Photovoltaic Research Articles

Experimental validation of a novel hybrid Equilibrium Slime Mould Optimization for solar photovoltaic system

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems.

Assessment of photovoltaic system in existence of nanomaterial cooling flow

In this study, a photovoltaic (PV) system was enhanced through the combination of a cooling duct utilizing a nanofluid composed of water and Al₂O₃ nanoparticles, aimed at optimizing thermal regulation and improving electrical efficiency. A novel approach was introduced by systematically examining the effects of channel cross-sectional shapes and fin arrangements on heat dissipation. Using a single-phase simulation model, the thermal performance of the nanofluid was evaluated across various nanoparticle shapes, providing new insights into the relationship between geometry and nanofluid cooling efficacy. The results demonstrated that altering the cross-sectional shape generally reduced thermal performance, but strategic fin configurations significantly enhanced heat transfer. The optimal design, featuring eight shorter fins arranged around an eight-lobed pipe, resulted in a 4.3% improvement in thermal performance. Additionally, blade-shaped nanoparticles were identified as the most effective, enhancing heat absorption by 1.15% compared to pure water. This research presents the first combination of advanced nanofluid cooling with a detailed analysis of geometric factors (cross-section and fin design) in PV systems. The findings provide practical guidelines for improving heat management in PV cells, ultimately leading to increased electrical efficiency and an extended operational lifespan. These insights hold promising implications for the design of more efficient solar energy systems and could inform future thermal management solutions in renewable energy applications.

Virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimization

Abstract The hybrid microgrid (HMG) possesses power generation, storage, and distribution capabilities, serving as an integrated foundational structure for advanced localized distribution networks. However, due to significant discrepancies in load demands and energy consumption among different users, the photovoltaic (PV) generation output and end-user load requirements exhibit unpredictability, resulting in relatively low self-sufficiency ratio (SSR) and self-consumption ratio (SCR) of the HMG PV system. To address this issue, this study proposes a virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimization. Initially, a bidirectional virtual energy dispatching system model based on energy provider/buyer classification is constructed, optimizing load demands and energy management of both the load side and the main utility grid (MUG) while considering demand response. Subsequently, a Lyapunov optimization-based bidirectional virtual energy dispatching algorithm (LOBVED) is introduced, optimizing queueing systems in stochastic networks based on drift-plus-penalty technique to resolve the dynamic interactions among stability, performance, and energy self-sufficiency in the HMG environment, aiming to maximize the PV SSR and SCR of the HMG while ensuring the reliability of battery energy storage (BES) energy queues. Finally, the effectiveness of the proposed method is validated through MATLAB simulations.

Integrated RES With Intelligent MPPT For Efficient Power Generation & Wireless Transmission for PV Applications

The increasing global energy demand and the urgent need to shift to sustainable practices have made the integration of renewable energy sources (RESs) into distribution power systems imperative. This project's main objective is to implement rooftop photovoltaic (PV) systems as an essential part of low-voltage (LV) DC networks' building-integrated centralized generation Maximum Power Point Tracking (MPPT) using Artificial Neural Networks (ANNs) is used to maximize power extraction from photovoltaic (PV) panels and boost power generation efficiency, particularly in partially shaded circumstances. After that, the PV system's generated power is sent to a Luo converter, which effectively tracks and optimizes the power production. For wireless power transmission, the Luo converter's output is then fed into a high-frequency converter. This wireless power transmission improves the system's adaptability and scalability by facilitating smooth energy transfer without the requirement for physical connections. An isolation transformer is attached to the high-frequency converter's output in order to guarantee the system's dependability and safety. The high-frequency converter is isolated from the downstream components by the isolation transformer, which also offers protection against electrical risks. Finally, a battery made especially for use in electric vehicle (EV) applications receives the transformer's isolated output, which is also supplied to DC loads. Finally, we will use the MATLAB 2021a / Simulink program to do a number of numerical simulations in order to validate the suggested controls. The output voltage of 130v is stored in the battery if a voltage of 65 v is taken as output from the photovoltaic system.

