Renewable Energy Sources Research Articles

Decomposition prediction fractional-order active disturbance rejection control deep Q network for generation control of integrated energy systems

The number of distributed renewable energy sources of integrated energy systems (IESs) are increasing. The volatility of renewable energy exacerbates active power imbalances and increase frequency deviations in power systems. This work proposes a decomposition prediction fractional-order active disturbance rejection control deep Q network (DPFOADRCDQN) to control each generator of IESs more accurately and to reduce systemic frequency fluctuation. According to the fluctuation size of frequency deviation, the sub-signal obtained after the prediction of the modal decomposition of frequency deviation is classified into big fluctuating signals and small fluctuating signals; fractional-order active disturbance rejection control (FOADRC) controls small fluctuating signals; deep Q network (DQN) controls big fluctuating signals. Frequency deviation signals in complex power systems with a large percentage of renewable energy have higher smoothness after modal decomposition, FOADRC can efficiently follow the small fluctuating signals, and DQN can learn the rich data features in the big fluctuating signals and give precise control commands. The DPFOADRCDQN, proportional-integral-derivative, Q-learning, fuzzy control, and the previous state-of-the-art reinforcement learning are simulated in IESs where the renewable energy generators output is 0 %, 20 %, 40 %, 65 %, and 80 % of all generators output, the results show the average frequency deviation, total generation cost, and carbon emission cost are at least 42.7 %, 0.92 %, and 0.93 % smaller than the comparison algorithm, respectively.

Rotor solidity and blade pitch influence on horizontal axis small wind turbine performance – Experimental study

The urgent need to reduce greenhouse gas emissions has accelerated the adoption of renewable energy sources such as wind power. In this context, small wind turbines (SWTs) have emerged as a viable solution for decentralized electricity generation. This paper investigates the combined influence of rotor solidity and pitch angle variation on the performance of a small horizontal axis wind turbine through experimental analysis conducted in a wind tunnel. Results show that increasing rotor solidity generally improves Cpmax, particularly for shorter chord blades, with up to a 25–35 % increase observed by increasing the number of blades and a 10–15 % increase by employing longer chord blades compared to benchmark designs. Additionally, the study highlights the significant sensitivity of turbine performance to slight changes in pitch angle resulting in a 4–8 % rise in Cpmax. Higher solidity rotors exhibit reduced sensitivity to pitch angle changes and reference velocity variations, contributing to improved stability in varying environmental conditions. The study highlights the influence of aerofoil Reynolds number on turbine performance, underscoring the importance of careful aerodynamic design considerations. It provides valuable insights for SWT design to enhance energy efficiency and promote the widespread adoption of wind energy technology.

Clean energy transition in rural Bangladesh: Challenges in adoption and impact

ABSTRACT At the household level, the solar photovoltaic (PV) system is an off-grid clean energy source with significant poverty reduction potential, thereby contributing to the attainment of several sustainable development goals. Nevertheless, there has been limited adoption of renewable or clean energy technologies in Bangladesh. At present, renewable energy sources account for only 3% of the country’s electricity generation. This study thus investigates the drivers of solar PV adoption and the impact of this on household income and poverty in Bangladesh. We present an econometric analysis of data from the International Food Policy Research Institute’s Bangladesh Integrated Household Survey, 2020. Our findings indicate that only 5.51% of the sample households adopted solar PV, with the likelihood of adoption 3.8% higher in households with a mobile phone, 1.7% higher in households with internet access, and 2.8% higher among homeowners. However, the government’s programs to expand the electricity grid made the delivery of solar PV by partner organizations less competitive. Our analysis reveals that the adoption of solar PV has a positive effect on household income of between 9.31% and 13.50%. The poverty gap is likely to decrease by around 20% to 26% due to adoption. These findings are pertinent to ongoing policy development efforts targeted at increasing the adoption of renewable energy to meet the sustainable development goals. Solar PV information could be potentially disseminated through mass media and modern communication technologies that require internet access. Furthermore, increasing the installation of solar PV systems in rented houses may promote the adoption of solar PV. It is imperative to implement policies that provide incentives for the installation and utilization of solar PV.

