Renewable Energy Revolution: Transforming Africa’s Energy Landscape through Solar, Wind, and Hydropower

This study examines how the plentiful solar, wind, and hydroelectric resources in Africa are transforming the continent's energy landscape. Africa faces significant challenges in achieving energy access and sustainability due to the growth of its population and urbanization. This analysis analyzes the transformational capacity of renewable energy, emphasizing pioneering initiatives like Morocco's Noor Ouarzazate Solar Complex and Kenya's Lake Turkana Wind Project. We examine the economic advantages of decentralized energy systems, such as mini-grids and pay-as-you-go solar solutions, which have empowered millions and invigorated local economies. Progress in hybrid systems and energy storage technologies is essential for improving grid stability and dependability. The success of this revolution depends on strong legislative frameworks, new financial structures, and regional collaboration to address infrastructural deficiencies and regulatory obstacles. This assessment highlights the need for inclusive strategies that include local people and tackle environmental issues related to large-scale projects. Africa is positioned to lead in renewable energy, underscoring the critical need for collaboration among governments, corporate sectors, and foreign partners to facilitate this transition. By using its extensive renewable resources, Africa may attain energy security, economic development, and environmental sustainability, therefore fostering a resilient future. Citation: Eyime, E., & Ushie, O. (2025). Renewable Energy Revolution: Transforming Africa’s Energy Landscape through Solar, Wind, and Hydropower. Trends in Renewable Energy, 11(2), 155-200. doi:http://dx.doi.org/10.17737/tre.2025.11.2.0018

The Impact of Operating Frequencies and Neural Network Training Program Properties on the Performance of Neural Network Topology Generator Methodology

Until now, Neural Network Topology Generator Methodology (NNTGM) has been theoretically proposed so that its generated overhead low-voltage broadband over power lines topologies (NNTGM OV LV BPL topologies) may populate the existing OV LV BPL topology classes. With reference to the OV LV BPL topology class maps, which are defined by the graphical combination of ACA and RMS-DS of the OV LV BPL topologies, and the NNTGM OV LV BPL topology footprints for given indicative OV LV BPL topologies, the impact on the relative position and the size of the NNTGM OV LV BPL topology footprints has been assessed for a number of factors that affect the preparation of the Topology Identification Methodology (TIM) OV LV BPL topology database being used during the NNTGM operation. In this companion paper, the effect of the operating frequencies and the Neural Network (NN) training program properties on the relative position and the size of the NNTGM OV LV BPL topology footprints is here examined. The effect study is supported by suitable Graphical Performance Indicators (GPIs).Citation: Lazaropoulos, A. (2025). The Impact of Operating Frequencies and Neural Network Training Program Properties on the Performance of Neural Network Topology Generator Methodology. Trends in Renewable Energy, 11(2), 237-254. doi:http://dx.doi.org/10.17737/tre.2025.11.2.0019

Enhancing Cybersecurity in Energy Infrastructure: Strategies for Safeguarding Critical Systems in the Digital Age

In the digital age, energy infrastructure faces unprecedented cybersecurity challenges that threaten the stability and reliability of critical systems. This paper explores the current threat landscape, detailing prevalent cyber threats such as malware, ransomware, and phishing that target energy systems. It examines the technical, organizational, and regulatory challenges in securing these infrastructures, highlighting issues like legacy systems, lack of cybersecurity awareness, and stringent compliance requirements. The paper proposes comprehensive strategies for enhancing cybersecurity, emphasizing the implementation of advanced technologies such as artificial intelligence, machine learning, and blockchain. Best practices, including regular security audits, incident response planning, and employee training, are also discussed. Furthermore, the importance of collaborative efforts, such as public-private partnerships and information sharing networks, is underscored. The paper concludes with recommendations for energy organizations to strengthen their cybersecurity posture, ensuring the protection of critical systems and the continuity of operations in the face of evolving cyber threats. Citation: Ajayi, O., Alozie, C., & Abieba, O. (2025). Enhancing Cybersecurity in Energy Infrastructure: Strategies for Safeguarding Critical Systems in the Digital Age. Trends in Renewable Energy, 11(2), 201-212. doi:http://dx.doi.org/10.17737/tre.2025.11.2.0019