A hybrid renewable energy system for Hassi Messaoud region of Algeria: modeling and optimal sizing

The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy security and reducing environmental impacts. This study focuses on optimizing a hybrid renewable energy system (HRES) for off-grid applications in the Hassi Messaoud region of Algeria to balance technical performance, economic viability, and environmental sustainability.A hybrid system consisting of photovoltaic (PV) panels, wind turbines (WT), fuel cells (FC), and diesel generators (DG) was modeled and optimized using a genetic algorithm (GA). The optimization process aims to minimize the annual cost of the system while ensuring high reliability, as measured by the loss of power supply probability (LPSP), and maximizing the use of renewable energy. A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. The optimized HRES demonstrated that renewable sources (PV and WT) provided 77% of the total energy demand, with an overall system cost of 0.18080$×kWh−1, significantly lower than recent studies, which reported costs between $0.213 and 0.609$×kWh−1. FCs contributed 14% to the load, whereas DGs were limited to 8% to minimize emissions, resulting in annual CO2 emissions of 10,865 kg and a relative emission rate of 3.608 gCO2eq×kWh−1. Economic analysis showed that DGs and FCs accounted for 44% and 24% of the annual cost, respectively, highlighting the impact of backup systems in ensuring reliability.Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system, and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability. Additionally, the social analysis highlighted a renewable fraction (RF) of 91.5%, emphasizing the contribution of the system to sustainable energy practices. These findings validate GA-based optimization as a superior method for designing cost-effective, reliable, and environmentally sustainable HRES, offering significant potential to reduce fossil fuel dependency in industrial applications. These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability.

It takes a village: The role of community attributes in shaping solar photovoltaic adoption intention in Germany

The shared attributes, attitudes, and beliefs of communities can either act as a catalyst or a barrier to the adoption of pro-environmental behaviours such as the adoption of solar photovoltaic (PV). Using a multilevel mixed-effect modelling approach on survey data from 1800 German homeowners, we examine how individual/household and objective community attributes and their interplay shape the intention to adopt solar PV. Research findings indicate that a significant explanation of intention to adopt solar PV is related to unobserved community characteristics (13 %); with community level covariates including a proxy for spatial peer effects explains 8 % of this variance. Testing for spatial peer effects via a cross-level interaction, our findings suggest that a higher diffusion rate of PV installations in a community can positively influence intention to adopt Solar PV for households who on average have a low intention to adopt. Understanding the degree that individual versus area-based effects impact intention to adopt can provide policymakers with a framework to develop policies to incentivize the uptake of Solar PV among traditionally “hard-to-convince” population groups at the local level.

Enhanced frequency control of a hybrid microgrid using RANFIS for partially shaded photovoltaic systems under uncertainties

Nowadays environmental concerns and fossil fuel limitations, as well as economic benefits and technical issues such as reliability lead conventional distribution networks to smart microgrids, where the renewable energy resources are merged with the grids. Nevertheless, the systems face new challenges due to the intermittent nature and uncertainties in the distributed generations, which cause frequency fluctuations in the microgrid. The photovoltaic cells are the main part of the contemporary microgrids. Although the photovoltaic (PV) systems depend on solar irradiance, and temperature and are affected by the partial shading phenomenon they could contribute to improving the microgrid frequency stability with a proper control scheme. In this paper, the frequency control strategy is designed for a hybrid stand-alone microgrid, which is robust against load disturbances, variations in weather conditions, and uncertainties in the microgrid parameters. The proposed intelligent control scheme relies on the Recurrent Adaptive Neuro Fuzzy Inference System (RANFIS). The Whale Optimization Algorithm (WOA) is employed to optimize the RANFIS controller structure and generate the parameters of membership functions. In this multi-objective optimization, the objectives are settling time (ST), overshoot (Osh), and Integral Square Error (ISE). The simulation results verify the high robustness and performance of the proposed RANFIS controller, compared to other controllers, during various operational circumstances, as well as the sporadic behavior of renewable energy resources (RES) such as fluctuations in solar radiation and certain uncertainties in the microgrid parameters.

Identifying the parameters of photovoltaic cells using Gaussian bare-bone imperialist competitive algorithm with opposition-based learning mechanism

Extracting the precise parameters of photovoltaic (PV) cells has become very important for simulation, evaluation, control, and optimization of PV systems. However, it is still a challenging task to accurately and reliably extract the parameters of PV cells. To solve this difficult problem, in this paper, a new meta-heuristic algorithm called Gaussian bare-bone imperialist competitive algorithm with opposition-based learning (OBL-GBBICA) is proposed to extract the parameters of PV cells. To strengthen the exploring ability and speed up the convergence, opposition-based learning (OBL) is introduced into an imperialist competitive algorithm (ICA) for two considerations. First, OBL is adopted in the population initialization to produce a high-quality population. Second, the OBL is introduced into the assimilation step to guide ICA to explore more promising regions. The above improvements not only speed up the convergence of ICA but also enhance its searchability, which is beneficial to improving the accuracy and reliability of identification results. Experimental results show that OBL-GBBICA exhibits great superiority in extracting the PV cells parameters, compared with other methods in the literature.

