Power Converter Solutions for Industrial PV Applications—A ReviewMykola Lukianov (ESR06)The paper conducts a comparison of different topologies on power converters based on two parameters that describe their cost and power loss for various PV applications. For a straightforward study, these parameters are represented using the gain factor, which allows for an accurate comparison of the efficiency of various types of converters. Energies 15, no. 9: 3295, doi: 10.3390/en15093295 |
A Genetic Algorithm for Residential Virtual Power Plants with Electric Vehicle Management Providing Ancillary ServicesAnas Abdullah Alvi (ESR03)Virtual power plants are a useful tool for integrating distributed resources such as renewable generation, electric vehicles, manageable loads, and energy storage systems under a coordinated management system to obtain economic advantages and provide ancillary services to the grid. This study proposes a management system for a residential virtual power plant that includes household loads, photovoltaic generation, energy storage systems, and electric vehicles. With the proposed management system, the virtual power plant is economically optimized (as in commercial virtual power plants) while providing ancillary services (as in technical virtual power plants) to the distribution grid. A genetic algorithm with appropriate constraints is designed and tested to manage the energy storage system and the charge/discharge of electric vehicles, with several economic and technical objectives. Single-objective optimization techniques are compared to multi-objective ones to show that the former perform better in the studied scenarios. A deterministic gradient-based optimization method is also used to validate the performance of the genetic algorithm. The results show that these technical targets (usually reserved for larger virtual power plants) and economic targets can be easily managed in restricted-sized virtual power plants. |
Power converter interface for urban DC traction substations - solutions and functionalityMykola Lukianov (ESR06)This paper focuses on extending an urban DC traction substation functionality by means of an additional power converter interface (PCI). In particular, by enabling bidirectional energy exchange between LV DC traction grid, AC grid and V2G chargers. Among other things, the presented material compares general attributes of the most promising DC/DC converters that can be used in a PCI, meet the requirements of galvanic isolation and can operate in a wide voltage range. Based on the literature, the application suitability of typical PCI structures and isolated DC/DC converters was made. In addition, the principles of power flow in the power converter interface that connects an AC grid, DC traction grid, V2G chargers and PV source are discussed.
Type: Journal Publication
Date: 2023-11-01
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Grounding and Isolation Requirements in DC Microgrids: Overview and Critical AnalysisMohammadreza Azizi (ESR05)DC microgrids, along with existing AC grids, are a future trend in energy distribution systems. At the same time, many related issues are still undefined and unsolved. In particular, uncertainty prevails in isolation requirements between AC grids and novel microgrids as well as in the grounding approaches. This paper presents a critical technical analysis and an overview of possible grounding approaches in DC systems and the feasibility of avoiding isolation between AC and DC grids.
Type: Journal Publication
Date: 2023-11-24
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Comparison of Energy Storage Management Techniques for a Grid-Connected PV- and Battery-Supplied Residential SystemLuis Ignacio Martínez Caballero (ESR02)Open access publication accepted in the journal Electronics |
Cooperative stochastic energy management of networked energy hubs considering environmental perspectivesSaeed Akbari (ESR12)Energy hubs (EHs) aim to increase the flexibility of energy systems by adopting different energy carriers and sources. This paper presents a cooperative stochastic framework for managing networked EHs (NEHs) from an economic-environmental perspective. Scenario preparation techniques, such as Monte Carlo simulation (MCS) and the k-means clustering algorithm, are used to develop scenarios for different sources of uncertainty. Furthermore, the Shapley value is used to allocate coalition gains among NEHs based on their contributions and performance. To distinguish the proposed model from existing literature, several case studies have been conducted to assess its effectiveness. Conducted simulations show that through cooperation, the total cost of EHs and CO2 emissions is reduced by approximately 3 % and 1.8 %, respectively. Moreover, the performed sensitivity analyses indicate the robustness and reliability of the model against input parameters. |
The potential of residential load flexibility: An approach for assessing operational flexibilitySaeed Akbari (ESR12)The potential of residential load flexibility: An approach for assessing operational flexibility |
