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

Deadline for manuscript submissions: 25 June 2026 | Viewed by 19821

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Special Issue Editors

Dr. Mohammad Alnajideen

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Guest Editor

College of Physical Sciences and Engineering, Cardiff University, Cardiff CF24 3AA, UK
Interests: hydrogen; ammonia; energy systems
Special Issues, Collections and Topics in MDPI journals

Dr. Hao Shi

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Guest Editor

The Institute of Reactive Flows and Diagnostics, Technical University of Darmstadt, 64287 Darmstadt, Germany
Interests: ammonia/hydrogen combustion; internal combustion engine; optical diagnostics; combined heating and power; heat pump
Special Issues, Collections and Topics in MDPI journals

Dr. Paweł Czyżewski

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Guest Editor

Institute of Thermal Science, Poznan University of Technology, Piotrowo 3, 60-965 Poznan, Poland
Interests: flameless combustion; biomass thermal conversion; pollutant emission

Special Issue Information

Dear Colleagues,

This Special Issue of Energies is dedicated to advancing the understanding of novel and emerging energy systems, bridging the gap between conventional and renewable technologies while exploring future directions and industry insights. Bringing together a collection of cutting-edge research papers, this Special Issue provides a comprehensive overview of the latest advancements in energy technologies that are shaping the future of global energy production and consumption.

The aim of this Special Issue is to capture the multidisciplinary nature of modern energy research, ranging from technological innovations in conventional energy systems to the development and integration of renewable sources such as solar, wind and bioenergy, and systems powered by renewable fuels such as ammonia and hydrogen. It includes thorough literature reviews and research studies that assess the progress, challenges and opportunities in novel energy systems, highlighting both their potential and limitations in achieving a more sustainable energy landscape.

Technological advancements are a key focus, with contributions discussing emerging trends in energy storage, smart grids and hybrid systems, as well as the role of digitalization, artificial intelligence and data-driven technologies in optimizing energy efficiency and reducing emissions. The Special Issue also features insights from industry professionals, offering a practical perspective on how these innovations are being implemented in real-world applications and the feedback loops driving further improvements.

In summary, this Special Issue serves as a platform for researchers, engineers and industry stakeholders to share knowledge, examine recent advancements and explore the future of energy systems, with the ultimate goal of promoting a transition to cleaner, more efficient and resilient energy solutions.

Dr. Mohammad Alnajideen
Dr. Hao Shi
Dr. Paweł Czyżewski
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 250 words) can be sent to the Editorial Office for assessment.

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

energy innovation
energy flexibility
hybrid energy systems
ammonia/hydrogen for power
power electronics in renewable energy

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Published Papers (10 papers)

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Research

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20 pages, 2677 KB

Open AccessArticle

Effect of Illumination Colour on the Growth and Energetic Properties of Chlorella vulgaris for Bioenergy Applications

by Pawel Czyzewski, Przemyslaw Matuszak, Marcelina Malecka, Joanna Jojka, Ahmad M. S. H. Al-Moftah, Hao Shi, Mohammad Alnajideen and Agustin Valera-Medina

Energies 2026, 19(6), 1572; https://doi.org/10.3390/en19061572 - 23 Mar 2026

Viewed by 531

Abstract

Microalgae are a promising third-generation biomass resource due to their high photosynthetic efficiency, rapid growth rates, capacity to accumulate energy-rich biochemical fractions, and efficient utilisation of carbon dioxide (CO₂). In this study, the effect of illumination colour on the growth and energetic properties of Chlorella vulgaris cultivated in laboratory-scale photobioreactors was investigated. Four independent cultivation cycles were conducted under controlled conditions using a 16 h light/8 h dark photoperiod, temperatures of 20–30 °C, and aeration with air enriched with 10% CO₂. Cultures were illuminated using six light colours: plant-specific, white, green, red, blue, and ultraviolet. Biomass productivity was quantified, and the higher heating value (HHV) of the produced biomass was determined by bomb calorimetry. In addition, proximate (technical) analysis was performed for Chlorella vulgaris and compared with Chlorella pyrenoidosa, Spirulina, and Fucus vesiculosus (bladderwrack). The results showed that white illumination promoted both the highest biomass growth and the highest HHV for Chlorella vulgaris (15.08 MJ·kg⁻¹), while ultraviolet illumination had a disruptive effect, leading to the lowest growth and calorific value (11.49 MJ·kg⁻¹). Comparative analysis revealed that Chlorella pyrenoidosa exhibited the most favourable energetic properties; however, Chlorella vulgaris remains attractive for cultivation due to its robustness and broad tolerance to operating conditions. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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21 pages, 22356 KB

