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The purpose of this paper is to present a novel approach to the determination of the maximum power point (MPP) in the photovoltaic system using genetic algorithm (GA). The optimization is realised on two types of photovoltaic (PV) modules: monocrystalline and polycrystalline solar modules, with the same rated peak power (400 Wp) but different electrical output data.

The proposed algorithm is a nature-based algorithm that uses genetic operators such as reproduction, crossover and mutation to realise the search through the investigated area of solutions. To determine the MPP of the PV modules, a two-diode model of a PV cell is used. Based on the input electrical data for the analysed PV module, as well as the mathematical model of the PV, the algorithm can estimate the current and voltage at the MPP for given solar irradiation and cell temperature. The analysis is made for several different irradiations, but in work, the results are presented for irradiations of: 100, 500 and 1,000 W/m² and cell temperatures of 0, 25 and 40 °C.

From the presented results and performed analysis, it can be concluded that GA gives adequate results for both modules and for all working conditions. From the obtained results, it can be concluded that the optimization algorithm performs better when applied to the monocrystalline module works better especially in conditions with larger cell temperature, in comparison with the performance of the optimization algorithm applied to the polycrystalline module. On the other hand, the optimization algorithm applied to the polycrystalline module works better for the other working scenarios with smaller cell temperatures.

From the performed analysis, it can be concluded that the use GA as an optimization tool for the determination of the MPP can be successfully implemented. In addition, to improve the overall performance of the PV system, it is also necessary to forecast the weather conditions of the location where the PV system would be installed to forecast the cell temperature and the solar irradiation. This is necessary to choose the right PV module and inverter for the given location.

An optimization technique using GA as an optimization tool has been developed and successfully applied in the determination of the MPP for a PV system. The results are compared with the analytically determined values as well as with the values given by the producer, and they show good agreement.

Decentralized solar systems are increasingly being used as alternative source of off-grid electrification in Bangladesh. They offer solutions to provide (clean) electricity to the low-income households that are not currently served by the national grid. The standards of solar systems need to be improved to maximize the benefits they offer for off-grid electrification.

A quantitative research approach was used to explore the power output performance of six solar systems samples. In order to realize a proper load management, daily power production was measured to determine the generation capacity of 50, 60 and 100 Wp monocrystalline and polycrystalline modules when average solar irradiation was 916 W/m². In the testing system, the irradiation was measured by panel analyzer HT instrument I-V 400. The load arrangement comprised of different kinds of appliances (fan, light, TV). The daily consumption of energy by these loads was calculated using daily operational hours to determine system power performance.

The authors found that monocrystalline system performs better than polycrystalline by 0.39 kilowatt-hour (kWh) with capacity of 100 watt-peak (Wp) modules. The carbon dioxide (CO₂) emissions reduction potential of our sample solar systems were also estimated by assuming a scenario. This was derived by using the electricity emission factor for natural gas (CH₄), since CH₄ is the main source of energy for power generation in Bangladesh. Savings in CO₂ of 0.52 kgCO₂/kWh is possible with the adoption of a 100 Wp monocrystalline module.

Government actions that promote the use of monocrystalline module will enhance the benefits of the use of solar systems in providing quality and sustainable electricity. This will contribute to government's efforts towards achieving some of the United Nations (UN) sustainable development goals (SDG) and resilience of the most vulnerable population to the effects and impacts of climate change.

Almost all solar modules found in off-grid areas are polycrystalline whose energy generation capacity is much lower compared to monocrystalline types. But use of low efficient polycrystalline solar module hindered the development of country's solar sector and option to save carbon emission. The use of highly efficient monocrystalline solar module will save also the country's land as the country has land scarcity challenges for establishing large-scale solar power plant. The authors also recommend actions that can be implemented at the national level to improve the attractiveness of monocrystalline solar systems in Bangladesh.