Traditional and Hybrid Topologies for Single-/Three-Phase Transformerless Multilevel InvertersAyesha Aslam (ESR01)With increasing interest in integrating solar power into the utility grid, multilevel inverters are gaining much more attention for medium- and high-power applications due to their high-quality waveform, low voltage stress across active components, and low total harmonic distortion in output voltage. However, to achieve these benefits, a large number of active and passive components are required. A transformer is also required to provide galvanic isolation, which increases its size and weight and reduces its power density and efficiency. In order to overcome the disadvantages posed by transformer-based inverters, research is being conducted on the transformerless topology of multilevel inverters. The first aim of this review article is to summarize traditional transformerless multilevel inverters (TMLIs) considering both single- and three-phase topologies. Secondly, the main aim of this article is to provide a detailed overview of the hybrid topologies of TMLIs that employ fewer components for photovoltaic applications. In addition, this study compares traditional and hybrid single-/three-phase topologies in terms of component count and performance factors, which will be useful to researchers. |
Online real-time robust framework for non-intrusive load monitoring in constrained edge devicesLuis Enrique Garcia Marrero (ESR11)Real-time information on detailed power consumption can motivate users to make informed decisions to reduce their energy bills. In that sense, Non-Intrusive Load Monitoring (NILM) emerges as a cost-effective technique to achieve the previously mentioned benefits. This paper presents an online real-time robust NILM framework that only requires the aggregated active power, operates by updating the appliance’s state probabilities sequentially, and uses this information to predict the power consumption of each monitored appliance. The framework primarily focuses on the seamless integration and practical deployment of a real-time NILM algorithm, operating at frequencies around 1 Hz, on constrained edge devices. Starting with detecting edges and the base load in real-time, the appliance’s state probabilities are updated considering the possible presence of unknown loads. The power consumption of each appliance is then estimated by employing a modified Population-Based Incremental Learning algorithm (PBIL). Experiments on two publicly available datasets against state-of-the-art methods demonstrated its accuracy and robustness in the presence of unknown appliances. The real-time capabilities of the framework were verified through integration in a Home Automation framework running in a constrained edge device. |
Influence of the temperature on the intrinsic parameters of thin-film photovoltaic modulesLuis Enrique Garcia Marrero (ESR11)The electrical parameters, the ideality diode factor and the parasitic resistances of a photovoltaic module can be estimated from its current–voltage (I–V) curve. However, there are only very few studies focused on thin-film devices, that could have a thermal behavior different from crystalline silicon technologies. This study analyzes the variation of these parameters from a set of current–voltage curves of several commercial modules from different technologies: single-crystalline silicon (sc-Si), multi-crystalline silicon (mc-Si), amorphous silicon (a-Si), tandem of micro-crystalline silicon and amorphous silicon (a-Si/c-Si), tandem of cadmium selenide and cadmium telluride (CdS/CdTe), and copper indium selenide (CIS). Most of the modules present a positive value for the current thermal coefficient, but the voltage and power temperature coefficients are negative in all the cases. With respect the series resistance, it is significantly higher for the thin-film modules than for the crystalline silicon ones. Moreover, the thermal coefficient of the series resistance varies depending on the technology. Regarding the shunt resistance, it seems to be insensitive with respect the temperature for a small range. Finally, the diode ideality factor seems to be constant for crystalline silicon whereas it depends on the temperature for thin-film. |
Self-adaptive single-diode model parameter identification under small mismatching conditionsLuis Enrique Garcia Marrero (ESR11)Current model-based methods for monitoring photovoltaic (PV) modules typically rely on the single-diode model (SDM) or its variants, assuming uniform operating conditions across the module. However, these ideal conditions are difficult to realize in real-world applications due to partial shading, soiling, degradation, and other phenomena. This paper proposes a 7-parameter self-adapting Double SDM model (D-SDM) to enhance the accuracy and reliability of parameter identification in PV modules under real operating conditions. A robust methodology based on evolutionary algorithms is proposed to estimate the parameters of the D-SDM, directly from the I–V characteristic of a PV module, applicable in both uniform and mismatched scenarios. The proposed methodology also includes a robust fitting error calculation that only considers the section of the I-V curve where all the cells operate with positive voltage. The methodology is validated using experimental and simulated I–V curves across various mismatching patterns, demonstrating the superior stability and reliability of the proposed method, which can be used for PV system monitoring and diagnosis in complex conditions. |