Multi-Parameter Based Models for Estimating Global Solar Radiation in Selected Locations in Ebonyi State, Southeastern Nigeria

This study aims to develop hybrid empirical models for estimating global solar radiation in selected locations across Ebonyi State, Nigeria, to enhance photovoltaic energy generation and support climate change mitigation and adaptation. The research is designed to create empirical models for calibrating and modeling global solar radiation using meteorological parameters at Alex Ekwueme Federal University Ndufu-Alike, Ebonyi State University Abakaliki and Akanu Ibiam Federal Polytechnic Unwana, all in Ebonyi State, Southeastern Nigeria. The long term monthly mean daily global solar radiation on the horizontal surface, sunshine hours, relative humidity, minimum and maximum temperature at 2 m height for the period of 1984-2019 for the selected stations were obtained from the National Aeronautics and Space Administration (NASA) atmospheric science data centre.  A multi-parameter based model was used to estimate the global solar radiation in each of these locations using Angstrom-Prescott-Page Model. Model performance was evaluated using statistical metrics, including Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Mean Percentage Error (MPE). Additionally, the correlation coefficient (r) and coefficient of determination (r2) were calculated. Results indicate that the developed empirical models demonstrate a high level of accuracy in estimating daily global solar radiation. Comparisons with existing models in the literature show that the locally calibrated models perform better on monthly and yearly timescales. Therefore, these models can be applied for solar radiation forecasting across Ebonyi State. However, routine recalibration is recommended, as climate variability over time may affect model stability and performance.Citation: Amadi, S. O., Eze, I. A., Enyi, V. S., Nwokolo, S. C., & Kalu, P. N. (2025). Multi-Parameter Based Models for Estimating Global Solar Radiation in Selected Locations in Ebonyi State, Southeastern Nigeria. Trends in Renewable Energy, 11(1), 213-236. doi:http://dx.doi.org/10.17737/tre.2025.11.2.0019

From Policy to Practice: Evaluating the Role of Private-Sector Champions Like Elon Musk in Shaping Trump's 2.0 Climate Agenda

This paper explores the prospective influence of private-sector leaders, particularly Elon Musk, on the formulation of climate and energy policy in a possible second term of President Donald Trump. Historically, the goals of the Trump administration have been viewed as opposed to environmental advocacy; yet, this analysis explores the potential for public-private partnerships that reconcile economic objectives with climate-positive results. Musk's enterprises—Tesla, SpaceX, and SolarCity—are transforming clean energy, and his impact on federal climate policies may initiate a new phase of environmentally sustainable economic development within conservative administration. This study analyzes case studies where Musk has collaborated with public authorities to tackle environmental and energy issues, highlighting practical strategies for partnership. Potential synergies are seen in sectors including renewable energy, electric vehicle infrastructure, and sustainability-oriented manufacturing, underscoring their alignment with Trump's economic plan. Additionally, the article examines the policy mechanisms—tax incentives, regulatory reforms, and investments in clean technology—that may encourage private sector participation in a nationally endorsed climate agenda. This article advocates for a worldview in which leaders like Musk advance environmental progress by harmonizing innovation with conservative regulatory frameworks while preserving traditional economic objectives. Ultimately, it advocates for a revolutionary public-private partnership paradigm that utilizes private sector expertise to tackle climate challenges. This viewpoint enhances the current dialogue on sustainable development and the changing function of private enterprises in public policy, proposing a future where economic growth and environmental stewardship coexist within U.S. federal climate policy.Citation: Nwokolo, S. (2024). From Policy to Practice: Evaluating the Role of Private-Sector Champions Like Elon Musk in Shaping Trump's 2.0 Climate Agenda. Trends in Renewable Energy, 11(1), 122-154. doi:http://dx.doi.org/10.17737/tre.2025.11.1.0019