Tunisia has high solar radiation levels, which makes it suitable for the installation of photovoltaic (PV) systems. The design of these kinds of systems is an important step because there are many crucial factors to assess the PV module efficiency such as temperature, module types and solar radiation.This paper aims to give an analysis of the most influencing factor for selecting location. In fact, after estimating the PV panel inclination, the solar radiation and the temperature in “Zarzis” (southeastern of Tunisia), a comparative analysis among the different PV panel types was given. Additionally, to find which technologies are suitable for the climate conditions of this area, it is important to compare the effect of temperature and solar radiation on their performances.

The purpose of this paper is to minimize and prevent current overloads (including the elimination of abnormal and fire hazardous situations) in photovoltaic solar arrays by using low-cost functional electronic elements, in particular, the new PolySwitch PPTC fuses.

The modeling method has been used to investigate the circuit solution of the use of PolySwitch type fuses to prevent and minimize current overloads in photovoltaic solar arrays.

It is shown that the limitation of the short-circuit current with parallel connection of photovoltaic components (photovoltaic cells or their modules) can be implemented when the following conditions are met: the resistance of the fuse in the conducting state is much lesser than the parallel connection of the series resistances of the photovoltaic components; and the tripping current of the fuse must be greater than the maximum current of the separate photovoltaic components and lesser than the current of a parallel connection of several photovoltaic components.

The influence of the magnitude of the resistance in the conducting state and the response current of the fuses to the current–voltage and volt–watt characteristics of parallel connections of the photovoltaic components (photovoltaic cells or their modules) is analyzed. The modeling results are confirmed by experimental data on the transformation research of light current–voltage and volt–watt characteristics of parallel connections of industrial photovoltaic modules using resettable fuses of the PolySwitch type.

Parameter identification of photovoltaic (PV) modules plays a vital role in modeling PV systems. This study aims to propose a novel hybrid approach to identify the seven parameters of the two-diode model of PV modules with high accuracy.

The proposed hybrid approach combines an improved particle swarm optimization (IPSO) algorithm with an analytical approach. Three parameters are optimized using IPSO, whereas the other four are analytically determined. To improve the performance of IPSO, three improvements are adopted, that is, evaluating the particles with two evaluation functions, adaptive evolutionary learning and adaptive mutation.

The performance of proposed approach is first verified by comparing with several well-established algorithms for two case studies. Then, the proposed method is applied to extract the seven parameters of CSUN340-72M under different operating conditions. The comprehensively experimental results and comparison with other methods verify the effectiveness and precision of the proposed method. Furthermore, the performance of IPSO is evaluated against that of several popular intelligent algorithms. The results indicate that IPSO obtains the best performance in terms of the accuracy and robustness.

An improved hybrid approach for parameter identification of the two-diode model of PV modules is proposed. The proposed approach considers the recombination saturation current of the p–n junction in the depletion region and makes no assumptions or ignores certain parameters, which results in higher precision. The proposed method can be applied to the modeling and simulation for research and development of PV systems.

The maintenance of green building technologies such as building-integrated photovoltaic (BIPV) is a challenge due to the non-existence of maintainability considerations during the design stage. This led to building defects which accounts to high expenditures throughout the building's lifecycle. The use of BIPV in buildings is an emergent trend, and further research is requisite for their maintainability. This paper assesses the performance and maintainability of BIPV façade applications based on the green maintainability design considerations.

Qualitative method is undertaken in this study, which includes field surveys, instrumental case studies and stakeholder interviews to probe the issues linked with the BIPV's maintainability.

Findings have shown some technical defects discovered in BIPV applications in tropical areas, as well as issues on cost, aesthetics and implementation are the main causes for the low adoption of BIPV in Singapore.

Understanding the research outcomes will embolden designers and allied professionals to team up in ensuring the long-term maintainability and sustainability of green building technologies. This research gives recent and important information in the design, installation and maintainability of BIPV, as well as good practices that would add value to facilities management and to the design of green building technologies.

The purpose of this study is to monitor the surface cooling of the photovoltaic (PV) panel and the effect of the dust accumulated on the panel surface on the electrical efficiency remotely and instantaneously.

