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Energies
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Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies
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Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (20 June 2025) | Viewed by 6886

Special Issue Editors

Prof. Dr. Sebastijan Seme

E-Mail Website
Guest Editor
Faculty of Energy Technology, University of Maribor, Hočevarjev trg 1, 8270 Krško, Slovenia
Interests: modeling and optimization; energy efficiency; power electronics; photovoltaic systems; renewable energy sources
Special Issues, Collections and Topics in MDPI journals
Dr. Klemen Sredenšek

E-Mail Website1 Website2
Guest Editor
Faculty of Energy Technology, University of Maribor, Hočevarjev trg 1, 8270 Krško, Slovenia
Interests: modeling and optimization; energy efficiency; power electronics; photovoltaic systems; renewable energy sources
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the integration of renewable energy sources and energy storage systems becomes increasingly crucial for the sustainability and resilience of modern electrical networks, understanding and optimizing their penetration is essential. This transition towards a more sustainable energy system presents significant challenges, as well as opportunities, in modeling, analysis, and the effective management of these resources within electrical networks.

This Special Issue aims to present and disseminate the latest research findings and advancements related to the modeling and analysis of the penetration of renewable energy sources and storage systems in electrical networks. We seek contributions that explore innovative approaches, methodologies, and technologies, incorporating renewable energy and storage solutions, to enhance the efficiency, reliability, and stability of electrical networks.

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

  • Modeling techniques for renewable energy integration in electrical networks;
  • Analysis of the impact of renewable energy sources on grid stability and reliability;
  • The role of storage systems in alleviating the demand on electrical networks;
  • Smart grid technologies for renewable energy and storage management;
  • Grid modernization to accommodate high levels of renewable penetration;
  • Techniques for optimizing renewable energy systems for low-voltage network usage;
  • Economic and environmental impacts of renewable energy and storage systems;
  • Electricity management systems in the low-voltage network (domestic use);
  • Policy and regulatory aspects of renewable energy and storage penetration;
  • Market impacts on the integration of renewable energy sources.

Prof. Dr. Sebastijan Seme
Dr. Klemen Sredenšek
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • renewable energy sources
  • electrical network
  • energy storage systems
  • modeling and analysis
  • optimization

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Related Special Issue

Published Papers (6 papers)