Energy Router: A Sustainable Solution for Future Residential BuildingsMohammadreza Azizi (ESR05)Electric energy consumption is increasing much faster than the predicted growth in energy generation. Although the installed capacity of renewable energy sources is also expanding, grid congestion remains unavoidable without adopting smart energy management systems (EMS) and flexible power electronics structures. Given the significant installed capacity of photovoltaic (PV) systems in the residential sector, moving towards zero-emission buildings (ZEBs) through the use of storage systems and smart power electronics is essential. This article provides a detailed review of power electronics solutions for ZEBs and offers strategies to address related challenges. By exploring the promising future of the low-voltage dc (LVDC) industry in ZEBs, it presents and compares grid connection scenarios and evaluates their overall efficiencies across hybrid, dc, and ac technologies. Furthermore, it addresses the integration of dc and ac systems in energy router (ER), proposing solutions for challenges related to protection, grounding, and leakage currents. Finally, it examines the latest EMS solutions, emphasizing the shift to full digitalization through a combination of cloud-based and edge-computing platforms. |
IEEE Transactions on Power ElectronicsShuyu Ou (ESR04)Monolithic Data-Driven Condition Monitoring Strategy for MMC Considering C and ESR DOI: 10.1109/TPEL.2025.3549226 (Early Access) |
Energy communities – lessons learnt, challenges, and policy recommendationsKonstantinos Pantazis (ESR15)Energy communities (ECs) are considered important in transitioning the energy system. They are of particular interest due to their potential to empower citizens and support a more just energy transition. However, experiences from ECs remain limited and vary across countries, thus raising questions on potential future advancements. In this article, we explore experiences from ECs in several European countries to inspire discussions on further evolvement and improvements. Insights into lessons learned and key challenges within the selected countries have been collected and analysed, and recommendations for advancing these efforts are provided to policy makers. The results indicate that ECs are making progress in producing and sharing renewable energy while supporting a more just energy transition by engaging a variety of actors within local communities. The challenges, however, often stem from limited national support and difficulties in fully achieving diversity within engaged local communities. The recommendations stress the importance of building on early learnings in community energy and further strengthening local anchoring to achieve a just transition. This in turn, generates fertile ground for discussions on how to localize energy policy and reinforce a multi-level policy approach beyond the European and national levels. |
Solar PV Generation and Consumption Dataset of an Estonian Residential DwellingSayeed Hasan (ESR10)Reliable data on residential power generation and consumption is vital for effectively integrating renewable energy sources. This is particularly important in the Baltic countries, where climate variability significantly impacts energy production and consumption. Such high-resolution residential usage data is beneficial for various applications, including planning, demand response, consumption behavior analysis, and forecasting. The dataset presented in this study contains one year (2023) of photovoltaic (PV) generation and energy meter power flow data collected at ten-second intervals from a residential dwelling in Estonia. To gather this data, two Camille Bauer PQ1000 power quality monitoring units were installed on the PV and meter side wiring of the house. The paper thoroughly discusses the data collection process, the original dataset, the processed data, and the feature analysis. |
IEEE Transactions on Power ElectronicsShuyu Ou (ESR04)Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters DOI: 10.1109/TPEL.2025.3556387 |
Experimental Assessment of Partial Shading Detection in PV Panels Using Impedance SpectroscopyLuis Enrique Garcia Marrero (ESR11)This article investigates the use of Impedance Spectroscopy (IS) to identify mismatches in Photovoltaic (PV) panels/string/array, particularly for detecting partial shading effects. The findings confirm IS as a promising tool for onfield applications, especially in small-scale urban power plants where partial shading is a common issue. An analysis of several experimental impedance spectra measured with PV panels operating at their Maximum Power Point (MPP), with controlled partial shading conditions, reveals that partial shading induces a characteristic double-arc deformation. This feature could be leveraged in a diagnostic tool for mismatch detection. The key advantage of this approach is its ability to perform IS measurements at MPP, preserving the normal operating conditions of the PV panels/string/array. Additionally, IS requires minimal modifications to the system's architecture and integrates easily into existing power electronics interfaces. To validate the consistency of impedance spectra under partial shading, experimental data were compared with two models: a Constant Phase Element (CPE) model adapted for PV strings in nonuniform conditions and an enhanced Single-Diode Model (SDM) developed for SPICE3-based simulations. The results confirm that IS successfully adjusts the models and detects mismatches in both experimental and simulated scenarios, demonstrating its scalability and effectiveness as a state-of-the-art PV diagnostic tool. |
