Journal of Renewable Energy and Environment
Volume:11 Issue: 1, Winter 2024

Microbial Fuel Cells (MFCs) represent an environmentally-friendly approach to generating electricity, but the need to study variation parameters to find improvement conditions has been an important challenge for decades. In this study, a single-chamber MFC was designed to investigate the key parameters such as the concentration and type of bacteria, chamber temperature, electrode spacing, and substrate rotation speed that affected the performance of MFCs. Therefore, two types of bacteria, Shewanella oneidensis (S.one) and Escherichia coli (E. coli), were compared as microorganisms. Then, the function of MFC was investigated under the following condition: three temperatures (30 ℃, 45℃, and 60℃), three bacterial concentrations (0.5% (v/v) (4.5 mg/ml), 1% (v/v) (9mg/ml), and 1.5% (v/v) (13.5mg/ml)), electrode distances (2 cm, 3 cm, 4cm), and substrate speeds (100 rpm, 150 rpm, 200 rpm). Ultimately, (S.one) bacteria, a chamber temperature of 45 ℃, a bacterial concentration of 1% (v/v) (9mg/ml), a cathode-anode spacing of 3 cm, and a rotation speed of 150 rpm proved to be the most efficient parameter settings for the constructed microbial fuel cell. The maximum voltage and highest power density were 486.9 mV and 9.73 mW/ , respectively, with a resistance of 7500 ohms. These results are meaningful for determining and improving important parameters in an MFC device.

Rising energy production and consumption, particularly from fossil fuels, pose substantial threats to both global climate and human well-being. Conventional fossil fuel technologies, as primary energy sources in power plants, predominantly generate pollutants during power generation. Conversely, renewable energy technologies are anticipated to contribute to pollution primarily during equipment manufacturing. The combustion of traditional fuels gives rise to significant volumes of greenhouse gases (GHGs) and hazardous substances, leading to escalated costs for individuals and the worldwide populace. External costs attributed to coal-fired power plants range from 4.0 to 9.5 cents per kilowatt-hour, nearly three times higher than those of gas-fired power plants, and multiple times greater than the expenditures linked with renewable energy technologies. The substitution of non-renewable fuels with clean energy sources stands as an efficacious approach to curtailing atmospheric pollution and the concomitant external expenses. On a global scale, an annual savings of up to 230 billion dollars is potentially attainable by achieving a 36% share of clean energy within the global energy mix by 2030. This topic has garnered the attention of policymakers worldwide. Consequently, this study undertakes an examination of the environmental ramifications and social costs associated with diverse energy sources.

Solar power energy continues to be a renewable and sustainable source of energy in the coming year due to its cleaner nature and abundant availability. Maximum Power Point Tracking (MPPT) is a technique used in solar power systems to extract maximum power from photovoltaic (PV) modules by tracking the operating point of the modules. MPPT is essential for achieving optimal power output from a solar panel, particularly in variable weather conditions. Traditional MPPT techniques are subject to limitations in handling the partial shading conditions (PSC). To ensure the tracking of maximum power point while boosting the MPPT's overall efficacy and performance, Machine Learning must be integrated into MPPT. As per the reviewer work, ML techniques have the potential to play a crucial role in the development of advanced MPPT systems for solar power systems operating under partial shading conditions and to compare the performance of existing ML-MPPT in terms of accuracy, response time, and efficacy. These review papers technically analyze the result of ML-MPPT techniques and suggest the optimum ML-MPPT tactics that are Q learning, Bayesian Regularization Neural Network (BRNN), and Multivariate Linear Regression Model (MLIR) to achieve optimum outcomes in MPPT under PSC. Further, these techniques can offer efficiency greater than 95%, tracking duration less than 1sec, and error threshold of 0.05. In the future, the reviewer may propose simulation work to compare the optimal algorithms.

The design of novel and effective receivers is one of the most challenging aspects of solar energy harvesters, especially for Parabolic Dish Collectors (PDCs). The variation of solar flux due to the solar time and sky clearance index can affect the output thermal energy of the collector. One of the major approaches to producing a uniform performance for the PDCs is the utilization of Phase Change Materials (PCMs). The PCMs can absorb the solar flux at its peak instances. Subsequently, due to the thermal buffering effect, excess energy is released in cases with lower solar flux. In the present study, a novel design of receiver with multiple layers of thin PCM inserted between the passages of the working fluid is numerically simulated. The simulations are designed to determine the effect of operational parameters on the performance of the examined novel receiver. According to the results, by increasing the Heat Transfer Fluid (HTF) flow rate from 60 to 90 kg/h, the system efficiency is increased from 53.8 to 66.4 %. 

