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The solar radiation is a critical metric for design and optimal operation of the solar energy system. Most of the locations available solar radiation records are not available due to high cost for buying and maintaining the measuring instruments. Aim of this paper is building an efficient neural network model that can reliably estimate solar radiation. In this work, different ANN models with three popular algorithms admired from the literature are investigated. The models were trained using meteorological data collected over a year from six different places from the hot area locations of Tamil Nadu, India. Based on minimal Mean Absolute Deviation (MAD), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), the optimum ANN algorithm and model are determined (R). Furthermore, the research illustrates that the ANN model’s prediction performance is dependent on the entire set of data utilised to train the network. Also, this article aims at finding out the accurate number of hidden layer neurons for the developed model. The proposed ANN model offers improved accuracy and applicability for estimating hourly average global radiation for the purpose of designing or evaluating photovoltaic (PV) installations in areas without meteorological data collection facilities.

This is an Accepted Manuscript of an article published by Taylor & Francis Group in International journal of electronics on Published online: 30 Dec 2021, available online at: https://www.tandfonline.com/doi/abs/10.1080/00207217.2021.2007544 Increasing the voltage gain by means of Z-source network will provide some features such as low voltage stress of semiconductor devices, low duty cycle of the switch and low reverse recovery problem of output diode that leads to improve the converter performance and efficiency. The proposed converter in this paper employs a Z-source network with coupled inductors integrated with flyback converter to make it appropriate for high step-up applications. One magnetic element is used in this converter, which is its main advantage over previously introduced Z-source converters. Steady state analysis and operation principles of the proposed converter in continuous conduction mode that leads to low current ripple, and low conductive losses for semiconductor devices due to decreasing the RMS currents are presented. In order to verify the theoretical analysis, experimental results of a prototype are provided. This converter’s high voltage conversion ratio will result in 300 V output from 20 V input voltage source for 100 W output power

Utilization of solar energy in Indonesia has begun to bloom. This is due to the fact that Indonesia is located at the equator where the sun is exposed all year round and is a very environmentally friendly energy. Based on this, solar energy is used as an option to meet electricity needs by using a photovoltaic (PV) system. The use of a photovoltaic system as a power provider to operate a pool water pump at a villa in Bali is an example of the application of a photovoltaic system. In this study, A Seri and Parallel photovoltaic arrays were used with a panel system that was integrated with PLN electricity. The angle of inclination and direction of placement chosen in this study is 15° with facing north, which refers to research that, has been done previously. PV designs and a series of control panels that can be accessed via the internet will be described as well. The aim in this research is investigate how photovoltaic design used as a solar power plant which applied to the module can be runing the pool water pump in the villa or tourist accommodation.

Luminescent solar concentrators (LSCs) have been widely studied for their potential application as building-integrated photovoltaics (BIPV). While numerous efforts have been made to improve the performance, the photothermal (PT) properties of LSCs are rarely investigated. In this report, we studied the PT properties of an LSC with a power conversion efficiency (PCE) of 3.27% and a concentration ratio of 1.42. The results showed that the total PT power of the LSC was 13.2 W, and the heat was concentrated on the edge of the luminescent waveguide with a high heat power density of over 200 W m−2.

To decrease indoor relative humidity and have relaxing environments, small dehumidifiers are widely used in tropical climatic. Due to the benefits of eco-friendly, small size and silence operation, the thermoelectric dehumidifier has gained interest but has limited practical application due to poor efficiency. Therefore, this study investigates the dehumidification characteristics of the thermoelectric module powered by a photovoltaic system for the production of fresh water under real climatic conditions. The performance of a novel prototype named as the Photo-Thermoelectric Dehumidifier (PVTE-D) was investigated both numerically and experimentally in different combinations of airflow rate and input power. The results obtained from the experiment suggested that the water condensate collection was increased by increasing the input power from a PV panel to the TE-D. In the month of May, the maximum water condensate collection of 1,852.3 mL/hr was attained at the input supply of 6 A and 5 V to the PVTE-D system. In the majority of cases, when the airflow rate is below 0.013 kg/s, maximum collections of water condensate have been achieved. This study provides a detailed understanding of the optimally suitable structural parameters of the PVTE-D under different operating conditions and reveals a novel configuration for higher water condensation capacity. HIGHLIGHTS Photovoltaic powered thermoelectric dehumidification system.; Simulation and experimental study of PVTED system.; Optimum performance parameter evaluation by regulating input power and air flow rate.