Innovative Strategies for Combining Solar and Wind Energy with Green Hydrogen Systems

The integration of wind and solar energy with green hydrogen technologies represents an innovative approach toward achieving sustainable energy solutions. This review examines state-of-the-art strategies for synthesizing renewable energy sources, aimed at improving the efficiency of hydrogen (H2) generation, storage, and utilization. The complementary characteristics of solar and wind energy, where solar power typically peaks during daylight hours while wind energy becomes more accessible at night or during overcast conditions, facilitate more reliable and stable hydrogen production. Quantitatively, hybrid systems can realize a reduction in the levelized cost of hydrogen (LCOH) ranging from EUR 3.5 to EUR 8.9 per kilogram, thereby maximizing the use of renewable resources but also minimizing the overall H2 production and infrastructure costs. Furthermore, advancements such as enhanced electrolysis technologies, with overall efficiencies rising from 6% in 2008 to over 20% in the near future, illustrate significant progress in this domain. The review also addresses operational challenges, including intermittency and scalability, and introduces system topologies that enhance both efficiency and performance. However, it is essential to consider these challenges carefully, because they can significantly impact the overall effectiveness of hydrogen production systems. By providing a comprehensive assessment of these hybrid systems (which are gaining traction), this study highlights their potential to address the increasing global energy demands. However, it also aims to support the transition toward a carbon-neutral future. This potential is significant, because it aligns with both environmental goals and energy requirements. Although challenges remain, the promise of these systems is evident.

Analysis of the Potential Carbon Emission Reduction Through Interaction Between New Energy Vehicles and Smart Grids

Abstract: This paper analyzes the potential for carbon emission reduction through the interaction between new energy vehicles and smart grids, discussing how the optimization of energy efficiency and balancing of grid loads can be achieved through Vehicle-to-Grid (V2G) technology. The interaction between new energy vehicles and smart grids can enhance energy utilization efficiency, optimize grid management, and reduce reliance on fossil fuels by leveraging renewable energy sources, thereby achieving the goal of carbon emission reduction. However, this process faces multiple challenges including technological integration, cost-effectiveness, policy support, and societal acceptance. The paper proposes a series of strategic recommendations, including promoting technological standardization, enhancing policy and economic incentives, and increasing public awareness and participation, to support the effective interaction between new energy vehicles and smart grids, and to achieve long-term carbon emission reduction goals.

Evaluating the Role of GCC Nations in Sustainable Energy Investment Using an Enhanced Low-Carbon Economy Index

In the past decade, environmental, social and country governance (ESG) aspects as well as economy have become key factors for decisions in the investment and future development of renewable energy industry. The abundancy of renewable resources and widely accessible technology are the key drivers for the renewable energy business in the GCC. However, lack of effective policies and regulations, along with subsidized fuel prices, are slowing down the implementation of renewable resource options. This study will illustrate the potential, the challenges, and the barriers of implementing renewable energy technologies in the GCC region. In addition, this research empirically examines the impact of renewable energy sources and other factors in the GCC countries. This study can be used as a screening tool, decision making tool, benchmarking tool and guidance of sustainable development.

Decision making for renewable energy source selection using q-rung linear Diophantine fuzzy hypersoft aggregation operators

Decision making for renewable energy source selection using q-rung linear Diophantine fuzzy hypersoft aggregation operators

Application of an Optimal Fractional-Order Controller for a Standalone (Wind/Photovoltaic) Microgrid Utilizing Hybrid Storage (Battery/Ultracapacitor) System