Open AccessArticle

Carbon Black–Enhanced Polyethylene Wax Phase Change Materials for Efficient Photothermal Energy Conversion and Storage in Mobile Heating Systems

by Martyna Szatkowska, Piotr Szatkowski, Katarzyna Suchorowiec, Ewelina Radomska and Kinga Pielichowska

Energies 2026, 19(5), 1162; https://doi.org/10.3390/en19051162 - 26 Feb 2026

Viewed by 542

Abstract

Organic phase change materials (PCMs) have been used and studied for many years. In this work, we focus on an industrially available PCM—polyethylene waxes (PEW) modified with seven types of carbon black (CB) exhibiting different properties. Carbon black (CB) was selected as a more cost-effective modifier compared to carbon nanomaterials, as it is easier to implement industrially and capable of converting and storing thermal energy. The experiments were designed to evaluate the thermal properties and photothermal conversion efficiency of PCMs modified with different grades of carbon black. The influence of carbon black on selected PCM properties was investigated using differential scanning calorimetry (DSC), thermogravimetric analysis (TG), scanning electron microscopy (SEM), and laser flash analysis (LFA). Furthermore, the photothermal conversion capability was evaluated. The results indicate that modification with carbon black decreases the phase transition enthalpy for most formulations, with reductions ranging from 8 to 12% for 1 wt.% CB to 10–15% for 2.5 wt.% CB. At the same time, an improvement in the thermal conductivity of PCMs modified with carbon black was observed, with the best performance achieved for N234 carbon black, showing an increase of approximately 17–18% in the 25–55 °C temperature range. The ratio of the heat of solidification to the heat of melting (Qs/Qm) for most samples was approximately 0.90–0.98, indicating excellent thermal cycling stability. The highest photothermal conversion efficiency was observed for samples modified with N234 and N330; these materials exhibited the greatest temperature rise, reaching approximately 135 °C in about 15 min, due to enhanced light absorption of PCMs by carbon black. Overall, the results confirm that PEW/CB systems demonstrate a good balance between absorption, heat generation, and controlled phase-change behavior, making them promising candidates for solar–thermal energy storage and conversion applications. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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23 pages, 2604 KB

Open AccessArticle

Multi-Criteria Model Predictive Controller for Hybrid Heating Systems in Buildings

by Ali Soleimani, Paul Davidsson, Reza Malekian and Romina Spalazzese

Energies 2025, 18(21), 5839; https://doi.org/10.3390/en18215839 - 5 Nov 2025

Viewed by 1046

Abstract

With more hybrid heating systems available, there is a need to optimize energy use intelligently from the end-consumer perspective. This paper focuses on a multi-criteria heating system optimization to optimize cost, carbon emission, and comfort level of building occupants. A discrete Multi-Objective Model Predictive Controller (MO-MPC) algorithm is proposed to optimally utilize two heating sources connected to a building, namely district heating (DH) and a building-integrated electrical heat pump (HP). The model is tested on a real-world building case simulated with a gray box building model. The results are compared to a conventional PID controller as well as the MPC scheme, each with a single heating input, and eight different cases are constructed to make this comparison more visible. The results indicate that, using MO-MPC, a cost saving of up to 10% and emission saving of up to 13% can be reached without additional thermal discomfort, while the potential savings on cost and emission with the hybrid system can be up to 25% and 77%, respectively. Further, a sensitivity analysis on price and emission parameters is conducted to investigate the changes in the provided solution. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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20 pages, 4023 KB

Open AccessArticle

Forecast-Driven Climate Control for Smart Greenhouses: Energy Optimization Using LSTM Model

by Abdulaziz Aborujilah, Mohammed Al-Sarem and Marwan Alabed Abu-Zanona

Energies 2025, 18(21), 5821; https://doi.org/10.3390/en18215821 - 4 Nov 2025

Cited by 3 | Viewed by 2579

Abstract

Greenhouses play a vital role in modern agriculture by providing controlled environments for year-round crop production. However, climate regulation within these structures accounts for a significant portion of their energy consumption, often exceeding 50% of operational costs. Current greenhouse systems predominantly rely on reactive control strategies, leading to energy inefficiency and unstable internal conditions. Addressing this gap, the present study develops a machine learning-based framework that leverages time series forecasting models—specifically Long Short-Term Memory (LSTM)—that predict key climate parameters and generate optimal actuator control recommendations. The system utilizes multivariate environmental data to forecast temperature, humidity, and CO₂ levels and minimize a composite energy proxy through proactive adjustments to heating, ventilation, and lighting systems. Experimental results demonstrate high prediction accuracy (R² = 0.9835) and significant improvements in energy efficiency. By integrating predictive analytics with real-time sensor feedback, the proposed approach supports intelligent, energy-aware decision-making and advances the development of smart agriculture through proactive greenhouse climate management. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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37 pages, 4331 KB

