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Novel Applications of Power Converters for Energy Storage and Grid Integration

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 6942

Special Issue Editors


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Guest Editor
Department of Electrical Engineering and Information Technologies, University of Napoli Federico II, 80125 Napoli, Italy
Interests: design and control of power converters for photovoltaics and distributed power generation systems; integration of renewable energy resources in electrical systems; modulation of multilevel converters; design and control of high-efficiency DC–DC converters; design of digital circuits on FPGA
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Guest Editor
Department of Electrical Engineering and Information Technologies, University of Napoli Federico II, 80125 Napoli, Italy
Interests: high-performance dynamic drives with PM motors; power electronic converters; fault tolerance in multilevel converters; power electronic transformers (PETs); energy storage for the integration of renewable energy sources and recharge stations for electric vehicles
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Electrical Engineering and Information Technologies, University of Napoli Federico II, 80125 Napoli, Italy
Interests: control of electrical drives for battery and hydrogen-based electric propulsion in railway and aircraft transportation; modeling and control of wind power generation systems; state-of-health estimation of battery energy storage systems

Special Issue Information

Dear Colleagues,

Nowadays, power converters play a crucial role in new energy grid access, power generation, and in the reliable and efficient interconnection and integration of different energy systems and technologies. Therefore, the development of novel applications for grid power converters is a rapidly evolving field of interest for scientific researchers and industrial technicians.

In this scenario, power converters will be instrumental in enabling the use of energy storage systems for stationary and mobile applications, renewable energy production, distributed generation, flexible AC/DC transmission, and electric drives for transportation. A recent area of research is the development of inherent grid-supporting functionalities, as provided by grid-forming control strategies to counteract the low inertia of new power systems. Unlike the conventional grid-following converters that rely on the stability of the existing grid, the grid-forming converters can actively contribute to grid stability.

The penetration of these converters is increasing rapidly, encouraging energy storage to become an indispensable component in future modern power systems to provide supply-demand balancing, power smoothing, load levelling, and power quality.

By unlocking these new functionalities, power converters are poised to play a transformative role in the next future. The ever-increasing need for integrated energy systems poses new issues in terms of their design, control methods, and interaction with grid.

This Special Issue seeks to address the challenges and potential solutions related to novel applications of power converters in modern power systems with a high level of penetration of energy storage, renewables, and full-electric road vehicles.

The topics of interest for publication include, but are not limited to the following:

  • The modeling, design, control, stability analysis, and reliability of power electronic converters;
  • Energy storage systems (batteries, fuel cells, supercap, etc.);
  • Novel power converter topologies for grid integration with renewables and storage systems;
  • The control and modulation of conventional and multilevel power converter topologies for renewable energy production and flexible transmission systems;
  • Advanced control techniques and grid-supporting functionalities of power converters;
  • The control and stability of power-converter-dominated microgrids;
  • The grid integration of electric vehicles.

Dr. Marino Coppola
Prof. Dr. Adolfo Dannier
Dr. Emanuele Fedele
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • power converters
  • energy storage systems
  • control techniques
  • electric vehicles
  • renewables
  • grid integration

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Related Special Issue

Published Papers (9 papers)