On the performance and thermal stability of solar cell based on CIGS-Sb2S3 combination with >35% power conversion efficiency

This study presents a solar cell design utilizing a CIGS (copper-indium-gallium-selenide) absorber and Sb2S3 (antimony trisulfide) back surface field (BSF) layers, targeting high photovoltaic (PV) performance with an emphasis on minimum possible effect of ambient temperature. We simulated a solar cell design consisting of zinc oxide, surface defect layer, zinc sulfide, CIGS layer, and an Sb2S3 layer using SCAPS-1D software. Our findings indicate that 200 nm Sb2S3 layer and a 1600 nm CIGS layer is the preferred combination for achieving high PV performance and appropriate J-V characteristics of the proposed solar cell. For this design, the achieved values of VOC (open circuit voltage), JSC (short circuit current density), PCE (power conversion efficiency), and fill factor (FF) are 1.069V, 42.08 mA/cm2, 35.94%, and 80.31%, respectively. The PV performance of the proposed solar cell is substantially better than the solar cell design without BSF layer as well as recently reported (2023-24) solar cell designs. This study further examines the impact of elevated ambient temperatures (295–360 K) on the PV performance. Our simulation results show that operating the proposed solar cell at moderately elevated temperatures is not a significant issue owing to small power temperature coefficient (-0.034% per K), which is comparable to that of commercially available solar cells. These findings are expected to contribute to the ongoing advancement of PV solar cells, aiming for higher PCE and improved stability, including thermal stability. Proposed solar cell with low PTC and high PCE can be suitable for space applications where temperature fluctuation is severe, as well as in tropical areas.

A study on the path planning and optimization of carbon peaking and carbon neutrality in the highway service area

The transportation sector is a major source of greenhouse gas emissions. Reducing emissions of the Highway Service Area (HSA) can help decrease the sector's carbon footprint and serve as a model for green transformation. Consequently, this study firstly employs the Life Cycle Assessment (LCA) to calculate the carbon emissions during the operational phase of a certain HSA in 2022, and then analyses the emission structure. Subsequently, four emission reduction pathways are identified, including Photovoltaic (PV) power generation, electrification retrofitting, forestry carbon sinks, and green roofs, in terms of both Three 100 Initiatives and carbon neutrality measures. On this basis, the planning of carbon peak and carbon neutral strategies for this service area under different scenarios are carried out, taking into account the dual carbon targets and relevant policies. The findings indicate that: (1) the HSA emitted approximately 766.84 tons of carbon emissions in 2022, with 96.53 % from purchased electricity. (2) PV power generation offers the optimal emission reduction benefits among four emission reduction pathways. (3) In carbon peaking scenarios, initiating PV construction is the optimal emission reduction strategy. (4) In most carbon neutrality scenarios, the simultaneous implementation of PV construction and bamboo planting can meet the neutrality requirements by 2060. However, if the HSA continues to develop economically after 2030, the economy could grow until 2035 to meet neutrality requirements. These findings can guide emission reduction strategies for other HSAs, accelerating the sector's transition to low-carbon emissions while supporting the development of policies for zero-carbon HSAs.

Promoting the Renewable Energy Zones by implementing the photovoltaic panels in an industrial building

Abstract Environmental protection depends on energy production and use, which are responsible for ∼94% of carbon emissions. The lack of sufficient energy resources has led EU countries to alternatives for Green Energy production. Albania’s national response to climate change has been limited to some small changes mainly in the sector of the integrated water and environmental management legislation. However, in terms of changing the energy law, no effort has been made to prioritize green energy production. Doing so it is expected to contribute to the overall goal of reducing greenhouse gas emissions through the integration of clean energy solutions. The paper is referred to a specific case study focused on renewable energy using photovoltaic panels in an industrial building in Saranda, as the city with the most hours of sunshine per year in Albania. To support renewable energy initiatives, it is being emphasized with the help of statistical methods that Saranda has strong potential to invest in energy production through solar panels, which give rise to long-term renewable energy solutions. In summary, there are being identified three main factors that seemed to contribute to the results of national renewable energy solutions: 1) Creating renewable energy zones, 2) Installing solar panels for electricity generation 3) Enforcing regulations. In such conditions when energy of any kind is the most demanded product, green energy is the best way to manage it. It is being used in any country, but especially in Albania, which has a high average of sunny days, compared to other European countries, is an immediate requirement and, as such it should be stripped of it all useless bureaucracies to enable a higher production of it, even with state subsidies. But development will also have to overcome the above issue by adapting to energy production in small units where bureaucratic hurdles are even smaller.