Open AccessArticle

Mitigating Energy Losses Under Incremental Load Variations in Distributed Power-Flow Systems While Ensuring User Comfort

by Sadiq Muhammad, Saher Javaid, Iacovos Ioannou, Yuto Lim and Yasuo Tan

Energies 2025, 18(21), 5716; https://doi.org/10.3390/en18215716 - 30 Oct 2025

Viewed by 647

Abstract

Renewable energy sources (RESs) such as photovoltaic (PV) and fuel cells (FCs) introduce variability that complicates reliable, loss-aware operation of distributed power-flow systems (DPFSs) in smart homes. Frequent charge/discharge cycling of energy storage systems (ESSs) can inflate losses and jeopardize user comfort when generation and demand are mismatched. This paper addresses the gap in multi-load, multi-source coordination under fluctuating RESs by proposing a Multiple-Load Power-Flow Assignment (MPFA) framework that explicitly minimizes storage-related losses while maintaining demand satisfaction. We evaluate four logical interconnection scenarios among generators (PGs), loads (PLs), and storage (PSs), and compare three control algorithms—total-demand-based (TDPF), adaptive-demand-based (ADPF), and grid-based (GBPF). Using measured PV/FC data across seasons, MPFA consistently reduces storage-related losses as interconnections increase, with GBPF guaranteeing full daily demand satisfaction by flexibly supplementing local generation with grid power. ADPF performs strongly when grid support is limited by prioritizing critical loads and optimizing storage utilization. The results provide actionable guidance for designing smart-home energy management that emphasizes sustainability, reliability, and user comfort. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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28 pages, 4828 KB

Open AccessArticle

Study on Determining the Efficiency of a High-Power Hydrogenerator Using the Calorimetric Method

by Elisabeta Spunei, Dorian Anghel, Gheorghe Liuba, Cristian Paul Chioncel and Mihaela Martin

Energies 2025, 18(18), 4813; https://doi.org/10.3390/en18184813 - 10 Sep 2025

Viewed by 1021

Abstract

The global energy crisis demands efficient electricity production solutions, especially for isolated communities where hydraulic energy can be harnessed sustainably. This paper presents a case study analyzing the efficiency of a 13,330 kW hydrogenerator, consisting of a bulb-type hydro-aggregate using the calorimetric method—a viable alternative when testing at nominal load is not feasible due to technical limitations. The method involves measuring the thermal energy absorbed by the cooling water under three operating conditions: no-load unexcited, no-load excited, and symmetric three-phase short-circuit. Measurements followed IEC standards and were conducted with high-precision instruments for temperature, flow, voltage, and current. The results quantify mechanical, ventilation, iron, and copper losses, as well as additional losses via radiation and convection. Thermal analysis revealed significant heat accumulation in the rotor and stator windings, indicating the need for improved cooling solutions. The calorimetric method enables efficiency evaluation without interrupting generator operation, offering a valuable tool for diagnostics, predictive maintenance, and informed decisions on modernization. Furthermore, integrating an intelligent operational control system could enhance efficiency and improve the quality of the supplied energy, supporting long-term sustainability in hydroelectric power generation. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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22 pages, 3550 KB

Open AccessArticle

Economic Feasibility of Using Municipal Solid Waste and Date Palm Waste for Clean Energy Production in Qatar

by Ahmad Mohamed S. H. Al-Moftah, Mohammad Alnajideen, Fatima Alafifi, Pawel Czyzewski, Hao Shi, Mohammad Alherbawi, Rukshan Navaratne and Agustin Valera-Medina

Energies 2025, 18(4), 988; https://doi.org/10.3390/en18040988 - 18 Feb 2025

Cited by 6 | Viewed by 4152

Abstract

The transition to clean energy is crucial for mitigating the impacts of climate change and achieving sustainable development. Reliance on fossil fuels, which are integral to manufacturing and transportation, remains a major contributor to greenhouse gas (GHG) emissions. Biomass gasification presents a renewable energy alternative that can significantly reduce emissions. However, proper disposal of municipal solid waste (MSW) and agricultural residues, such as date palm waste (DPW), is an increasing global challenge, including in Qatar. This study evaluates the economic feasibility of implementing an MSW and DPW gasification plant for clean electricity generation in Qatar. The country’s growing population and economic development have led to substantial waste production, making it an ideal location for waste-to-energy (WTE) initiatives. Using discounted cash flow (DCF) analysis, the study estimates the capital cost of a 373 MW_th facility at approximately $12.07 million, with annual operating costs of about $4.09 million and revenue of $26.88 million in 2023. The results indicate a net present value (NPV) of $245.77 million, a return on investment (ROI) of 84.80%, a payback period of approximately 5 years over a 20-year project lifetime and a net reduction of 206,786 tonnes CO₂ annually. These findings demonstrate the economic viability of biomass gasification in Qatar while contributing to reduced GHG emissions and advancing the country’s sustainability goals under Qatar National Vision 2030. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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Review