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Research

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19 pages, 5281 KiB  
Article
Bidirectional Energy Transfer Between Electric Vehicle, Home, and Critical Load
by Ștefan-Andrei Lupu and Dan Floricău
Energies 2025, 18(9), 2167; https://doi.org/10.3390/en18092167 - 23 Apr 2025
Viewed by 405
Abstract
In the transition to a sustainable energy system, the integration of electric vehicles into residential energy systems is an innovative solution for increasing energy resilience and optimizing electricity consumption. This article presents a bidirectional AC/DC converter capable of charging the electric vehicle battery [...] Read more.
In the transition to a sustainable energy system, the integration of electric vehicles into residential energy systems is an innovative solution for increasing energy resilience and optimizing electricity consumption. This article presents a bidirectional AC/DC converter capable of charging the electric vehicle battery under normal conditions, while providing power to a critical consumer in the event of a power grid outage. The simulations performed show us the functionality of this converter, demonstrating its efficiency in ensuring the continuity of supply. Full article
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16 pages, 3818 KiB  
Article
Design and Control of an Enhanced Grid-Tied PV CHB Inverter
by Marino Coppola, Adolfo Dannier, Emanuele Fedele, Gerardo Saggese and Pierluigi Guerriero
Energies 2025, 18(8), 2056; https://doi.org/10.3390/en18082056 - 17 Apr 2025
Viewed by 275
Abstract
This paper deals with the design and control of an enhanced grid-tied photovoltaic (PV) cascaded H-Bridge (CHB) inverter, which suffers from issues related to operation in the overmodulation region in the case of a deep mismatch configuration of PV generators (PVGs). This can [...] Read more.
This paper deals with the design and control of an enhanced grid-tied photovoltaic (PV) cascaded H-Bridge (CHB) inverter, which suffers from issues related to operation in the overmodulation region in the case of a deep mismatch configuration of PV generators (PVGs). This can lead to reduced system performance in terms of maximum power point tracking (MPPT) efficiency, or even instability (i.e., a lack of control action). The proposed solution is to insert into the cascade a power cell fed by a battery energy storage system (BESS) with the aim of providing an additional power contribution. The latter is useful to reduce the modulation index of the cell, delivering more power than the others when a preset threshold is crossed. Moreover, a suitable hybrid modulation method is used to achieve the desired result. A simulated performance in a PLECS environment proves the viability of the proposed solution and the effectiveness of the adopted control strategy. Full article
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14 pages, 959 KiB  
Article
Online Identification of Differential Order in Supercapacitor Fractional-Order Models: Advancing Practical Implementation
by Arsalan Rasoolzadeh, Sayed Amir Hashemi and Majid Pahlevani
Energies 2025, 18(8), 1876; https://doi.org/10.3390/en18081876 - 8 Apr 2025
Viewed by 277
Abstract
Supercapacitors (SCs) are increasingly recognized as a reliable energy storage solution in various industrial applications due to their high power density and exceptionally long lifespan. SC-powered systems demand precise parameter identification to enable effective energy management. Although various approaches exist for the offline [...] Read more.
Supercapacitors (SCs) are increasingly recognized as a reliable energy storage solution in various industrial applications due to their high power density and exceptionally long lifespan. SC-powered systems demand precise parameter identification to enable effective energy management. Although various approaches exist for the offline identification of SCs, some parameters depend on factors such as state of health (SoH), aging, temperature, and their combination. Consequently, the variation in parameter values under different conditions highlights the importance of online identification based on a dynamic model structure. Among various SC models proposed in the literature, fractional-order models offer greater accuracy, making them a superior choice for SC modeling. However, the conventional formulation in these models requires a very long window of samples and coefficients for filter implementation. Additionally, due to the several orders of magnitude difference in the elements of matrices, numerical instability can arise, leading to errors and drift in the final calculations. In this paper, a novel online identification approach is introduced for differential order estimation in fractional-order SC models. The proposed method significantly shortens the long window while maintaining accuracy, making it feasible for implementation in low-cost microcontrollers and a viable solution for real-world applications. In addition, the proposed method addresses the drift error by applying online least squares error estimation that aligns it with its offline estimated value. Full article
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33 pages, 7876 KiB  
Article
Methods for the Investigation and Mitigation of Conducted Differential-Mode Electromagnetic Interference in Commercial Electrical Vehicles
by Per Widek and Mats Alaküla
Energies 2025, 18(4), 859; https://doi.org/10.3390/en18040859 - 12 Feb 2025
Viewed by 750
Abstract
One of the main challenges as the market for fully commercial electrified vehicles quickly expands is predicting the electromagnetic interference (EMI) in traction voltage systems (TVSs) in differential mode (DM) and common mode (CM). The number of subsystems connected to vehicle TVSs is [...] Read more.
