Reliable Energy Source Research Articles

A novel optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning

Natural gas is an emerging and reliable energy source in transition to a low-carbon economy. The natural gas transportation pipeline network systems are crucial when transporting natural gas from the production endpoints to processing or consuming endpoints. Optimizing the operational efficiency of compressor stations within pipeline networks is an effective way to reduce energy consumption and carbon emissions during transportation. This paper proposes an optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning (DRL). The mathematical simulation model is derived from mass balance, hydrodynamics principles of gas flow, and compressor characteristics. The optimization control problem in steady state is formulated into a one-step Markov decision process (MDP) and solved by DRL. The decision variables are selected as the discharge ratio of each compressor. By the comprehensive comparison with dynamic programming (DP) and genetic algorithm (GA) in three typical element topologies (a linear topology with gun-barrel structure, a linear topology with branch structure, and a tree topology), the proposed method can obtain 4.60% lower power consumption than GA, and the time consumption is reduced by 97.5% compared with DP. The proposed framework could be further utilized for future large-scale network optimization practices.

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.

Enhanced Efficiency of Dye-Sensitized Solar Cells Using Nitrogen-Titanium Dioxide Composites and Optimized Azo Dye Mixtures

In response to the increasing global energy demand, developing cost-effective and reliable renewable energy sources is crucial. Dye-Sensitized Solar Cells (DSSCs) have emerged as a promising alternative due to their low production cost, flexibility, and capability to operate under diffuse sunlight. This study aims to enhance the efficiency of DSSCs by incorporating Nitrogen-Titanium Dioxide (N-TiO2) composites synthesized via the Sol-Gel method [1]. The DSSCs were constructed using N-TiO2 composites in conjunction with VC, RP, and RM azo dyes. Nitrogen in the TiO2 matrix effectively reduced the band gap, leading to improved light absorption. The presence of Nitrogen dopants is expected to introduce additional energy levels within the TiO2 bandgap, enhancing light absorption and charge carrier separation, which are crucial factors for improved DSSC performance [2,3]. The current-voltage (I-V) characteristics of the DSSCs revealed significant variations in key performance metrics, including short circuit current (Isc), fill factor, and power conversion efficiency. Specifically, DSSCs utilizing N-TiO2 with VC-RP dye mixture achieved a higher efficiency of 0.349%, an Isc of 0.85 mA, and a fill factor of 44.59%, with Rs and Rsh values of 328.13Ω and 1637.18Ω, respectively [4]. These results underscore the potential of N-TiO2 composites, particularly when paired with optimized dye mixtures, to significantly enhance the electronic properties and overall efficiency of DSSCs.

Nuclear Energy as a Sustainable Source? Examining Media Discourses Surrounding the EU-Complementary Delegated Act

This paper contributes to the understanding of media discourses surrounding the sustainability of nuclear energy, particularly within a crisis context. The study examines the implications of the adoption of the Complementary Delegated Act on EU taxonomy by the European Commission on July 6, 2022, which officially categorises nuclear energy as sustainable. Employing a critical discourse analysis (CDA) methodology, the research explores the discourse strategies–nomination, predication, and argumentation– utilised across 695 news articles. The findings reveal the intricate representation of nuclear energy’s sustainability across the media. The Russian-Ukrainian conflict amplifies favourably the nuclear energy view as a reliable and sustainable energy source. However, the media discourse on nuclear energy’s sustainability reveals a variety of viewpoints. These varying outlooks provide essential insights for shaping effective energy policies. This research contributes valuable insights into understanding how media shapes and influences public perception of sustainability energy policies, amplifying specific actors’ voices and steering discourse toward distinct trajectories. Such insights are crucial in crafting energy policies.

Decarbonising primary industries with geothermal heat – a pathway to greater direct use

ABSTRACT This paper discusses the opportunities and policy levers to increase the use of low-temperature geothermal resources in New Zealand for decarbonising primary industries, in particular, covered crops. Geothermal heat (geoheat) is a local, reliable, resilient and sustainable energy source. Low-temperature geothermal energy (220°C) is available in the Taupō Volcanic Zone with low awareness of the nationwide availability of lower temperature resources. Covered crop growers in New Zealand, needing to decarbonise their operations, are investigating the potential of utilising geoheat, following the example of the Netherlands. The Netherlands has strategically invested in low-temperature geothermal energy, utilising 80 °C water resources, from ∼ 2 to 3 km below the surface to heat greenhouses. Internationally, risk mitigation schemes and insurance programmes have proven pivotal policy instruments for fostering geothermal adoption. This paper discusses the opportunities that the adoption of using low-temperature geothermal provides to New Zealand drawing upon successful models from other countries.