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32 pages, 2680 KB

Open AccessReview

A Review of Multi-Port Converter Architecture in Hydrogen-Based DC Microgrid

by Qiyan Wang, Kosala Gunawardane and Li Li

Energies 2025, 18(24), 6487; https://doi.org/10.3390/en18246487 - 11 Dec 2025

Cited by 2 | Viewed by 1178

Abstract

With the rapid advancement of hydrogen-based direct current microgrid (H₂-DCMG) technology, multi-port converters (MPCs) have emerged as the pivotal interface for integrating renewable power generation, energy storage, and diverse DC loads. This paper systematically reviews the current research status and development trends of isolated and non-isolated MPC topologies within hydrogen-based DC microgrids. Firstly, it analyses the interface requirements for typical distributed energy sources (DER) such as photovoltaics (PV), wind turbines (WT), fuel cells (FC), battery energy storage (BESS), proton exchange membrane electrolyzers (PEMEL), and supercapacitors (SC). Secondly, it classifies and evaluates existing MPC topologies, clarifying the structural characteristics, technical advantages, and challenges faced by each type. Results indicate that non-isolated topologies offer advantages such as structural simplicity, high efficiency, and high power density, making them more suitable for residential and small-scale microgrid applications. Isolated topologies, conversely, provide electrical isolation and modular scalability, rendering them appropriate for high-voltage electrolytic hydrogen production and industrial scenarios with stringent safety requirements. Finally, the paper identifies current research gaps and proposes that future efforts should focus on exploring topology optimization, system integration design, and reliability enhancement. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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38 pages, 3977 KB

Open AccessEditor’s ChoiceReview

Biomass for Residential Heating: A Review of Technologies, Applications, and Sustainability Aspects

by Jakub Katerla and Krzysztof Sornek

Energies 2025, 18(22), 5875; https://doi.org/10.3390/en18225875 - 7 Nov 2025

Cited by 2 | Viewed by 3343

Abstract

Biomass has long been a major source of energy for residential heating and, in recent decades, has regained attention as a renewable alternative to fossil fuels. This review explores the current state and prospects of domestic biomass-based heating technologies, including biomass-fired boilers, local space heaters, and hybrid systems that integrate biomass with complementary renewable energy sources to deliver heat, electricity, and cooling. The review was conducted to identify key trends, performance data, and innovations in conversion technologies, fuel types, and efficiency enhancement strategies. The analysis highlights that biomass is increasingly recognized as a viable energy carrier for energy-efficient, passive, and nearly zero-energy buildings, particularly in cold climates where heating demand remains high. The analysis of the available studies shows that modern biomass-fired systems can achieve high energy performance while reducing environmental impact through advanced combustion control, optimized heat recovery, and integration with low-temperature heating networks. Overall, the findings demonstrate that biomass-based technologies, when designed and sourced efficiently and sustainably, can play a significant role in decarbonizing the residential heating sector and advancing nearly zero-energy building concepts. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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Other

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38 pages, 6294 KB

Open AccessSystematic Review

Machine Learning-Driven Advancements in Electric Motorcycles: A Systematic Review of Electric Motors, Energy Storage, Charging Technologies, and Electronic Components

by Lukasz Pawlik, Jacek Lukasz Wilk-Jakubowski, Krzysztof Podosek and Grzegorz Wilk-Jakubowski

Energies 2025, 18(17), 4529; https://doi.org/10.3390/en18174529 - 26 Aug 2025

Cited by 2 | Viewed by 3161

Abstract

The integration of artificial intelligence (AI) and machine learning (ML) technologies is rapidly transforming the design, operation, and optimization of electric motorcycles. This review analyzes research published between 2015 and 2024, focusing on how ML algorithms enhance performance, energy efficiency, diagnostics, and charging strategies across four key domains: electric motors, energy storage, charging systems, and electronic components. The review highlights state-of-the-art solutions such as torque and range prediction using LSTM/GRU models, predictive maintenance via CNNs and autoencoders, energy flow control in hybrid battery–supercapacitor systems using reinforcement learning, and federated learning for privacy-preserving embedded applications. Comparative insights reveal quantifiable performance gains over traditional methods, while integrated frameworks are proposed for linking ML diagnostics, Vehicle-to-Grid (V2G) functionalities, and renewable energy integration. The paper concludes with targeted recommendations for future research, including lightweight edge-deployable models, Explainable AI for safety-critical applications, and the fusion of intelligent charging with eco-design principles, aiming to enable intelligent, sustainable, and high-performance electric motorcycle systems. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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