchronous generators, transmission lines, transformers, and filters, while addressing the dynamic behavior of rolling stocks and inherent system uncertainties. Study cases, including Monte Carlo simulations, are developed to evaluate probabilistic scenarios and impedance variations across the network using nodal admittance modeling and frequency scanning. Key contributions include a method to model moving loads, a comprehensive approach to harmonic resonance analysis based on meshed grid characteristics of the ERPS, and an uncertainty assessment framework that highlights insights for system planning and mitigation actions. Discussion outlines future research directions for improved ERPS harmonic resonance studies. 

Flexibility Contracts (FlexCons), in the context of power and energy systems, aim to address challenges arising from uncertainties in electricity consumption and variable renewable generation using a bilateral short-term instrument. Through such contracts, electricity retailers (RETs) and variable renewable energy producers (VREPs) agree to provide power flexibility to one another to reduce the impact of imbalances on their respective decision-making processes. In this paper, two four-stage decision-making problems are developed for RETs and VREPs to analyze their participation in FlexCons alongside the day-ahead market (DAM), intraday market (IDM), and balancing market (BLM). The proposed models incorporate uncertainties in market prices, electricity consumption, and renewable generation through scenario sets and a stochastic decision-making approach. Additionally, the framework includes single-price and 15-minute imbalance settlement, as well as location-specific considerations within the system. Subsequently, the outcomes of these decision-making problems are integrated into the market-clearing processes of DAM, IDM, and BLM to assess the positive and negative impacts of such bilateral transactions. A two-bus illustrative example and the IEEE 24-bus RTS system are used for simulations. The results indicate higher profit for FlexCons’ participants by 1.6%, lower flexibility prices in the BLM by 6.8%, and an overall reduction in system costs by 4% when FlexCons are used.

The growing penetration of power-electronic loads such as EVs in low-voltage networks motivates accurate models for harmonic and supraharmonic impact assessment. This paper proposes a parameterized framework for EV front-end converters in which a detailed Simulink switching model is used to identify the frequency coupling matrix (FCM) and the resulting frequency-dependent admittance. Based on a focused literature review, the FCM approach is adopted to capture cross-frequency, cross-sequence, and cross-phase interactions. The framework is applicable to both two-level VSC and three-level Vienna-type converters and their control strategies, enabling scalable frequency-domain propagation studies. A charging-hub case study demonstrates integration of the identified admittances into a network model, where disturbance propagation is quantified via controlled current injection and evaluation of the resulting nodal voltage spectra.

Sweden has a very high and variable soil resistivity, making it difficult to ensure a consistently good connection to earth along the track. Booster Transformers (BTs) have been used to ensure that the current returns through the intended path and that stray currents are limited. The ability of BTs to control return currents is limited by their series impedance and by imperfect coupling. In this article, we make a detailed model of the BT system between two feed-in points and evaluate how well the BT system can contain stray currents at harmonic frequencies. The main contribution is that we demonstrate that harmonic currents are significantly less well contained by the BT system, and that the practice of allowing local grid connections to the railway earth system risks creating significant stray currents in the local grid, particularly at harmonic frequencies, but also that electrical safety may be compromised by the transmission of touch voltages to locations with a different soil resistivity than the rail bed.

The waveform distortion interactions and time-varying behavior in electric railway power systems (ERPS) are explored in this paper by investigating measurements from a traction converter station. The paper proposes a methodology aimed at contributing to three aspects: screening detailed measurements with high resolution in time and frequency, comprehensively assessing waveform distortion parameters of the system, and developing a time-varying framework to assess waveform distortion interactions and sub-1-min variations in the railway grid. Specific focus is given to identifying disturbance sources and patterns during operation, including limitations of traditional methodologies based on aggregated values and addressing the challenges posed by the differences between the two electromagnetic environments (railway grid and public grid). The results propose new indices ( z-WDSV,z-WDSV_w ) for evaluating waveform distortion in ERPS, highlighting the suitability of the methodology for assessing time-varying interactions and probabilistic aspects. The proposed framework can determine and quantify the frequency-domain components impacted by the operation of vehicles in the traction sections. Additionally, the limitation of longer measurement intervals is confirmed by the relationship between the aggregated value and variance due to the rapid variation caused by rolling stock operations. Other aspects of mechanisms involving waveform distortion on both sides of the traction converter station are discussed.

This paper aims to characterize the long-term variations of the Low Voltage (LV) distribution grid impedance in the MHz band, as well as the impedance variations between the electrical phases in three-phase installations, based on extensive field trials in real scenarios. These measurements were carried out in different scenarios and over different periods. The results provide valuable insights into the temporal evolution and variability of the grid access impedance at Broadband Power Line Communications (BB-PLC) frequencies. Comprehensive knowledge of these variations is essential for improving the design, reliability, and robustness of BB-PLC systems, as well as for developing more adaptive communication strategies and grid monitoring tools that can effectively cope with impedance variations.

Electric railway systems (ERS) are characterized by several particularities regarding the return current circuits, moving loads, multiple sources of waveform distortion, and extensive deployment of static converters from various manufacturers, topologies, and solutions. This work presents a methodology for application of load monitoring to classify rolling stock (RS) waveform distortion signatures. The proposed methodology combines the benefits and advantages of unsupervised deep learning and reconstruction error performance classification for performing non-intrusive load monitoring (NILM) in ERS. It consists of adapting autoencoder-based novelty detection for load classification problems. The method is applied to pantograph measurements from four rolling stock items using two types of data input (harmonic spectra up to kHz and VI diagram images), which are compared in binary classifications of the same kind of railway electrification. The methodology shows suitable classification performance with high accuracy, scoring an average of 98.81 % for spectrum input and 97.77 % for VI diagram input. It has also been validated with a NILM dataset (LIT) for multi-class applications showing 99.13 % for spectrum input and 94.28 % for VI diagram input. The proposed method has suitable computational times and scalability, allowing application to a wide range of NILM and classification problems using distortion signatures.