Nowadays, standalone microgrids that make use of renewable energy sources have gained great interest. They provide a viable solution for rural electrification and decrease the burden on the utility grid. However, because standalone microgrids are nonlinear and time-varying, controlling and managing their energy can be difficult. A fractional-order proportional integral (FOPI) controller was proposed in this study to enhance a standalone microgrid’s energy management and performance. An ultra-capacitor (UC) and a battery, called a hybrid energy storage scheme, were employed as the microgrid’s energy storage system. The microgrid was primarily powered by solar and wind power. To achieve optimal performance, the FOPI’s parameters were ideally generated using the gorilla troop optimization (GTO) technique. The FOPI controller’s performance was contrasted with a conventional PI controller in terms of variations in load power, wind speed, and solar insolation. The microgrid was modeled and simulated using MATLAB/Simulink software R2023a 23.1. The results indicate that, in comparison to the traditional PI controller, the proposed FOPI controller significantly improved the microgrid’s transient performance. The load voltage and frequency were maintained constant against the least amount of disturbance despite variations in wind speed, photovoltaic intensity, and load power. In contrast, the storage battery precisely stores and releases energy to counteract variations in wind and photovoltaic power. The outcomes validate that in the presence of the UC, the microgrid performance is improved. However, the improvement is very close to that gained when using the proposed controller without UC. Hence, the proposed controller can reduce the cost, weight, and space of the system. Moreover, a Hardware-in-the-Loop (HIL) emulator was implemented using a C2000™ microcontroller LaunchPad™ TMS320F28379D kit (Texas Instruments, Dallas, TX, USA) to evaluate the proposed system and validate the simulation results.

Low-Carbon Rural Areas: How Are Polish Municipalities Financing the Green Future?

The main aim of the research was to assess Polish rural municipalities’ investment activity connected with the development of a low-carbon economy, supported with EU funds in the 2007–2013 and 2014–2020 financial frameworks. The empirical study was based on data from Poland’s Ministry of Development Funds and Regional Policy, Ministry of Finance, and Statistics Poland, analysed through basic descriptive statistics and a logistic model to identify key factors influencing investment activity. The study showed that the greatest number of agreements on funding were, in fact, signed by rural municipalities in the period under analysis. The predominant measures undertaken during this time were the promotion of renewable energy sources and the improvement in energy efficiency. In the earlier financial framework, low-carbon economy projects in rural areas were more often implemented by municipalities with developing demographic potential, including those characterised by a higher level of enterprise development. In the subsequent financial framework, human capital turned out to be of key importance for the investment activity of rural municipalities. Experience gained from 2007–2013 positively influenced fund absorption in 2014–2020, improving project value, number, and support. The study confirmed that rural municipalities play a vital role in advancing a low-carbon economy, as local actions are key to achieving sustainable development and reducing greenhouse gas emissions.

Research on performance and potential of distributed heating system for peak shaving with multi-energy resource

Climate change and its negative effects are driving the global shift from fossil fuels to renewable energy sources. To tackle the dependency on traditional energy sources in harsh winter regions and improve heating quality during periods of thermal demand fluctuations, this paper proposes a new distributed heating peak shaving system (DHPS). The system combines municipal heat and clean energy within the secondary network while reducing the return water temperature in the primary network. It comprises solar collectors, electric thermal storage tanks (ETST), and absorption heat pump (AHP) units, integrated into conventional heat exchange stations. The system operates in two modes to manage peak and off-peak loads respectively, with TRNSYS simulation used to evaluate performance across a range of peak-shaving gradients. A multidimensional comprehensive assessment is conducted between the DHPS under optimal peak shaving coefficient (θ) conditions and conventional peak clipping boiler (PCB). Results indicate that DHPS achieves a high primary energy ratio (PER) of 1.251 at θ = 0.5, reducing combustion emissions by nearly 40%. The static payback period (PBP) of the system is 3.5 years. When the electricity price drops to 0.275 CNY, its operational costs are comparable to PCB. DHPS caters to the energy characteristics of cold regions where electricity supply exceeds demand. It enables flexible peak shaving while ensuring the complete utilization of clean energy and effectively utilizing waste heat from power plants.

A new integrated modelling and control of ternary pumped storage hydro power generation for small signal stability studies