Life cycle assessment and cost analysis of innovative agar extraction technologies from red seaweeds

Developing efficient and sustainable extraction technologies for valuable biocompounds from seaweed is crucial to overcome the limitations of conventional technologies. This study aims to compare three innovative technologies for agar extraction from two red seaweed species, G. sesquipedale and G. vermiculophylla: subcritical water extraction (performed at 125 °C, 2.5 atm, 1 min, and at 140 °C, 3.8 atm, 1 s), moderate electric fields (applied at 85 °C for 120 min and 95 °C for 180 min), and a combination of both methods. The comparison used life cycle assessment and life cycle costing methodologies, considering a gate-to-gate approach. The combined technology demonstrated the lowest energy consumption, with 67 MJ/kgagar for G. vermiculophylla and 100 MJ/kgagar for G. sesquipedale. A carbon footprint reduction of up to 94 % was obtained when compared to the control, with 15.9 kgCO2 eq. /kgagar for G. vermiculophylla and 20.4 kgCO2 eq. /kgagar for G. sesquipedale. Using photovoltaic panels as alternative energy further cut carbon emissions by 50 %. The cost analysis showed that the combined technology was the most cost-effective extraction method.

Advanced Maximum Power Point Tracking Technique for Photovoltaic Reverse Osmosis Systems

Abstract The paper presents a novel control algorithm for a standalone Photovoltaic Reverse-Osmosis (PV-RO) system without a battery. It highlights the importance of tracking the maximum power tracking points in the photovoltaic panels. The development of new methods has become more urgent than before. The PV-RO system combines solar energy and reverse osmosis technology to provide reliable and sustainable access to clean drinking water in remote areas. Traditional PV-RO systems often require energy storage solutions such as batteries to maintain a constant water supply during periods of low solar irradiation. However, the integration of batteries adds complexity, cost, and environmental impact to the system. The paper presents the development of different MPPT techniques, which are better than traditional techniques (more accurate and faster). The paper also provides a comparison with the studied methods (P&O and Incremental Conductance) and the proposed one.

Improving the efficiency and productivity of solar distillation by creative design and heater and baffle integration

The hemispherical solar still (HSS) is a simple device used to desalinate saline water, but it has low productivity. This study aimed to enhance the evaporation rate of a hemispherical solar still (HSS) through several design modifications. The main innovation involved integrating an upper absorber with hanging wick cords, creating a modified system called the cords wick hemispherical solar still (CWHSS). Additionally, electric heaters powered by photovoltaic panels were incorporated to further boost performance, along with the introduction of squared baffles inside the CWHSS. Experimental results showed that the highest efficiency was achieved with the CWHSS incorporating baffles, heaters, and a condenser (CWHSS-B), leading to a 258% increase in distillate output and a 66.5% thermal efficiency. Under optimal conditions, the distillation rates were 4000 mL/m²/day for the HSS and 14,300 mL/m²/day for the CWHSS-B with heaters. Furthermore, the cost of water treatment was calculated at $0.022 per liter for the HSS and $0.016 per liter for the CWHSS-B, indicating significant cost benefits with the modified design.

Effect of Thermal Environment on Heat Transfer Mechanism of Solar-Powered Balloon

Solar energy units, as an ideal alternative, can be supplied to the balloons by mounting them over the envelope of the balloon. To avoid superheating and superpressure, the solar-powered balloon’s thermal efficiency should be controlled. In the current research, the thermal model of a solar-powered zero-pressure balloon has been built up and simulated in FORTRAN via iterative techniques and validated with published experimental data. The simulation of stratospheric solar-powered balloon flight has been carried out in real seasonal atmospheric conditions. The temperature variation of solar panels, interior helium, and balloon envelope material has been observed and compared with the unpowered balloon in winter and summer atmospheric conditions. The output power performance of the photovoltaic panel placed over the balloon with and without thermal effect has been reported. Furthermore, the characteristic length, angle, and area of the solar panel effects on photovoltaic panel temperature and output power are discussed in detail. The maximum temperature of the helium and envelope of the solar-powered balloon is obtained as 350.03 K and 351.19 K, respectively, and is notable in the summer solstice compared with the unpowered balloon. This research would help design the energy unit of the stratospheric balloon for long endurance.