Turkey’s Hydropower Potential in the Near Future and the Possible Impacts of Climate Change—A Case Study of the Euphrates–Tigris Basin

Hydropower is becoming an important renewable energy source in Turkey, but the ever-changing atmospheric and climatic conditions of Turkey make it very difficult to be projected efficiently. Thus, an efficient estimation technique is crucial for it to be adopted as a reliable energy source in the future. This study evaluates Turkey’s hydropower potential in the Euphrates–Tigris Basin under changing climatic conditions. We adapted an empirical equation to model reservoir outflows, considering the site-specific characteristics of 14 major dams. Initial results from employing a model with a constant empirical coefficient, α, yielded moderate predictive accuracy, with R2 values ranging from 0.289 to 0.612. A polynomial regression identified optimal α values tailored to each dam’s surface area, significantly improving model performance. The adjusted α reduced predictive bias and increased R2 values, enhancing forecast reliability. Seasonal analysis revealed distinct hydropower trends: Ataturk Dam showed a notable decrease of 5.5% in hydropower generation up to 2050, while Birecik and Keban Dams exhibited increases of 2.5% and 2.2%, respectively. By putting these discoveries into practice, water resource management may become more robust and sustainable, which is essential for meeting Turkey’s rising energy needs and preparing for future climatic challenges. This study contributes valuable insights for optimizing reservoir operations, ensuring long-term hydropower sustainability, and enhancing the resilience of water resource management systems globally.

Effects of Microbiota on the Soiling Process of PV Modules in Arid Zones of the Atacama Desert

Photovoltaic technology has proven to be a reliable, economical, and clean energy source that is capable of adapting to diverse geographical conditions. However, factors such as soiling overshadow these qualities, thus leading to production losses and affecting the profitability of this technology. For these reasons, soiling is a highly studied topic, which involves considering the physicochemical characterization of the deposited material, mitigation strategies, effect predictions, and cleaning mechanisms. However, there is a relatively unexplored area related to the microbiological contribution to soiling. The surface of photovoltaic modules, along with the deposited material and local atmospheric factors, fosters favorable conditions for the colonization of microorganisms. These microorganisms influence the soiling mechanisms and optical properties of photovoltaic modules. This work presents a detailed characterization of the microbial diversity present in the soiling deposited on photovoltaic modules installed in the Atacama Desert. Two study sites were defined: Antofagasta and the Solar Platform of the Atacama Desert, which have warm and cold desert climates, respectively. Mineralogical characterization tests, heavy metal analyses, TOC, and inorganic element analyses were conducted on the deposited material. Additionally, the culturable isolates and the metagenomic DNA of the soiling samples and biofilms grown on standard PV glass were characterized using next-generation sequencing. The results show that the deposited soiling contained a microbiological component that had adapted to extreme desert conditions. The presence of the genera Arthrobacter, Kocuria, and Dietzia were identified in the culturable isolates from Antofagasta, while Arthrobacter and Dietzia were obtained from the Solar Platform of the Atacama Desert. The metagenomic DNA was mainly represented by the genera Pontibacter, Noviherbaspirillum, Massilia, Arthrobacter, Hymenobacter, and Deinococcus at Antofagasta. However, at the Solar Platform of the Atacama Desert, the analyzed samples presented DNA concentrations below 0.5 ng/µL, which made their preparation unviable. At the PSDA, the biofilms formed by the genera Peribacillus and Kocuria were identified, whereas the UA showed a greater abundance of bacteria that favored biofilm formation, including those that belonged to the genera Bacillus, Sporosarcina, Bhargavaea, Mesaobacillus, Cytobacillus, Caldakalibacillus, and Planococcus. Based on these results, we propose a soiling mechanism that considers the microbiological contribution to material cementation.

Hybridization of Concentrated Solar Thermal With Geothermal and Biomass Power

While Geothermal Power Plants (GPPs) can be a reliable renewable energy source, this reliability can decrease over the years due to brine mass flow declining. This reduced mass flow causes extra capacity unused in the GPP turbines. This problem can be overcome by hybridizing GPPs with CST and biomass. These three thermal technologies can, in theory, complement each other if all the resources are present at the exact location. This is the scenario for this study, as the location for the case study is the Kızıldere 2 (KZD2) GPP in Denizli, Turkiye, operated by Zorlu Energy. This region has sufficient potential for all three technologies: CST, geothermal, and biomass. Furthermore, by building a topping cycle using CST and biomass, it is possible to generate additional power. This study utilizes a topping steam Rankine cycle run equally by CST and biomass, and, as a result, the 20% excess capacity in the GPP turbine is used while generating an additional 20 MWe of power.