Pumped storage hydro power generation (PSHPG), a reliable renewable energy source with an energy storage feature, can impart efficient damping torque to power system oscillations to improve small signal stability with appropriate modelling and additional compensation through the governor. But ternary PSHPG (T-PSHPG) has the unique feature of hydraulic short circuit (HSC) mode, where both pumping and generating modes operate simultaneously. This study presents a novel fourth-order modified Heffron Phillips (MHP) model of T-PSHPG in coordination with a multi-band Power system stabilizer (MB-PSS) employing 2-way penstock, where primary penstock circulates water from the upper reservoir to the lower reservoir through the turbine and secondary penstock divides primary penstock, thereby creating short-circuit path through the pump. Also, this model includes additional reactive power droop control to maintain the voltage profile. A new state space matrix has been developed for coordinating T-PSHPG in HSC mode with MB-PSS. The control parameters of the proposed coordinated model are set by a new multi-objective differential evolution-improved particle swam optimization (DE-IPSO) algorithm. With variable load, random solar and wind source penetrations, it has been found that the proposed model can provide adequate damping actions. The sensitivity of the proposed model has been observed by varying critical model parameters by ±50 %. For all conditions, the settling time of speed variation is within 2.672 s to 5.951 s and the minimum damping ratio lies within 0.105 to 0.455. The minimum damping ratio is 0.32 and the settling time is found to be 3.1 s for system response subject to sudden solar power variation, which has been observed by shifting system eigenvalues toward the left half of the complex plane. Time and frequency domain parameters with sensitivity analysis predict system oscillations being damped effectively with consistency for the proposed modelling and control strategy. The results are verified in real-time with OPAL-RT real-time digital simulator. It has been justified by the present study that appropriate modelling of T-PSHPG along with coordinated control action provided by MB-PSS can handle critical power system oscillations efficiently and effective damping torque can be imparted in HSC mode.

Coupled hydro-mechanical model for underground hydrogen storage undergoing cyclic injection and production

ABSTRACT Excess renewable energy can be used to generate and store hydrogen underground, offering a secure and econimical solution to the intermittency challenges of renewable energy sources. The success of underground storage relies on understanding and controlling the geo-mechanical integrity of storage sites during cyclic loadings. While geological deformation during natural gas and carbon dioxide storage is well studied, few have investigated pore pressure and in-situ stress variations during cyclic loading, which is unique to underground hydrogen storage sites. This paper presents a predictive analytical model for the pore pressure and stress changes during cyclic loading. The model was derived based on continuous point source injection, a basic hydro-mechanical model while applying the superposition to consider the cyclic loading. The developed model was evaluated for hydrogen and natural gas subjected to cyclic injection and production. Comparing hydrogen and natural gas storage cases can offer valuable insights into the behavior of hydrogen since the deformation of natural gas storage is more studied. Finally, analytical solutions for both storage cases were validated by numerical models with discrepancies between the models amounting to less than 1%. Comparative analysis of the results from 3 to 99 cycles of injection and production for both hydrogen and methane demonstrates that rise in cycle numbers leads to a corresponding rise in stress accumulation in the system. Neglecting the stress accumulation during these cycles can lead to significant geomechanical issues, potentially compromising the storage system’s safety and integrity.

Data-driven stochastic dynamic economic dispatch for combined heat and power systems using particle swarm optimization

In modern power systems, the uncertain behavior of renewable energy sources (RESs) may result in deviations from the optimal operating dispatches for the various power sources. The electric power generation from Combined Heat and Power (CHP) units is characterized by high efficiency with less pollution. To use CHP units more efficiently, the dynamic economic dispatch problem is applied to obtain the optimal power and heat sources’ outputs to satisfy heat and power demands while meeting the different operational constraints. In this paper, data-driven stochastic optimization is used to model these uncertainties utilizing the Generative Adversarial Networks in scenario generation that are accurate and do not require fitting models or modeling probability distributions. Then, the Fast Forward Selection technique is used to decrease the number of scenarios to improve system tractability. The results obtained indicate that the variability in electrical load, photovoltaic (PV), and wind turbine (WT) output significantly impacts the overall operational costs of the power system. Therefore, it is essential to incorporate the uncertainties associated with electrical load, PV, and WT when aiming for accurate results in economic dispatch. the study found that the overall operation cost of the dynamic economic dispatch of the electrical system for 24 hours after integrating RES achieved a daily savings of 2.5 % in the first scenario. Furthermore, the findings demonstrate that RESs positively contribute to reducing the total operational costs of the power system. The economic dispatch of CHP systems is influenced by the integration of RESs and the uncertainties associated with electrical parameters.