One of the main challenges as the market for fully commercial electrified vehicles quickly expands is predicting the electromagnetic interference (EMI) in traction voltage systems (TVSs) in differential mode (DM) and common mode (CM). The number of subsystems connected to vehicle TVSs is increasing, and thus, so are the electromagnetic compatibility (EMC) requirements. These requirements should make sure that neither the function nor lifetime of any source or load is affected by another, but experience shows that they are often insufficient. The purpose of this article is to show how circuit simulations can complement these requirements and that a generalized artificial network/line impedance stabilization network (LISN) is insufficient to correctly predict the EMI situation of a real vehicle. This article presents a method for complexity reduction in TVS DM simulations and a comparison with the usage of LISN to predict the EMI between subsystems; the article also addresses how to mitigate the EMI with DM filters for the subsystems. The proposed method creates a foundation for a faster and safer development process. The simulation model’s development includes a traction battery and TVS subsystems. It is found that a standardized LISN does not reflect the behavior of a commercial TVS and cannot be used solely to judge if a subsystem will operate as intended within a TVS without creating EMI. A change in switching frequency in the DUT can cause severe resonance between TVS subsystems, but this is not seen with a LISN. The conclusion of the article is that LISN can provide a false sense of security and that calibrated simulation models of a complete TVS are necessary to predict the behavior in that TVS; this study also highlights the importance of using DM filters to ensure protection against resonance frequencies. Full article
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16 pages, 9719 KiB  
Article
Optimal Variable Frequency Soft Switching for Interleaved Grid Tied Inverters in Electric Vehicle Charging Applications
by Youssef A. Fahmy, Matthew Jahnes and Matthias Preindl
Energies 2024, 17(23), 6077; https://doi.org/10.3390/en17236077 - 3 Dec 2024
Viewed by 856
Abstract
Synchronized variable frequency soft-switching is analyzed and implemented in a 3-phase bidirectional grid-tied inverter. The common-mode connected topology and control allow for independent analysis of a single phase leg before six are combined into two interleaved, 3-phase inverters. Effective operation is enabled by [...] Read more.
Synchronized variable frequency soft-switching is analyzed and implemented in a 3-phase bidirectional grid-tied inverter. The common-mode connected topology and control allow for independent analysis of a single phase leg before six are combined into two interleaved, 3-phase inverters. Effective operation is enabled by discretizing the variable switching frequencies before synchronizing them with a control signal. The resulting inverter can operate at any power factor at power levels up to 50 kVA while maintaining zero-voltage switching (ZVS) throughout the grid cycle. Formal conditions for soft-switching and methods for achieving ZVS while maintaining global synchronization are presented. These conditions are then verified in a simulation. Finally, results for different power factors with and without interleaving are demonstrated in a prototype that achieves >98.1% efficiency when converting all real power. Full article
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19 pages, 4201 KiB  
Article
Novel Droop-Based Techniques for Dynamic Performance Improvement in a Linear Active Disturbance Rejection Controlled-Dual Active Bridge for Fast Battery Charging of Electric Vehicles
by Armel Asongu Nkembi, Danilo Santoro, Fawad Ahmad, Iñigo Kortabarria, Paolo Cova, Emilio Sacchi and Nicola Delmonte
Energies 2024, 17(20), 5171; https://doi.org/10.3390/en17205171 - 17 Oct 2024
Viewed by 1043
Abstract
Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging [...] Read more.
Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging stations. A critical issue in EV battery charging is the smooth transition between charging stages (constant current and constant voltage) which can disrupt converter performance. This work proposes a novel feedforward control method using a combination of droop-based techniques combined with a sophisticated linear active disturbance rejection control system applied to a single-phase shift-modulated dual active bridge. This combination ensures a seamless transition between charging stages and enhances the robustness of the system against fluctuations in both input voltage and load. Numerical simulations using MATLAB/Simulink R2024a demonstrated that this approach not only enables smooth charging but also reduces the peak input converter current, allowing for the use of lower-rated components in the converter design. This translates to potentially lower costs for building these essential charging stations and faster adoption of EVs. Full article
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13 pages, 4866 KiB  
Article
A New Topology of Multi-Input Bidirectional DC-DC Converters for Hybrid Energy Storage Systems
by Simone Cosso, Alessandro Benevieri, Mario Marchesoni, Massimiliano Passalacqua, Luis Vaccaro and Paolo Pozzobon
Energies 2024, 17(20), 5120; https://doi.org/10.3390/en17205120 - 15 Oct 2024
Viewed by 1170
Abstract
A new topology of multi-input bidirectional DC-DC converters is proposed in this paper. The converter has a boost behavior, i.e., the output voltage is higher than the sum of the input voltages. This family of converters is particularly suited for hybrid energy storage [...] Read more.
A new topology of multi-input bidirectional DC-DC converters is proposed in this paper. The converter has a boost behavior, i.e., the output voltage is higher than the sum of the input voltages. This family of converters is particularly suited for hybrid energy storage systems, where different DC sources are connected together and where the output voltage is significantly higher than the voltage of a single storage. The proposed converter reduces the number of required switches, leading to higher efficiency and reduced complexity compared to traditional n-input converters. The new topology demonstrates superior performance by enabling higher efficiency with fewer components. A dedicated control, based on PI controllers, is provided to ensure stable operation under dynamic conditions. The effectiveness of the proposed solution is tested using experimental results on a four-input 20 A/100 V converter prototype. Full article
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Review