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Research

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13 pages, 1235 KiB  
Article
Effects of Climate Change on Wind Power Generation: A Case Study for the German Bight
by Reinhold Lehneis
Energies 2025, 18(13), 3287; https://doi.org/10.3390/en18133287 - 23 Jun 2025
Viewed by 532
Abstract
Driven by the demands of climate change mitigation, many countries have begun large-scale electricity production from variable renewables, such as solar PV and wind power. Electricity production from wind turbines, in particular, strongly depends on local weather conditions and their changes caused by [...] Read more.
Driven by the demands of climate change mitigation, many countries have begun large-scale electricity production from variable renewables, such as solar PV and wind power. Electricity production from wind turbines, in particular, strongly depends on local weather conditions and their changes caused by climate change. Thus, for many countries with a high share of wind power generation, such as Germany, two essential questions arise: how will climate change affect electricity production, and how strong will be this impact for different RCPs? To better assess the impact on existing onshore wind turbines, spatially and temporally resolved data on their power generation are required. In order to create such disaggregated data, this study uses a physical simulation model and climate data modified for the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. To investigate the effects on a significant region with very high wind power generation in Germany, the numerical simulations were carried out on an ensemble of 22 onshore wind turbines with an installed capacity of 65.5 MW in the German Bight. After model validation, the power generation from this turbine ensemble was simulated for the high-wind year 2008 and the low-wind year 2010. The simulation results are presented with a high temporal resolution, and the observed changes are discussed for the applied RCPs. In summary, the resulting wind power generation of the entire plant ensemble decreases with increasing RCP to values of up to nearly 3 GWh for both years. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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34 pages, 3449 KiB  
Article
Impacts of Inertia and Photovoltaic Integration on Existing and Proposed Power System Transient Stability Parameters
by Ramkrishna Mishan, Xingang Fu, Chanakya Hingu and Mohammed Ben-Idris
Energies 2025, 18(11), 2915; https://doi.org/10.3390/en18112915 - 2 Jun 2025
Viewed by 500
Abstract
The integration of variable distributed energy sources (DERs) can reduce overall system inertia, potentially impacting the transient response of both conventional and renewable generators within electrical grids. Although transient stability indicators—for instance, the Critical Clearing Time (CCT), fault-induced short-circuit current ratios, and machine [...] Read more.
The integration of variable distributed energy sources (DERs) can reduce overall system inertia, potentially impacting the transient response of both conventional and renewable generators within electrical grids. Although transient stability indicators—for instance, the Critical Clearing Time (CCT), fault-induced short-circuit current ratios, and machine parameters, including subtransient–transient reactances and associated time constants—are influenced by total system inertia, their detailed evaluation remains insufficiently explored. These parameters provide standardized benchmarks for systematically assessing the transient stability performance of conventional and photovoltaic (PV) generators as the penetration level of distributed PV systems (PVD1) increases. This study explores the relationship between conventional stability parameters and system inertia across different levels of PV penetration. CCT, a key metric for transient stability assessment, incorporates multiple influencing factors and typically increases with higher system inertia, making it a reliable comparative indicator for evaluating the effects of PV integration on system stability. To investigate this, the IEEE New England 39-bus system is adapted by replacing selected synchronous machines with PVD1 PV units and adjusting the PV penetration levels. The resulting system behavior is then compared to that of the original configuration to evaluate changes in transient stability. The findings confirm that transient and subtransient reactances, along with their respective time constants under fault conditions, are shaped not only by the characteristics of the generator on the faulted line but also by the surrounding network structure and overall system inertia. The newly introduced sensitivity parameters offer insights by capturing trends specific to conventional versus PV-based generators under different inertia scenarios. Notably, transient parameters show similar responsiveness to inertia variations to subtransient ones. This paper demonstrates that in certain scenarios, the integration of low-inertia PV generators may generate insufficient energy, which is not above critical energy during major disturbances, resulting surviving fault and subsequently an infinite CCT. While the integration of PV generators can be beneficial for their own operational performance, it may adversely impact the dynamic behavior and fault response of conventional synchronous generators within the system. This highlights the need for effective planning and control of DER integration to ensure reliable power system operation through accurate selection and application of both conventional and proposed transient stability parameters. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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19 pages, 3253 KiB  
Article
Research on the Modelling and Analysis of the Penetration of Renewable Sources and Storage into Electrical Networks
by Eva Simonič, Sebastijan Seme and Klemen Sredenšek
Energies 2025, 18(9), 2263; https://doi.org/10.3390/en18092263 - 29 Apr 2025
Cited by 1 | Viewed by 468
Abstract
To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. This paper investigates the impact of integrating residential rooftop photovoltaic [...] Read more.
To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. This paper investigates the impact of integrating residential rooftop photovoltaic (PV) systems and battery energy storage systems (BESSs) into low-voltage (LV) distribution networks. A stochastic approach, using the Monte Carlo method, is applied to randomly place PV systems across the network, generating multiple scenarios for power flow simulations in MATLAB Simulink R2024b. The method incorporates real-world consumer load data and grid topology, representing a novel approach in simulating distribution network behaviour accurately. The novelty of this paper lies in its ability to combine stochastic PV placement with real-world load data, providing a more realistic representation of network conditions. The simulation results revealed that widespread PV deployment can lead to overvoltage issues, but the integration of BESSs alongside PV systems mitigates these problems significantly. The findings of this paper offer valuable insights for Distribution Network Operators, aiding in the development of strategies for optimal PV and BESS integration to enhance grid performance. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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12 pages, 2367 KiB  
Article
The Electricity Generation Landscape of Bioenergy in Germany
by Reinhold Lehneis
Energies 2025, 18(6), 1497; https://doi.org/10.3390/en18061497 - 18 Mar 2025
Cited by 2 | Viewed by 785
Abstract
Disaggregated data on electricity generation from bioenergy are very helpful for investigating the economic and technical effects of this form of renewable energy on the German power sector with a high temporal and spatial resolution. But the lack of high-resolution feed-in data for [...] Read more.
Disaggregated data on electricity generation from bioenergy are very helpful for investigating the economic and technical effects of this form of renewable energy on the German power sector with a high temporal and spatial resolution. But the lack of high-resolution feed-in data for Germany makes it necessary to apply numerical simulations to determine the electricity generation from biomass power plants for a time period and geographic region of interest. This article presents how such a simulation model can be developed using public power plant data as well as open information from German TSOs as input data. The physical model is applied to an ensemble of 20,863 biomass power plants, most of which are in continuous operation, to simulate their electricity generation in Germany for the year 2020. For this period, the spatially aggregated simulation results correlate well with the official electricity feed-in from bioenergy. The disaggregated time series can be used to analyze the electricity generation at any spatial scale, as each power plant is simulated with its technical parameters and geographical location. Furthermore, this article introduces the electricity generation landscape of bioenergy as a high-resolution map and at the federal state level with meaningful energy figures, enabling comprehensive assessments of this form of renewable energy for different regions of Germany. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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13 pages, 5072 KiB  
Article
The Impact of Financial Support Mechanisms and Geopolitical Factors on the Profitability of Investments in Solar Power Plants in Slovenia
by Iztok Gornjak, Filip Kokalj and Niko Samec
Energies 2024, 17(22), 5714; https://doi.org/10.3390/en17225714 - 15 Nov 2024
Cited by 1 | Viewed by 994
Abstract
This article examines the impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants within Slovenia. The European Union’s energy policy prioritizes increases in renewable energy sources, aiming to reduce dependency on unstable and volatile fossil [...] Read more.
This article examines the impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants within Slovenia. The European Union’s energy policy prioritizes increases in renewable energy sources, aiming to reduce dependency on unstable and volatile fossil fuel markets. Solar power plants play a vital role in this transition. The energy policy framework also includes mechanisms and support systems to operate such facilities. This article analyzes electricity price trends over the past decade and addresses which support type—guaranteed purchase or operational support—has proven more profitable for investments in solar power plants up to 50 kW in Slovenia, considering economic and geopolitical influences on the electricity market. Although the global energy market has been affected by various significant events in recent years, it was found that the COVID-19 pandemic had minimal impact on the electricity market. In contrast, the onset of the conflict in Ukraine has contributed to rising electricity prices and has influenced the support dynamics essential for the development and sustainability of renewable energy systems. Analyses from the past decade indicate a higher return on investment in solar power plants when operational support mechanisms are chosen over guaranteed purchase support. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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Review