Evaluation of PV-based Buck-Boost and SEPIC Converters for EV Charging Applications

In recent decades, environmental issues have become an area of greatest concern due to changes in global climate conditions. The transportation sector is a major contributor to carbon dioxide emissions, accounting for more than 22.9% of total carbon dioxide emissions. At present, most vehicles run on gasoline/diesel as fuel which is unsustainable and unviable as fossil fuels produce carbon emissions and fuel costs are rising. To address these issues, electric vehicles (EVs) offer an attractive solution as alternative to internal combustion engine vehicles that use electricity as an energy source. It is logical to use renewable energy to charge vehicles, which makes renewable energy an end-to-end clean energy source. In electric vehicles, energy conversion plays an important role. In the energy conversion process, alternating current (AC) can be converted to direct current (DC), or direct current can be converted to alternating current. In EV fast charging applications, DC-to-DC conversion is used, which requires DC-to-DC converters. In this paper, a detailed evaluation of the Buck-Boost and Single-Ended Primary Inductance Converters (SEPIC) with PV as input is analyzed for EV charging applications to make it end-to-end clean energy. For this purpose, a 5-by-5 PV system with a Buck-Boost, SEPIC converters with particle swarm optimization technique is considered, which is simulated in a MATLAB/SIMULINK environment. The simulation results showed that the ripples in output are minimal in SEPIC which supports the smooth and efficient charging of EV battery. Citation: K, J., & Chengaiah, C. (2024). Evaluation of PV-based Buck-Boost and SEPIC Converters for EV Charging Applications. Trends in Renewable Energy, 10(2), 159-169. doi:http://dx.doi.org/10.17737/tre.2024.10.2.0016

Development Status and Outlook of Hydrogen Internal Combustion Engine

Hydrogen energy is one of the best energy carriers for achieving carbon peak and carbon neutrality, with the characteristics of high energy and no pollution. The hydrogen internal combustion engine is one of the important forms of hydrogen energy utilization, with the significant advantages of high efficiency, high reliability, low cost and low emissions. In this paper, the characteristics of hydrogen internal combustion engines and hydrogen fuel cells were compared, and the industrialization prospects of hydrogen energy utilization in the future were analyzed. Focusing on the hydrogen internal combustion engine technology system, a comprehensive analysis was conducted on the technical issues and technical progress in hydrogen storage, combustion, NOx emissions, etc. of hydrogen internal combustion engines.Citation: Liu, M. (2024). Development Status and Outlook of Hydrogen Internal Combustion Engine. Trends in Renewable Energy, 10(3), 257-265. doi:http://dx.doi.org/10.17737/tre.2024.10.3.0017

Assessment of Temporal Trend in Surface Air Temperatures across Some Selected Eco-Climatic Zones in Nigeria