Design and analysis of zero-energy and carbon buildings with renewable energy supply and recycled materials

Given the notable consumption of fossil fuels, buildings prioritize their energy utilization. This paper’s aim is to explore the primary strategies in attaining zero-energy and zero-carbon buildings. The investigation employs two specialized software programs: Design Builder, which analyzes energy usage, and PV Syst, which evaluates renewable energy requirements. The study is conducted in Fort Myers, USA, and Dubai, UAE, leveraging diverse regional and climate discrepancies, and real-world data on zero-energy and carbon constructions for comparison and validation. Within the Design Builder software, the research examines four strategies, with the first serving as the realistic baseline. By implementing the second strategy, utilizing internal shading devices such as Shade Roll, a reduction of 376 kWh in Fort Myers and 591 kWh in Dubai is achieved. The third strategy encompasses the deployment of blind-type internal shading systems, resulting in reductions of 212 kWh in Fort Myers and 348 kWh in Dubai. The fourth strategy involves integrating renewable energy via photovoltaic panels, injecting 323.5 kWh in Fort Myers and 2237 kWh in Dubai into the power grid for lighting purposes. Furthermore, 3200.5 kWh and 4722 kWh of energy are respectively injected into the grid for heating in Fort Myers and Dubai. Cooling, however, necessitates additional energy from the grid, amounting to 2243.94 kWh in Fort Myers and 9211.64 kWh in Dubai. In the pursuit of zero-carbon goals, the implementation of suitable low-carbon recycled materials, in place of primary building materials, reduces carbon dioxide emissions from 79 tons to 7.315 tons in Fort Myers and 7.038 tons in Dubai. By employing appropriate materials, the zero-carbon objective is attained.

Achieving Off-Grid Refrigeration in Remote Areas: A Solar-Powered Vapor Compression Refrigerator Prototype with PCM Integration

The availability of vaccines, medicines, and perishable goods in remote or off-grid areas remains a formidable challenge. Integrating solar photovoltaic (PV) systems with refrigeration technology has emerged as a promising solution to address this critical need. This paper presents an autonomous solar-powered refrigerator prototype for off-grid refrigeration in remote areas utilising renewable energy. The system comprises a 160 W photovoltaic module, a 12/24 V DC compressor refrigerator, a lead-acid battery, and a Maximum Power Point Tracking (MPPT) controller. Its main feature is complete autonomy from the electricity grid, thanks to its standalone configuration. An experimental campaign evaluated the system's behaviour in the laboratory for 24 hours at different set-point temperatures. A water-based Phase Change Material (PCM) was implemented to improve its autonomy in severe outdoor conditions. A further experimental campaign emulated the functioning of the prototype while managing the temperature of a sample solution whose melting temperature was equal to – 21°C to ensure its liquid state during the tests. The target range for preserving the sample was defined at ± 1°C. Several real conditions have been considered, such as higher cooling loads realised through 21 litres of additional thermal mass in the refrigerator and pick and place conditions for simulating the opening and closing of the door. The results demonstrate that the solar refrigerator prototype achieves complete autonomy from the electricity grid, paving the way for solutions for preserving perishable goods such as medicines and food in unelectrified areas.

Modelling and experimental investigation of cooling of field-operating PV panels using thermoelectric devices for enhanced power generation by industrial solar plants

The performance of commercial solar power plants degrades due to an increase in module temperatures for which standard PV-T air or water-cooling techniques are mostly used. In this study, a thermoelectric cooling system is studied for improving photovoltaic cell power efficiency and hence solar power generation. The cooling optimization requires solar cell temperature prediction of field operating PV modules, for which analysis of six models, is presented. The experimentation results show that TEC cooling maintains PV cell at 25 °C whereas PV cell without TEC operates at 55–63 °C, a higher temperature range, showing the effectiveness of the thermoelectric cooling system in precisely controlling PV cell temperature to operate at or near STC conditions in the field creating a temperature difference of 30–38 °C. The NOCT and Faiman model results are found close to the experimental values in comparison to other models. The potential for cooling and a corresponding increase in solar plant energy production is assessed using PV Syst modeling and simulation for three practical PV installation scenarios for 31 different climatic zone locations worldwide showing 6–27 % power loss due to elevated temperatures, which is not studied in previous studies adding novelty to the analysis. The results show that PV-TECS is an effective system to control the temperature of field operating PV modules, which can be used in future photovoltaic power plants. Field results and analysis of PV temperature models is crucial for the optimization and future development of PV-thermoelectric systems deployed under actual outdoor conditions as well as the expected cooling gains in different climatic locations. These aspects are collectively studied in the current work adding to the novelty of the study.