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40 pages, 485 KiB  
Review
A Review of Electricity Price Forecasting Models in the Day-Ahead, Intra-Day, and Balancing Markets
by Ciaran O’Connor, Mohamed Bahloul, Steven Prestwich and Andrea Visentin
Energies 2025, 18(12), 3097; https://doi.org/10.3390/en18123097 - 12 Jun 2025
Cited by 1 | Viewed by 2914
Abstract
Electricity price forecasting plays a fundamental role in ensuring efficient market operation and informed decision making. With the growing integration of renewable energy, prices have become more volatile and difficult to predict, increasing the necessity of accurate forecasting in bidding, scheduling, and risk [...] Read more.
Electricity price forecasting plays a fundamental role in ensuring efficient market operation and informed decision making. With the growing integration of renewable energy, prices have become more volatile and difficult to predict, increasing the necessity of accurate forecasting in bidding, scheduling, and risk management. This paper provides a comprehensive review of point forecasting models for electricity markets, covering classical statistical approaches both with and without exogenous inputs, and modern machine learning and deep learning techniques, including ensemble methods and hybrid architectures. Unlike standard reviews focused solely on the day-ahead market, we assess model performance across day-ahead, intra-day, and balancing markets, with each posing unique challenges due to differences in time resolution, data availability, and market structure. Through this market-specific lens, the paper merges insights from a broad set of studies; identifies persistent challenges, such as data quality, model interpretability, and generalisability; and outlines promising directions for future research. Our findings highlight the strong performance of hybrid and ensemble models in the day-ahead market, the dominance of recurrent neural networks in the intra-day market, and the relative effectiveness of simpler statistical models such as LEAR in the balancing market, where volatility and data sparsity remain critical challenges. Full article
(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)
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