The primary objective of the proposed work is the design of a Hybrid Teaching Learning-based Horse Herd Optimization Algorithm regulated Fractional Order Tilt Derivative Acceleration with Filter (TLBO-HHOA regulated FOTDAF) controller for enhanced performance and enhanced devaluation of harmonic components of the grid-connected photovoltaic system. The solar photovoltaic system incorporates constituents such as a photovoltaic array, interleaved fractional order boost converter (IFOBC), Reduced Switch Multilevel Inverter (RSMI), and TLBO-HHOA regulated FOTDAF controller. IFOBC is preferred over boost converter because of its low ripple voltage, faster transient response, high efficiency, low duty cycle, reduced EMC, and improved reliability and stability. In this control strategy, the control logic is formulated by using a Tilt Integral Derivative Controller (TIDC), whose control parameters are considered as a function of the error to improve the robustness. The validation, better performance, and superiority of TLBO-HHOA regulated FOTDAF are established by comparative result analysis using modern controllers. This study implements TLBO-HHOA-regulated FOTDAF and applies Support Vector Pulse Width Modulation (SVPWM) technique. The proposed model managed to achieve improvements in overall system response and reduced harmonic distortions as well as better accuracy, improved stability, improved robustness, and better capabilities to handle system uncertainties.

This paper  presents an analytical expression for the temperatures of the plant, room air, and solar cell, as well as the electrical efficiency, for a photo-voltaic thermal (PVT) roof façade of a greenhouse integrated semi-transparent photovoltaic thermal (GiSPVT) system. The expression considers climatic variables such as solar intensity and ambient air temperature, as well as design parameters such as the area of the PV module, electrical efficiency under standard test conditions (STC), temperature coefficient, and various heat transfer coefficients. Using monthly numerical computations for different parameters in Indian climatic conditions, this study evaluates energy matrices such as energy payback time (EPBT), energy production factor (EPF), and life cycle conversion efficiency (LCCE) for various solar cell materials, including single-crystalline (c-Si), multi-crystalline (mc-Si), amorphous (a-Si), copper indium gallium diselenide (CIGS), and cadmium telluride (CdTe), with and without thermal exergy. Considering that the life span of greenhouse materials varies from 5-30 years for low cost, medium, and high-tech greenhouses, different solar cell materials are recommended for different life spans of GiSPVT. Therefore, this study recommends suitable solar cell materials for known greenhouse
designs:(a) The EPBT and (LCCE considering thermal exergy for c-Si/mc-Si range from approximately 3.5 to 4.5 years and 13 to 22%, respectively. Consequently, these values render crystalline silicon solar cells highly fitting for application in high-tech greenhouses with a comparable lifespan.
(b) For the CIGS, the EPBT is 1.17 years with an associated LCCE (including thermal exergy) of 16.44%. This establishes CIGS as particularly well-suited for deployment in cost-effective greenhouse environments
designs:(a)  EPBT and LCCE for c-Si/ mc-Si are about 3.5 to 4.5 years and 13 to 22%, respectively, with respect to thermal exergy. Hence, these two solar cell materials are most suitable for high-tech greenhouses that are similar to crystalline solar cell in terms of life cycle.
 (b)  EPBT and LCCE of CIGS are 1.17 years and 16.44%, respectively, with respect to thermal exergy. Hence, the solar cell material of CIGS is most suitable for low-cost greenhouses.

This article investigates the utilization of thermal management systems for electric car applications and their optimization through the incorporation of phase change materials (PCMs) and nanoparticles (NPs). In recent years, with the expansion of the automobile sector and the introduction of electric vehicles (EVs) into the market, new challenges have emerged. One critical challenge is managing heat in lithium batteries, as the performance of these batteries can deteriorate significantly outside the normal temperature range. Consequently, this research delves into the reasons favoring passive thermal management systems over active ones in the electric vehicle industry. Additionally, it elucidates the motivations behind opting for active thermal management systems and explores research on various types of phase change materials (PCMs) utilized in this domain, along with the impact of nanoparticle additives. The objective is to comprehensively understand why researchers employ different types of phase change materials (PCMs) in this field and how these materials can influence battery cooling, including factors such as the thermal conductivity of PCMs. It also scrutinizes which materials and simulations have been proposed for these systems and assesses their potential applicability to other vehicle components, as several components of electric vehicles that remain unexamined in the literature become increasingly apparent. In conclusion, the proposal is considering the use of phase change materials in other automobile components.  