Generic residential load profile generator based on weather data and occupancyCheikh Elkebir Sidi Lekhel (ESR09)Due to changing policies favoring renewable energy, residential energy management increasingly requires flexible consumption forecasting to optimize energy sources and costs. This paper introduces a simple application to generate home electricity consumption profiles by combining thermal and mathematical modeling with weather forecasts, occupancy schedules, and user settings. The model classifies household loads into thermostatically controlled appliances such as heat pump, water heater, and refrigerator and those highly depend on occupant behavior like lighting, washing machine, and common ON/OFF devices. By accounting seasonal changes, occupancy schedules, and varying temperatures, the model reflects real case conditions. Validation conducted under diverse conditions in a French context reveals that daily energy consumption can range from 14 kWh to 30 kWh, underscoring the adaptability of the proposed approach with different scenarios. A fully functional prototype, deployed on a Raspberry Pi 4 and integrated with Home Assistant, computes detailed 24-hour load forecasts with a resolution of one second. This modeling framework facilitates integration into home energy management systems or demand side management, offering a model with the ability to adjust for weekday or weekend schedules. Moreover, its generic design and flexible in changing parameters enable adaptation to different household sizes, number of occupants and insulation types, making it well suited to a wide range of residential scenarios. |
Enhancement of residential PV energy storage system by supercapacitor battery – high spatial resolution data analysisSayeed Hasan (ESR10)This article addresses frequent instability issues observed in the operation of typical residential photovoltaic (PV) microinstallations through a new approach to energy storage system (ESS) design. Based on high-resolution, long-term recordings of power fluctuations in a residential PV installation located in Tallinn, Estonia, various instability problems are identified and analyzed. A mixed ESS is proposed to provide rapid and effective compensation for the detected fluctuations. The study introduces a hybrid energy storage solution combining supercapacitors and batteries to mitigate these issues and ensure balanced system operation. Specifically, an innovative 32 Wh supercapacitor bank, integrated with the DC link of a standard PV inverter, is proposed to address both short- and long-term power fluctuations on the generation side. Peaks and dips in power consumption and generation are detected using a Z-score-based peak detection method. Experimental results comparing different ESS configurations are presented and discussed. Furthermore, the study demonstrates how the supercapacitor bank successfully mitigates several instances of generation fluctuations. The paper also explores how the incorporation of a supercapacitor ESS in a DC microgrid can affect battery lifespan, in addition to stabilizing PV generation. |
Transfer capabilities of Seq2Seq and Seq2Point CNN architectures in Non-intrusive Load Monitoring with unseen appliancesLuis Enrique Garcia Marrero (ESR11)In the Non-Intrusive Load Monitoring context, Seq2Seq and Seq2Point Convolutional Neural Network architectures have demonstrated state-of-the-art performance. However, as these methods suffer from high computational costs and the need for large volumes of training data, their transfer capabilities to different domains are essential for real-world implementation. This paper analyzes the drop in performance of Seq2Seq and Seq2Point architectures in the presence of appliances not seen in the aggregated power used for training. A theoretical analysis based on a first-order Taylor expansion is performed to analyze the structure of the additional error incurred. The experimental results showed a significant decrease in the performance of the methods when the noise increases, especially for monitored appliances with low-power states or complex patterns. The study reveals a strong dependence on the aggregated power structure in the training set and suggests that future methods should focus on learning robust appliance-specific signatures rather than directly regressing from the aggregated signal. |
A Residential Droop-Controlled AC Nanogrid with Power Quality EnhancementAyesha Aslam (ESR01)Harmonic distortion from non-linear loads poses a significant challenge to power quality in residential nanogrids, often requiring complex control strategies and communication between distributed resources. This paper presents a parallel hybrid inverter system for an AC nanogrid that enhances power quality using only decentralized droop-based primary control, without the need for secondary control or communication links. The system features two inverters with strategic placement: one maintains voltage stability at the point of common coupling, while the other directly supplies the harmonic and reactive current demanded by non-linear loads. A compensation mechanism allows the second inverter to dynamically switch from supplying sinusoidal current to injecting targeted harmonic components, effectively isolating distortion from the main grid. Simulation results confirm that this approach significantly reduces voltage distortion at the PCC and ensures balanced power sharing, all while simplifying the control architecture. The proposed method offers a scalable, cost-effective solution for residential nanogrids seeking to integrate diverse loads and distributed energy resources while maintaining high power quality. |