Tailored IrO2@ZIF-67 nanocomposites for efficient oxygen evolution reaction: Insights into catalyst design and performance enhancement

The pursuit of effective electrocatalysts for the oxygen evolution reaction (OER) is crucial for advancing sustainable energy technologies. Efficient OER catalysts play a vital role in the development of water splitting systems, which are fundamental for producing hydrogen—a clean and renewable energy source. The synthesis of IrO2 nanoparticles embedded in ZIF-67 nanostructures has been explored to improve the performance of OER electrocatalysts. The resulting IrO2@ZIF-67 composite catalyst demonstrates a remarkable overpotential of 220 mV and 290 mV at current densities of 10 and 50 mA cm⁻2, alongside a low Tafel slope of 58 mV dec⁻1, significantly outperforming the pristine ZIF-67 catalyst. Integrating IrO2 nanoparticles into the ZIF-67 matrix significantly enhances both the catalytic activity and durability of the material. Extensive electrochemical testing reveals that the IrO2@ZIF-67 catalyst maintains exceptional stability, operating consistently for over 50 h at a current density of 50 mA cm⁻2 without significant degradation. This enhanced performance is attributed to the synergistic effects between the highly active IrO2 nanoparticles and the robust ZIF-67 framework, which collectively facilitate efficient charge transfer and improve structural integrity during prolonged OER operation. These findings highlight the potential of IrO2@ZIF-67 nanostructures as a promising electrocatalyst for sustainable water splitting applications, providing a pathway towards the development of more efficient and durable OER catalysts.

ENERGY SECURITY POLICY OF UKRAINE: STRATEGIC CHALLENGES AND INTERNATIONAL COOPERATION

The issues of energy security are among the decisive factors in determining domestic and foreign policy most countries of the world. The article is devoted to the evolution of the concept of energy security of Ukraine from the beginning of the 20th century to the present. Also raised are the problematic issues of the formation of the concept of international energy security at the current stage, which poses problems of a global nature to Ukraine, taking into account the risks that arise, which are resolved through dialogue between states. Which is especially important in the conditions of Russian aggression on the territory of Ukraine. The article analyzes the practical approach to the concept of “energy security”, reveals the main concepts of “energy security”. Based on the study of the concept of energy policy of countries that are importers, exporters and countries through which energy resources are transited, an attempt is made to identify unified approaches to the content of this concept. The analysis of the current international legislation showed the absence of a single formulation of the studied concept, which is based, in our opinion, on the difference in approaches and multifacetedness. At the same time, the authors indicate the need for a scientific analysis of this concept precisely from a legal point of view, which is justified by the need for constant regulatory support of the conditions necessary to ensure energy security. The article is devoted to the description of the main renewable energy sources and their use in Ukraine, which is dictated by the energy policy. According to experts, the potential of renewable energy sources is significantly higher than the total consumption of fuel and energy resources, which can reduce emissions of the latter into the atmosphere. Therefore, the need to immediately build a “green economy” in Ukraine is substantiated. Based on the theory and taking into account the similar experience of advanced countries, the directions, planned paths and mechanisms of accelerated development of Ukraine’s energy security policy were selected.

Intelligent parking lot power management: Augmented epsilon‐constraint concept with correlation analysis

AbstractThis paper addresses essential aspects of decision‐making and management in energy resources. To achieve this, a tri‐objective model is proposed that seeks to find the best solution within the basic constraints framework of the optimization problem so that all three proposed objective functions can approach their ideal point. The uncertainty is used for the photovoltaic and wind power plants’ output in the proposed multi‐objective optimization problem as a scenario‐based stochastic approach. The proposed objective functions are realizing the operating cost, the amount of emission produced by generation resources, the amount of load‐shedding, and the maximum participation of responsive demands in the management program. The idea of employing plug‐in electric vehicle (PHEV) units in the form of intelligent parking lots within the network is also included in the proposed study, which can increase network flexibility and help improve the main features of the network. A modified IEEE 83‐bus test system is used to ensure the accuracy and effectiveness of the proposed model. The properties of PHEVs significantly affect the simulation results and compensate for the uncertainty associated with renewable energy sources. Randomly considering the parameters of PHEVs can also realistically bring the results of power management more realistic. In addition, the multi‐objective problem defined for each scenario is solved by the augmented epsilon‐constraint method with the correlation coefficient concept for the network under study, and the Pareto front curves are obtained separately and the best solution is extracted by a proper decision‐making method.