Maiden application of mountaineering team-based optimization algorithm optimized 1PD-PI controller for load frequency control in islanded microgrid with renewable energy sources

Load Frequency Control (LFC) is essential for maintaining the stability of Islanded Microgrids (IMGs) that rely extensively on Renewable Energy Sources (RES). This paper introduces a groundbreaking 1PD-PI (one + Proportional + Derivative-Proportional + Integral) controller, marking its inaugural use in improving LFC performance within IMGs. The creation of this advanced controller stems from the amalgamation of 1PD and PI control strategies. Furthermore, the paper presents the Mountaineering Team Based Optimization (MTBO) algorithm, a novel meta-heuristic technique introduced for the first time to effectively tackle LFC challenges. This algorithm, inspired by principles of intellectual and environmental evolution and coordinated human behavior, is utilized to optimize the controller gains. The effectiveness of the proposed methodology is rigorously evaluated within a simulated IMG environment using MATLAB/SIMULINK. This simulated IMG incorporates diverse power generation sources, including Diesel Engine Generators (DEGs), Microturbines (MTs), Fuel Cells (FCs), Energy Storage Systems (ESSs), and RES units like Wind Turbine Generators (WTGs) and Photovoltaics (PVs). This paper employs the Integral Time Multiplied by the Squared Error (ITSE) and Integral of Time Multiplied By Absolute Error (ITAE) indicators as the primary performance metrics, conventionally used to mitigate frequency deviations. To achieve optimal controller parameter tuning, a weighted composite objective function is formulated. This function incorporates multiple components: modified objective functions related to both ITSE and ITAE, along with a term addressing overshoot and settling time. Each component is assigned an appropriate weighting factor to prioritize specific performance aspects. By employing distinct objective functions for different aspects of control performance, the derivation of optimized controller gains is facilitated. The efficacy and contribution of the proposed methodology are rigorously demonstrated within the context of RES-based IMGs, featuring a comparative analysis with well-known optimization algorithms, including Particle Swarm Optimization (PSO) and the Whale Optimization Algorithm (WOA). These algorithms are used to optimize the 1PD-PI controller, resulting in three control schemes: 1PD-PI/MTBO, 1PD-PI/WOA, and 1PD-PI/PSO. The effectiveness of these control schemes is evaluated under various loading conditions, incorporating parametric uncertainties and nonlinear factors of physical constraints. Three case studies, presented in eight scenarios (I-VIII), are utilized to comprehensively assess the efficiency, robustness, and sensitivity of the proposed approach. This analysis extends beyond the time domain, considering the stability evaluation of the proposed control scheme. Simulation results unequivocally establish the superior performance of the MTBO algorithm-optimized 1PD-PI controller compared to its counterparts. This superiority is evident in terms of minimized settling time, reduced peak undershoot and overshoot, and enhanced error-integrating performance characteristics within the system responses. Improvements are observed in both the high range and within the 80–90% range for criteria such as overshoot, undershoot, and the numerical values of the objective functions. This paper underscores the practicality and effectiveness of the 1PD-PI/MTBO control scheme, offering valuable insights into the management of frequency disturbances in RES-based IMGs.

An open-loop and closed loop based passive thermal management techniques applicable to photovoltaic systems

Photovoltaic (PV) technology adoption in recent years has experienced significant growth due to its inherent advantages over alternative technologies. Nevertheless, there is a concern regarding performance deterioration due to high operating temperatures. Various thermal management methods have been studied to address this issue, each having its own advantages and disadvantages. Hence, a comprehensive review aimed at developing effective passive cooling techniques was undertaken and two techniques were finalized for outdoor testing viz. natural circulation loop based cooling (PV-NCL) and evaporative cooling (PV-EVP). Though the former version could drop module temperature by 7.4 °C–13.9 °C (Power output increment in the range of 3.5 %–6.7 %), this improvement was not sustained throughout the day due to factors such as flow resistance within the loop and a lack of convective cooling in the vicinity of the cooler. Subsequent experiments confirmed that loop resistance played a dominant role in this phenomenon. Additionally, concerns about water circulation in PV-NCL were resolved through a comparison with water duct-integrated PV. On the other hand, the innovative gravity-assisted water flow for evaporation method (PV-EVP) yielded more promising results, with a power output enhancement ranging from 3.7 % to 11.5 %. However, considering the in-field operational issues, PV-NCL with a modified design will likely be the best technique.