Performance analysis of PID and SMC for PEMFC-based grid integrated system using nine switch converter - A comparative study

Hydrogen fuel cells are gaining popularity as a reliable and efficient sustainable energy source. They have found uses in electric vehicles and microgrid applications. A grid-connected microgrid system with a 60 kW proton exchange membrane fuel cell (PEMFC) is proposed. A PEM fuel cell-based generating unit is studied, using a sliding mode controller (SMC) in the control scheme and a nine-switch converter (NSC) for the system integration. The NSC is used to integrate the FC system with the utility grid and controls the system's power flow. This study is focused on the performance evaluation of the proportional-integral-derivative (PID) and SMC controllers. The controllers' gains are tuned using an improved arithmetic optimization method (IAOA). The article also emphasizes improving system performance and stability by incorporating SMC in the control scheme. The suggested system is exposed to different source and load-side disturbances for performance evaluation. Matlab/Simulink is used to model the proposed system and validated by the real-time OPAL-RT 4510.

Numerical Investigation of Wake Characteristics for Scaled 20 kW Wind Turbine Models with Various Size Factors

Wind energy is essential for sustainable energy development, providing a clean and reliable energy source through the wind turbine. However, the vortices and turbulence generated as wind passes through turbines reduce wind speed and increase turbulence, leading to significant power losses for downstream turbines in wind farms. This study investigates wake characteristics in wind turbines by examining the effects of different scale ratios on wake dynamics, using both experimental and numerical approaches, utilizing scaled-down models of the Aeolos H-20 kW turbine at scales of 1:33, 1:50, and 1:67. The experimental component involved wind tunnel tests in an open-circuit tunnel with adjustable wind speeds and controlled turbulence intensity. Additionally, Computational Fluid Dynamics (CFD) simulations were conducted using STAR-CCM+ (Version 15.06.02) to numerically analyze the wake characteristics. Prior to the simulation, a convergence test was performed by varying grid density and y+ values to establish optimized simulation settings essential for accurately capturing wake dynamics. The results were validated against experimental data, reinforcing the reliability of the simulations. Despite minor inconsistencies in areas affected by tower and nacelle interference, the overall results strongly support the methodology’s effectiveness. The discrepancies between the experimental results and CFD simulations underscore the limitations of the rigid body assumption, which does not fully account for the deformation observed in the experiment.

Time-variations of wave energy and forecasting power availability at a site in Fiji using time-series, regression and ANN techniques

ABSTRACT Recently, there has been a shift in the global energy landscape to move to reliable, clean, and eco-friendly renewable energy sources to address global issues such as climate change and greenhouse gas emissions. One such energy source is wave energy; researchers attempt to develop models that can accurately forecast the availability of wave energy as an alternative energy source. In this paper, an Artificial Neural Network (ANN) model along with statistical models such as time series models, and regression models are proposed for forecasting wave energy at a site in Fiji using the wave height and wave period as the independent variables. The performance of the proposed models developed is compared using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the goodness-of-fit ( R 2 ) value. The proposed model is then further benchmarked with the naïve model. The empirical results reveal that the proposed ANN model outclassed all the other models and was more efficient and accurate in forecasting wave energy than the regression and time series models. By accurate wave modelling and by incorporating impedance matching, maximum power generation can be achieved.

A Multi-Objective Optimization Approach for Solar Farm Site Selection: Case Study in Maputo, Mozambique

Solar energy is an important source of clean energy to combat climate change issues that motivate the establishment of solar farms. Establishing solar farms has been considered a proper alternative for energy production in countries like Mozambique, which need reliable and clean sources of energy for sustainable development. However, selecting proper sites for creating solar farms is a function of various economic, environmental, and technical criteria, which are usually conflicting with each other. This makes solar farm site selection a complex spatial problem that requires adapting proper techniques to solve it. In this study, we proposed a multi-objective optimization (MOO) approach for site selection of solar farms in Mozambique, by optimizing six objective functions using an improved NSGA-II (Non-dominated Sorting Genetic Algorithm II) algorithm. The MOO model is demonstrated by implementing a case study in KaMavota district, Maputo city, Mozambique. The improved NSGA-II algorithm displays a better performance in comparison to standard NSGA-II. The study also demonstrated how decision-makers can select optimum solutions, based on their preferences, despite trade-offs existing between all objective functions, which support the decision-making.