Jump to: Research

31 pages, 6978 KiB  
Review
An Overview of Recent AI Applications in Combined Heat and Power Systems
by Ashkan Safari and Arman Oshnoei
Energies 2025, 18(11), 2891; https://doi.org/10.3390/en18112891 - 30 May 2025
Viewed by 120
Abstract
Combined heat and power (CHP) systems are among the important components for enhancing energy efficiency and sustainability by simultaneously generating electricity and useful thermal energy, reducing waste and costs. Consequently, the effective control of these systems is considered important. To that end, this [...] Read more.
Combined heat and power (CHP) systems are among the important components for enhancing energy efficiency and sustainability by simultaneously generating electricity and useful thermal energy, reducing waste and costs. Consequently, the effective control of these systems is considered important. To that end, this paper provides a comprehensive review of the intelligent methodologies applied to CHP systems, emphasizing their prevalence in the USA and Europe through statistical insights. It outlines the mathematical foundations of CHP systems, analyzing the advancements in intelligent control methods for optimal planning, economic dispatch, and cost minimization. Artificial Intelligence (AI) models, such as Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Random Forest, are described and applied to a simulated CHP system. The Key Performance Indicators (KPIs) derived from these models demonstrate their efficacy for optimizing CHP performance. This paper also highlights the impact of AI-driven models for enhancing CHP system efficiency, while identifying the challenges in AI-CHP integration and envisioning CHP systems as important components of future sustainable energy systems. Full article
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29 pages, 2182 KiB  
Review
Optimization Techniques for Low-Level Control of DC–AC Converters in Renewable-Integrated Microgrids: A Brief Review
by Guilherme Vieira Hollweg, Gajendra Singh Chawda, Shivam Chaturvedi, Van-Hai Bui and Wencong Su
Energies 2025, 18(6), 1429; https://doi.org/10.3390/en18061429 - 13 Mar 2025
Viewed by 608
Abstract
The optimization of low-level control for DC–AC power converters is crucial for enhancing efficiency, stability, and adaptability in modern power systems. With the increasing penetration of renewable energy sources and the shift toward decentralized grid architectures, advanced control strategies are needed to address [...] Read more.
The optimization of low-level control for DC–AC power converters is crucial for enhancing efficiency, stability, and adaptability in modern power systems. With the increasing penetration of renewable energy sources and the shift toward decentralized grid architectures, advanced control strategies are needed to address challenges such as reduced system inertia and dynamic operating conditions. This paper provides a concise review of key optimization techniques for low-level control, highlighting their advantages, limitations, and applicability. Additionally, emerging trends, such as artificial intelligence (AI)-based real-time control algorithms and hybrid optimization approaches, are explored as potential enablers for the next generation of power conversion systems. Notably, no single optimized control technique universally outperforms others, as each involves trade-offs in mathematical complexity, robustness, computational burden, and implementation feasibility. Therefore, selecting the most appropriate control strategy requires a thorough understanding of the specific application and system constraints. Full article
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