Floating photovoltaic solar systems offer numerous advantages, including reduced land usage, diminished water evaporation, and lowered thermal losses compared to terrestrial installations. If widely adopted, this system has the potential to generate a staggering 10,600 TWh of electricity. The widespread implementation of this technology could curtail water evaporation by approximately 30%. Floating solar power plants operate at temperatures about 20°C cooler than their terrestrial counterparts, enabling floating panels to yield up to 33.3% more energy. Furthermore, floating photovoltaic systems exhibit an 18.18% greater efficacy in curbing greenhouse gas emissions compared to their land-based counterparts. The heightened adoption of this system is driven by diverse factors, including escalating energy demand, ecological concerns, land-use constraints, and water scarcity, all contributing to sustainability. Despite the manifold benefits of these systems, there exist drawbacks associated with this technology, such as heightened panel corrosion, challenges in cleaning, and potential adverse environmental impacts that need to be addressed. This study meticulously examines the merits and challenges of floating photovoltaic systems in comparison to land-based installations through the content analysis method, meticulously categorizing pertinent research within the existing literature. Tailored approaches to cooling and cleaning, suited to the distinct installation conditions and environments of these systems, are concisely outlined. Through a comprehensive literature review and a meticulous comparison of cooling methods, it has been ascertained that the application of such strategies for floating solar plants yields an efficiency increase of 5-7% in the short term. Consequently, this study furnishes an initial guide for researchers and designers engaged in the development of both floating and land-based solar photovoltaic systems.

The design of a Spotted Hyena Optimization Algorithm-Variable Parameter Tilt Integral Derivative with Filter (SHO-VPTIDF) controller for improved performance and enhanced devaluation of harmonic components of grid-connected photovoltaic systems is the main objective of the suggested manuscript. The SHO-VPTIDF controller is proposed by reformulating Tilt Integral Derivative Controller with Filter (TIDCF). The TIDCF is characterized by longer simulation time, lower robustness, longer settling time, attenuated ability for noise rejection, and limited use. This research gap is addressed by replacing the constant gains of TIDCF by variable parameter tilt integral derivative with filter. The VPTIDF replaces the constant gains of TIDCF with error varying control parameters to improve the robustness of the system. The photovoltaic system with nonlinearities causes power quality issues and occasional faults, which can be detected by using Levenberg-Marquardt Algorithm (LMA) based machine learning technique. The novelties of the proposed manuscript including improved stability, better robustness, upgraded accuracy, better harmonic mitigation ability, and improved ability to handle uncertainties are verified in a Matlab simulink environment. In this manuscript, the SHO-VPTIDF and the Direct and Quadrature Control based Sinusoidal Pulse Width Modulation (DQCSPWM) method are employed for fault classification, harmonic diminishing, stability enhancement, better system performance, better accuracy, improved robustness, and better capabilities to handle system uncertainties.

Failure Mode and Effects Analysis (FMEA) is utilized for risk appraisal in various domains. In the FMEA methodology, each failure mode is evaluated by considering three risk factors: severity (S), occurrence (O), and detection (D). Subsequently, the Risk Priority Number (RPN) is obtained by multiplying these listed factors. This study introduces the Deviation Value Step-Wise Method (DVSM) as a new mathematical model for determining the scores of the SOD factors. This methodology consists of three main steps. Firstly, the FMEA technique is used to identify failure modes. Then, the DVSM is employed to assign weights to the SOD components. In this step, relative importance is determined based on linguistic variables. The third step involves ranking failure modes using the weighted RPN. Two general examples and a case study of two-pipe heat exchanger failure modes are considered to validate the proposed model and test the obtained results. The results demonstrate that the suggested approach has enhanced the overall prioritization of failure modes. This enables the Decision-Maker (DM) to identify primary failure modes and formulate corrective/preventive actions. Finally, both sensitivity analysis and energy efficiency investigation have been performed.

In the present day, a significant portion of the world's energy demand can be satisfied through the utilization of renewable energy sources. Solar energy, in particular, holds a pivotal position owing to its numerous merits. However, it faces a challenge known as mismatch response within the photovoltaic (PV) modules of an array when subjected to partial shading. This issue restricts power output, leads to the formation of local hot spots, and results in the underutilization of PV modules within the array. One of the most effective solutions to address this problem is optimizing the PV array (PVA) configuration to maximize output power under partial shading (PS) conditions. In this research paper, we commence with a thorough numerical analysis under uniform shading conditions. Following that, we scrutinize the performance of six traditional PVA configurations and three hybrid PVA configurations under PS conditions. The results consistently indicate that the Total Cross Tied (TCT) configuration outperforms others in all shading scenarios in terms of mitigating mismatch power loss, enhancing the fill factor, and improving overall efficiency.