Diurnal humidity cycle driven selective ion transport across clustered polycation membrane

The ability to manipulate the flux of ions across membranes is a key aspect of diverse sectors including water desalination, blood ion monitoring, purification, electrochemical energy conversion and storage. Here we illustrate the potential of using daily changes in environmental humidity as a continuous driving force for generating selective ion flux. Specifically, self-assembled membranes featuring channels composed of polycation clusters are sandwiched between two layers of ionic liquids. One ionic liquid layer is kept isolated from the ambient air, whereas the other is exposed directly to the environment. When in contact with ambient air, the device showcases its capacity to spontaneously produce ion current, with promising power density. This result stems from the moisture content difference of ionic liquid layers across the membrane caused by the ongoing process of moisture absorption/desorption, which instigates selective transmembrane ion flux. Cation flux across the polycation clusters is greatly inhibited because of intensified charge repulsion. However, anions transport across polycation clusters is amplified. Our research underscores the potential of daily cycling humidity as a reliable energy source to trigger ion current and convert it into electrical current.

A Prototype Design of a Vertical Axis Wind Turbine as One of the Renewable Energy Sources in Brunei

Background: According to the Asia Wind Energy Association, Brunei can harness the power of wind energy to meet its future demands for a reliable energy source that is both renewable and non-polluting. Objective: A preliminary study to design and manufacture wind turbines needs to be initiated earlier especially in the Brunei with has potential wind energy. Methods: This preliminary study compares several Vertical Axis Wind Turbine (VAWT) types and examines the optimal design in terms of mechanical parts for wind speed characteristics in Brunei. The project focuses on the engineering design stages to obtain a selected design that differs from other available designs. Results: The preliminary study successfully generated a small amount of electricity from the mechanical rotation of the VAWT. Conclusion: Although the preliminary study can generate a small amount of electricity, several design parameters need to be improved in further study. Proper manufacturing technologies are also needed to fabricate a better VAWT.

An overview of hydrogen storage technologies – Key challenges and opportunities

Hydrogen energy has been proposed as a reliable and sustainable source of energy which could play an integral part in demand for foreseeable environmentally friendly energy. Biomass, fossil fuels, waste products, and clean energy sources like solar and wind power can all be employed for producing hydrogen. This comprehensive review paper provides a thorough overview of various hydrogen storage technologies available today along with the benefits and drawbacks of each technology in context with storage capacity, efficiency, safety, and cost. Since safety concerns are among the major barriers to the broad application of H2 as a fuel source, special attention has been paid to the safety implications of various H2 storage techniques. In addition, this paper highlights the key challenges and opportunities facing the development and commercialization of hydrogen storage technologies, including the need for improved materials, enhanced system integration, increased awareness, and acceptance. Finally, recommendations for future research and development, with a particular focus on advancing these technologies towards commercial viability.

Smart and Sustainable Energy Consumption: A Bibliometric Review and Visualization

This paper presents a comprehensive bibliometric review and visualization of smart and sustainable energy consumption, delving into the challenges and opportunities of developing renewable and non-renewable energy sources. The study examines research trends and emerging themes about integrating smart solutions and sustainable energy resource consumption. The analytical methods used involve thoroughly analyzing empirical data, case studies, and review papers to map the research landscape. The results highlight dominant research topics, influential authors, and publication timelines in this field. The review identifies the key challenges in harnessing renewable and non-renewable energy sources, including the need for reliable energy sources, energy storage systems, and smart grid technologies. The paper concludes with insights into the most effective practices for promoting smart and energy-efficient methods while emphasizing the complexity of sustainable energy solutions.

Modified sliding mode control for seamless integration of P.V. energy in A.C. grid

Solar energy is a potentially abundant and reliable source of renewable energy. While it can undoubtedly increase grid reliability and efficiency, the inverted voltage generated from P.V. sources may introduce distortion into the A.C. grid. The proposed control mechanism, modified sliding mode control (MSMC), can seamlessly integrate the inverter output generated by obtaining D.C. voltage from the boost converter linked with the P.V. output. This research confirms the validity of the proposed method by comparing its results with a similar system that is only integrated through filters and with a system with a P.I. control technique. The simulation proves the effectiveness of seamlessly integrating the Photovoltaic (P.V.) source into the A.C. grid.