An autonomous system has been designed that can measure and record the PV surface temperature, the amount of dust on the surface, current, voltage and power values at certain intervals. It can also perform surface cooling and cleaning with water cycle when the temperature and dust amount reach certain threshold values and transmit these values to the user via global system for mobile communications module, Bluetooth module and graphically with a touchscreen liquid crystal display panel. Thus, it is aimed to benefit from PV at the maximum level, and it was installed in Kahramanmaras Sütçü Imam University Faculty of Engineering and Architecture.

An increase in power was observed for PV surface cooling and surface dust removal by 3.78% and 45.99%, respectively.

This system is of vital importance in terms of time and energy-saving, especially for solar plants far from the city center, which are difficult to access because of climatic conditions. In other hand for future studies, it is foreseen that more efficiency gains can be achieved by using artificial intelligence and image processing techniques.

The purpose of this paper is to investigate the dark properties as a function of reverse current induced defects. Dark characteristics of solar modules are very essential in the understanding the functioning of these devices.

Reverse currents were applied on the photovoltaic (PV) modules to create defects. At several time intervals, dark characteristics along with surface temperature were measured.

Current-voltage (I-V) and capacitance-voltage (C-V) characteristics furnished valuable data and threshold values for reverse currents. Maximum module surface temperatures were directly related to each of the induced reverse currents and to the amount of leakage current. Microstructural damages, in the form of hot spots and overheating, are linked to reverse current effects. Experimental evidence showed that different levels of reverse currents are a major degrading factor of the performance of solar cells and modules.

These results give a reliable method to predict most of the essential characteristics of a silicon solar cell or a module. Similar test could help predict the amount of degradation or even the failure of PV modules.

The purpose of this paper is to discuss the effect of electric reverse stress currents on the performance of photovoltaic solar modules.

The effect of a reverse introduced current as a function of time is studied on the I‐V and C‐V characteristics and parameters which were extracted and analyzed using numerical analysis based on a reliable double exponential model.

The effect of an introduced reverse current for different periods simulated the effect of accumulated extreme reverse currents which may arise in solar cells and modules due to different reasons, causing dramatic changes in the shunt resistance as well as other characteristics, mainly when the time of the current application exceeded a certain limit.

The paper contributes to the research on the damaging effects of reverse currents on the normal operation of the solar cells and modules.

Solar photovoltaic (PV) is commonly used as a renewable energy source to provide electrical power to customers. This research establishes a method for testing the performance reliability of large grid-connected PV power systems. Solar PV can turn unrestricted amounts of sunlight into energy without releasing carbon dioxide or other contaminants into the atmosphere. Because of these advantages, large-scale solar PV generation has been increasingly incorporated into power grids to meet energy demand. The capability of the installation and the position of the PV are the most important considerations for a utility company when installing solar PV generation in their system. Because of the unpredictability of sunlight, the amount of solar penetration in a device is generally restricted by reliability constraints. PV power systems are made up of five PV modules, with three of them needing to be operational at the same time. In other words, three out of five. Then there is a charge controller and a battery bank with three batteries, two of which must be consecutively be in operation. i.e. two out of three. Inverter and two distributors, all of which were involved at the same time. i.e. two out of two. In order to evaluate real-world grid-connected PV networks, state enumeration is used. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems. Every module's test results on a realistic 10-kW PV system. To see how the model works in practice, many scenarios are considered. Tables and graphs are used to show the findings.

The system of first-order differential equations is formulated and solved using Laplace transforms using regenerative point techniques. Several scenarios were examined to determine the impact of the model under consideration. The calculations were done with Maple 13 software.

The authors get availability, reliability, mean time to failure (MTTF), MTTF sensitivity and gain feature in this research. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems.

This is the authors' original copy of the paper. Because of the importance of the study, the references are well-cited. Nothing from any previously published articles or textbooks has been withdrawn.