The study explores the impact of surface orientation and tilt on incident solar irradiation. It was conducted in M'Sila, an Algerian province, from February to June. A number of experiments were carried out using an experimental setup consisting of a heliometer and a slant changer, which allowed for the variation of the tilt angle. Nineteen tilt angles ranging from 0° to 90° were investigated for the four main directions: North, South, East, and West. The obtained outcomes were statistically analyzed. At east and south orientations, incident solar irradiance rose as a function of tilt angle, reaching a maximum at the optimal angle, and then gradually decreased. Generally, the incident solar irradiance decreased as the tilt angle increased in the case of west and north orientations. The tilt angle of the exposed surface as well as the sun's elevation in the sky affected the amount of intercepted energy significantly at each orientation (p<0.05). When the sun was low in the sky, the south orientation was most preferred for an inclination greater than or equal to 25°. The north-facing surfaces with steep slopes (β³ 55°) received the least amount of solar radiation. These results hold great importance, particularly in the building sector, as they can be utilized to achieve energy saving.

The power generation sector accounts for a significant portion of GHG emissions, and many countries strive for the large-scale adoption of renewable generation. Although the intermittent nature of renewables brings about complications in energy system planning, the share of renewable generations is increasing to the greatest extent. The wind generation has drawn increasing attention to expanding the use of renewable energy to reduce carbon emissions from the power generation sector, and the estimation of capacity factor is crucial in energy system modeling. This study develops a mathematical model for estimating the capacity factor of a wind farm with the consideration of outage probability of individual turbines. In addition, the power curves and wind speed distribution of the wind farm need to be estimated, which is demonstrated with a wind farm in Korea. It is asserted that the proposed method may render the wind farm capacity factor effectively. Thus, the results from this study can be useful for energy system modeling involving wind generations.

Preserving food from harvest to consumer level is a challenge in the agriculture sector. Drying is a crucial post-harvest technique that lowers moisture to levels suitable for storage. Solar drying is a traditional renewable energy drying process. Different solar drying methods have been developed to speed up the drying process and maintain the product's nutritious content. Indirect solar drying is one of the efficient drying methods that has better control over the drying temperature. Indirect solar drying has developed into a desirable, effective, and environmentally responsible drying technique when combined with solar collectors and thermal storage. Flat plates, evacuated tubes, and concentrated solar collectors are used in indirect solar dryers along with direct air heating or thermal storage systems. This study aims to review the improvement in the drying rate with different air heating mechanisms. Flat plate collectors with liquid working fluid are employed to heat the air, whereas in evacuated tube collectors, the air is directly heated passing through the tubes. Working fluids, air temperature, air velocity, and solar radiation are important dryer parameters affecting the drying rate. The paper also discusses the usage of heat storage devices for continuous drying operations. The drying time is greatly reduced through integration with latent and sensible storage technologies. Products that have been dried using indirect solar dryer and appropriate drying models are tabulated. Aspects of indirect solar drying and challenges in drying time reduction are also reported.

The INVELOX system is an innovative approach that offers improved energy absorption efficiency from wind flow and reduced costs by utilizing smaller wind turbines. This research focuses on investigating the steady-state performance of one, two, or three wind turbines arranged within the venturi section of the system. A comprehensive modeling approach using an improved Blade Element Momentum (BEM) theory is proposed and implemented as a MATLAB code. The code incorporates Prandtl's tip and hub loss factors, as well as turbulent wake corrections. The accuracy of the code is validated against experimental and numerical data. The results demonstrate that in a three-rotor tandem configuration in the INVELOX system, the power extracted from the second and third turbines is 0.54 and 0.24 times the power of the first turbine, respectively. Furthermore, for a two-turbine arrangement in the venturi section, the total power extracted from the system is 53.9% higher than that of a single turbine layout. In the case of a three-turbine configuration, the total power increases up to 1.78 times compared to a single turbine. The proposed model is suitable for geometric optimization and parameter studies. The system's performance is evaluated in terms of tip speed ratio, and the effects of different correction models are analyzed, including the local changes in forces and moments.