Building integrated photovoltaic with hydrogen storage as a sustainable solution in Iranian rural healthcare centers

The reliable and sustainable energy source for supplying energy demand of rural health clinic centers (RHCC) is very important especially in Coronavirus Disease 2019 (COVID-19) epidemic. However, diesel generator due to the fuel supply and environmental challenges can’t be a sustainable source. In this regard a standalone energy system based on solar with hydrogen storage/fuel cell system is proposed to solve this issue. In the present study, five regions with different climatic conditions in Iran are considered and the layout are evaluated for the first time in RHCC with a load demand of about 10 kWh/day. HOMER software is used to optimize the size of the equipment. The results showed the capacity factor (CF) of photovoltaic panels is about 17.4–20.4%, while the CF of electrolyzers is 17–25%. The CF of fuel cell remains similar at about 36–37%. The net present value of the systems ranges 22,000–27,000$ and the levelized cost of electricity ranges 0.28–0.34 $/kWh, with the lowest (highest) values in Kerman(Gylan). The proposed system reduced the consumption of approximately 1,830 L of diesel, resulting in significant environmental benefits. The hybrid renewable energy system combining solar and hydrogen storage can be considered as sustainable solution in RHCC in Iran.

How does natural resource depletion affect energy security risk? New insights from major energy-consuming countries

The continuous supply of reliable and affordable energy sources is crucial for driving a nation's economic activities. The phenomenon of continuous energy supply at affordable prices is called energy security. To date, more than two-thirds of the global energy demand is met by non-renewable energy derived from natural resources. The empirical connection between natural resource depletion and energy security risk remains unexplored in the prior literature. Thus, this study analyzes the empirical linkage between natural resource depletion and energy security risk by applying the CS-ARDL and PMG-ARDL models. As per our findings, natural resource depletion increases long-term energy security risks Globally and in Asia, America, Europe, and Africa. In short run, the role of natural resource depletion is mostly insignificant in energy security risk. In contrast, the GDP, financial development, trade openness, and technological development help reduce long-run energy security risk in all regions except Africa. In the short run, only GDP and trade openness help reduce energy security risks in most regions. Therefore, policymakers should focus on efficiently utilizing natural resources to mitigate energy security risks.

A statistical study for the impact of REMS and nuclear energy on carbon dioxide emissions reductions in G20 countries

Renewable and nuclear energy are seen as clean and eco-friendly substitutes for energy derived from fossil fuels. Which of the two is better, though, is still up for debate. In order to meet their combined global energy objectives and perhaps become carbon neutral or even carbon negative in the near future, a shift to additional renewable energy sources and nuclear energy will be necessary. One such method of improving energy usage through the implementation of a renewable energy management system (REMS) that will help attain a continuous and reliable source of energy, allowing for the proactive and effective management of renewable assets and dependable supply. This article investigates attitudes and opinions about nuclear and renewable energy production technologies by analyzing the dependence of carbon dioxide (CO2) emissions on non-renewable energy sources, renewable energy sources, and nuclear energy in the group of twenty (G20) countries, over the period from 2000 to 2021. This study employs advanced panel data econometric techniques in the presence of outliers in the G20 dataset, utilizing a robust random coefficient regression (RRCR) model via the M-estimation approach to study the impacts of non-renewable, renewable, and nuclear energy use with respect to CO2 emission mitigation in G20 countries. The overall conclusions of the econometric analysis confirm renewable and nuclear energy's importance in reducing CO2 emissions. We can conclude that the robust M-estimate approach is the best estimation technique for the G20 dataset, as compared to the classical estimation methods in the presence of outliers. The results show that for every percentage point of energy consumption that falls into the category of non-renewable energy, CO2 emissions will increase by 2.5737% for all G20 countries. Also, A 1% rise in renewable energy consumption reduces CO2 emissions by 1.0566% for all G20 countries. Similarly, a 1% increase in nuclear energy consumption will reduce CO2 emissions by 5.5703% for all G20 countries. Therefore, we can conclude that energy derived from renewable sources and nuclear energy greatly cuts CO2 emissions in all G20 countries. Total energy consumption, on the other hand, increases CO2 emissions in the long run. According to these findings, it is pivotal for the G20 countries to increase nuclear energy use and employ REMS to reduce the majority of G20 country's reliance on fossil fuels in order to minimize CO2 emissions. These findings are vital for understanding the relationship between these variables and the implementation of new or revised policies and initiatives supporting carbon neutrality at the G20 countries and national levels.