The doping of two-dimensional materials provides them with tunable physical properties and broadens their application. In this study, the doping of tungsten disulfide with metallic Sn atoms via a co-sputtering technique was demonstrated. In particular, WS2 was deposited by radio frequency (RF) magnetron sputtering, while Sn atoms deposited by DC sputtering become substitutional dopants. It was revealed that the metallic tungsten atom, and in some cases sulfur vacancies, in the WS2 atomic layer created by RF magnetron sputtering were partially filled/substituted by metallic Sn atoms. The Sn-doped WS2 layers exhibited n-type doping behavior with remarkable opto-electronic properties (bandgap 2.09 eV, mobility 7.84 cm2/V·s and resistivity 2.81 × 103 Ω-cm for 1 min Sn doping) suitable for photovoltaic applications. Overall, this technique facilitates better control of the dopant distribution than the traditional approach.

The depleting fossil fuel and growing environmental concern have opened the doors for clean and green energy development using renewable energy sources. Also, the growing oil demand and carbon emissions have created a huge scope for Electric Vehicle (EV) usage across the world which has resulted in blooming EV market. Photovoltaic (PV) powered EV charging can substantially reduce the carbon foot prints when compared to the conventional utility grid based EV charging. The amalgamation of solar power and EV charging is one of the best methods in sustainable development for EV market. Recent statistics suggest that usage of EVs in different cities in India has proliferated and the development of the charging infrastructure is a big challenge for the densely populated country. Firstly, theoretical demand model and stochastic model for EV traffic and resource utilization pattern is developed. Secondly, the optimal configuration and techno-economic assessment of Solar powered EV Charging Station (EVCS) in microgrid is analyzed for four different Indian cities (Shillong, Bengaluru, Jaipur and Kashmir) with varied solar radiation conditions. Lastly, the environment benefits of solar PV powered EVCS are assessed and analyzed. The results demonstrate that the optimal configuration and investment efficiency in each urban area is greatly affected by the solar irradiation and feed-in-tariff (FIT) price of rooftop solar power. Kashmir with high solar irradiation conditions can invest in the solar EVCS compared to the other cities.

A techno-economic study has been proposed for an off-grid combined renewable energy system (HRES) by photovoltaic (PV) and fuel cell (FC) systems. The proposed HRES has been studied to provide electricity for a remote area in Jiaju Tibetan Village, Danba, Sichuan Province China The main idea is formulated according to the Total Annual Cost (TAC). The study uses a new improved metaheuristic, called Amended Water Strider Algorithm (AWSA) to optimal estimation of the photovoltaic panels’ number, electrolyzer, fuel cells, and hydrogen storage tanks to get the minimum value of the overall net present value (ONPV). For increasing the system efficiency, the loss of power supply probability (LPSP) has been considered. Sensitivity analysis is used on the changing of the proposed HRES according to Levelized cost of energy (LCOE). Also, a comparison of the algorithm with several techniques from the literature is performed to illustrate its effectiveness. The results showed that the proposed method has further proper results than the other algorithms.

Renewable energy complementary hydrogen production can enhance the full consumption of renewable energy and reduce the abandonment of wind and solar power. The integration of renewable energy and hydrogen production equipment through existing multi-terminal DC systems can reduce new power lines construction and save investment in distribution equipment. For integrated renewable energy/hydrogen energy in an existing multi-terminal DC system, this paper investigates its potential of hydrogen production based on renewable energy, while ensuring the normal performance of the existing system being not affected. The typical structure and control strategy of the integrated renewable energy/hydrogen energy in multi-terminal DC system are firstly described. Then the state space model of the system is constructed, and the key parameters affecting the hydrogen production capacity are studied by using the eigenvalues analysis method. Finally, the corresponding system simulation model and test platform are built, and the theoretical analysis results are verified, and the potential of using multi-terminal DC system to enhance hydrogen production is quantitatively analyzed. The proposed scheme can enhance the hydrogen production potential from renewable energy, meanwhile the normal performance of the existing system is not affected.