Exploring the Bioelectricity of Fruits as Sources for Sustainable and Renewable Energy

Exploring the Bioelectricity of Fruits as Sources for Sustainable and Renewable Energy

Light-driven lytic polysaccharide monooxygenasecatalysis mediated by Type I photosensitizers.

The use of light as abundant, renewable, and clean energy source to boost lytic polysaccharide monooxygenase (LPMO) reactions represents an exciting and yet under-explored opportunity. Herein we demonstrated that photosensitizers, commonly used in photodynamic therapy, which act through the photocatalytic Type I mechanism can drive the oxidation of PASC by LPMOs, whereas Type II photosensitizers are not capable of promoting the LPMO activity. We analyzed Type I and Type II photosensitizers (methylene blue and tetraiodide salt of meso-tetrakis-(4-N-methylpyridyl) porphyrin, respectively) and demonstrated that, even without an addition of external reductant, Type I was capable of boosting Thermothelomyces thermophila MtLPMO9A activity in the presence of light. We also evaluated the photobiosystem in the presence and/or absence of molecular oxygen (O2) and hydrogen peroxide (H2O2), and investigated the role of superoxide radical in the methylene blue fueled reactions. Furthermore, we demonstrated that sodium bisulfite (NaHSO3), a chemical scavenger of H2O2, acts by safeguarding the enzyme from oxidative damage caused by accumulation of H2O2 early in photosensitizer-driven LPMO reactions. Finally, the results of the present work demonstrated that light-driven LPMO reactions mediated photodynamic therapy (PDT) Type I photosensitizers, which also includes molecules such as curcumin and riboflavin, is a general phenomenon.

Optimization of operational strategies for industrial applications of solar-based green hydrogen

Renewable-based green hydrogen is emerging as a viable solution for decarbonizing energy-intensive industries. However, the fluctuating and intermittent nature of renewable energy sources requires careful consideration of operational strategies to ensure the safe and economical use of green hydrogen in industrial applications. This study examines the influence of operational strategies for electrolyzers and downstream processes on the cost of solar-based green hydrogen. The results demonstrate that optimal operational strategies for electrolyzers significantly impact the sizes of batteries and electrolyzers, reducing the Levelized Cost of Hydrogen (LCOH) by an average of 5.3%. Case studies further demonstrate that decentralized end-user supply strategies and cooperation with downstream processes can reduce LCOH by up to 39.8% for fully distributed end-users and by 24.2% with the introduction of supply tolerance. Additionally, the study evaluates the impact of grid backup, revealing that grid utilization can reduce LCOH by 12.9% in Houston, underscoring the potential for further cost reductions through grid decarbonization. These findings highlight the importance of optimizing operational strategies to improve the economic performance and market viability of green hydrogen systems.

High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations

Wind speed (and direction) estimated from numerical weather prediction (NWP) models is essential to wind energy applications, especially in the absence of reliable fine scale spatio-temporal wind information. This study evaluates four high-resolution wind speed numerical datasets (UERRA MESCAN-SURFEX, CERRA, COSMO-REA6, and NEWA) against in situ observations from coastal meteorological stations in the eastern Mediterranean basin. The evaluation is based on statistical comparisons of long-term wind speed data from 2009 to 2018 and involves an in-depth statistical comparison as well as a preliminary wind power density assessment at or near the meteorological station locations. The results show that while all datasets provide valuable insights into regional wind variability, there are notable differences in model performance. COSMO-REA6 and UERRA exhibit higher variability in wind speed but tend to underestimate extreme values, particularly in the southern coastal areas, whereas CERRA and NEWA provided closer fits to observed wind speeds, with CERRA showing the highest correlation at most stations. NEWA data, where available, overestimate average wind speeds but capture extreme values well. The comparison reveals that while all datasets provide valuable insights into the spatial and temporal variability of wind resources, their performance varies by location and season, emphasizing the need for the careful selection and potential calibration of these models for accurate wind energy assessments. The study provides essential groundwork for leveraging these datasets in planning and optimizing offshore wind energy projects, contributing to the region’s transition to renewable energy sources.