Temporal trends in surface air temperatures across some selected eco-climatic zones in Nigeria from 1981 to 2018 were assessed using the Merra-2 reanalysis dataset. A total of 15 stations spread across the eco-climatic zones in Nigeria were used for this study. The Mann-Kendall (M-K) trend test was used to detect direction, significance, coefficients of time trends, while the linear regression and the Sen’s slope trend tests were used to estimate the trend magnitudes. The M-K trend test showed that the surface air maximum temperature of 14 stations had monotonic increasing trends, of which 13 stations were statistically significant at the 0.01 significance level, and 1 station was statistically significant at the 0.05 significance level. However, the M-K trend test also showed that surface air minimum temperature for all the 15 stations (representing 100%), showed monotonic upward trends, statistically significant at the 0.01 significance level. The Sen's slope and linear trend tests showed higher trend magnitudes at most stations, particularly stations in the Guinea-wooded, Sudan and Sahel savannas. The estimated mean trend magnitudes of maximum and minimum air surface temperatures increased by approximately 0.035°C/year and 0.036°C/year, respectively. The estimated mean air surface temperature increased by approximately 0.036°C/year and approximately 1.4°C for Nigeria over the 38-year period. The study then presents a linear trend projection of mean air surface temperature increase in Nigeria of approximately 4.3°C by 2100. This is 0.2°C below maximum levels and within the range of approximately 1.5 to 4.5°C that global air surface temperature is projected to rise by 2100 in the Intergovernmental Panel on Climate Change (IPCC) 2007 report. The M-K and linear trend tests were fully consistent with the standardized time series anomaly plots. Mean annual values of the air surface temperatures showed latitudinal dependence. The manifestation of significant long-term trends at high confidence levels in the air surface temperatures over the period, provides a clear evidence that the climate of Nigeria is witnessing a possible human-induced radiative forcing and a strong tendency for the occurrences of climate-related extreme events and their resulting adverse implications. Citation: KING, L.E., Udo, S.O., Ewona, I.O., Amadi, S.O., Ebong, E.D., & Umoh, M.D. (2024). Assessment of Temporal Trend in Surface Air Temperatures across Some Selected Eco-Climatic Zones in Nigeria. Trends in Renewable Energy, 10, 132-158. doi:http://dx.doi.org/10.17737/tre.2024.10.1.0016

Effect of Hydrogen Injection Flow Rate on the Performance of In-Cylinder Direct Injection Hydrogen Engines

When a hydrogen internal combustion engine uses intake manifold injection to supply hydrogen, it must face the contradiction of abnormal combustion (premature combustion, backfire, etc.). The occurrence of abnormal combustion such as backfire can be avoided by using in-cylinder direct injection of hydrogen. In this paper, the In-Cylinder Direct Injection single-cylinder engine is modified, a three-dimensional simulation model is established, and simulation tests using AVL-Fire software on this basis is conducted. Through the analysis of the research results, the optimal hydrogen injection flow rate for the direct injection hydrogen engine to achieve the best power and economy under different working conditions was obtained. The results show that: under the same speed and load, the increase of hydrogen injection flow rate increases the hydrogen injection speed, which promotes the turbulent motion in the cylinder. At the same time, with the increase of hydrogen injection flow rate, the maximum pressure, temperature, indicated power and indicated thermal efficiency in the engine cylinder generally show a trend of first increasing and then decreasing, and there is an optimal hydrogen injection flow rate value.Citation: Ma, H. (2024). Effect of hydrogen injection flow rate on the performance of in-cylinder direct injection hydrogen engines. Trends in Renewable Energy, 10(3), 266-282. doi:http://dx.doi.org/10.17737/tre.2024.10.3.0017

Mechanical Study of a Solar Central Air Conditioning Duct Cleaning Robot

With the rapid economic development and the depletion of fossil fuels, the use of renewable energy such as solar energy can help alleviate energy supply pressure and carbon emissions. There have been many studies on solar energy powered robots. In this paper, a solar-powered duct-cleaning robot is used as the basis for the design of its mechanism. The robot is designed to clean vertical ducts with a length of 5~10 meters, a width of more than 400 mm and a height of 500~800 mm. The design of the robot is based on four aspects: solar energy, drive, camera and cleaning device. AutoCAD was used for 2D drawing of each part, while SolidWorks was used for modeling and assembling the parts of the vertical duct cleaning robot. The solar duct cleaning robot is characterized by high adaptability, low cost, and smooth and fast movement within the allowed size range.Citation: Sun, L. (2024). Mechanical Study of a Solar Central Air Conditioning Duct Cleaning Robot. Trends in Renewable Energy, 10(2), 239-256. doi:http://dx.doi.org/10.17737/tre.2024.10.2.0017