As decentralized energy supply systems are becoming more and more important for the global energy supply, – apart from a heightened focus on energy rationalization and energy efficiency – increasing the role of variable renewable energy sources, such as solar and wind energy, in energy consumption is gaining more and more significance. Since energy projects tend to be meant for the long term and involve considerable financial investments, it is indispensable to be aware of the country-specific regulatory background when establishing photovoltaic (PV) systems. The last few years have witnessed a trend that new PV power plants are mostly built using traditional crystalline PV technologies, which are prone to irreversible PV module damage due to shading effects. During the operation of PV power plants, anomalies causing loss of income and even fire hazard in extreme cases may occur. Thus, the identification of the problematic parts of the system is of utmost importance. This paper presents the energy relationships of shading by the example of a Hungarian PV system. The goal of this study is to introduce a methodology that can be used internationally to categorize the operational characteristics of the strings of PV power plants on the basis of monitoring data, which allows the assessment of the annual energy loss. The innovative novelty of the model is that its use can provide practical help for the operators of PV systems around the world, since the solution is easy to adapt to real-time supervisory and management platforms and it makes the localization of problematic strings possible, thusly allowing a more focused inspection of PV power plants. The novel practical benefit of the model is that by its use it becomes possible to detect any energy loss resulting from the spacing distance of the strings of PV power plants or faulty operation (the negative shading effects of trees and other objects, faulty inverter operation) by using a simpler calculating mechanism. The early detection of problems is essential for the protection of the PV modules, the subsequent reconstruction of the strings or even solving issues under guarantee. In addition, by assessing the annual energy loss caused by shading, it becomes possible to detect any negative change in the economic indicators of the investment.

Lack of electricity networks in remote areas and also the high cost of connecting these areas to national networks due to the unfavorable geographical situation of the region leads to the use of other energy sources independent of the network in these areas. Today, the use of distributed generation sources is increasing due to the reduction of fossil fuel sources and heat problems. The output power of distributed generation sources, especially renewable energy sources, fluctuates under the influence of atmospheric conditions. The main purpose of the present study is to present a new optimal configuration for a hybrid photovoltaic/diesel generator/battery system to refine the load demand of a rural area in Hoxtolgay, China. The idea is to minimize the CO2 emissions value, the annualized cost, and the loss of load probability of the system. To simplify this system, e -constraint method is performed. The problem has been solved by an adaptive version of Marine Predators Algorithm (AMPA) to improve the optimization results. The total ACS for the optimal system is achieved 8224.15 $. Also, an optimal value of 451.30 kW for diesel generator, 4266$ for battery storage, and 2670.53 $ for PV generator are achieved. The initial capital cost of the system is achieved 47940 $ that is less than the NPC. In this case, the maximum cost of the system with 43.12% belongs to the PV system of total cost of the system. Finally, CO2 emission by the suggested AMPA with 1624 kg/year shows the minimum value with cleanest result among the others. Final results of the proposed technique are compared with PSO method and HOMER-based optimization to indicate its effectiveness. Sensitivity analysis has been also performed to determine the system efficiency.

This work presents the results of a study to optimize the production of electricity, by hybrid system Photovoltaic – Diesel – Batteries, to power the village of Kalakala in the north of Côte d'Ivoire. The study site is an isolated rural community, powered by a diesel generator. It is located in northern Côte d'Ivoire. HOMER software has been used for system simulation and optimization. The result of this study is then compared to those of PV - Batteries and diesel alone systems. From the results of the simulations, it appears that the optimal combination of the hybrid system includes a diesel generator of 50 kW, a photovoltaic field of 46 kW, 10 batteries of 48V and a converter of 100 kW. With a photovoltaic penetration rate of 52.7%, this system, compared to the photovoltaic - batteries system, reduces the photovoltaic field by 56%, the number of batteries by 61.5% and increases battery life by 42.84%. Compared to diesel alone, it reduces fuel consumption and the quantity of CO2 by 60% and improves diesel efficiency by 17%. The cost of generating electricity for the hybrid system is €0.373/kWh compared to €0.466 and €0.608/kWh respectively, for the PV-Batteries and diesel alone systems. The hybrid system with the best technical, economic and environmental performance could be a good alternative for generating electricity in remote communities.

Agriculture traditionally still uses large areas of land with relatively large amounts of water. The application of solar energy is one of the uses of new and renewable energy. This research uses a 50 Wp photovoltaic cell, battery, solar charge controller, DC stepdown, DC pump and hydroponic frame. The stages of the research are the design of the tools, the calculation of the power required by the tools, the manufacture of the tools, the collection of data and the analysis of the data. The data collected is temperature, sunlight intensity, electric power, electrical energy, water discharge, and photovoltaic efficiency. The data were processed and analyzed in an exploratory manner. Based on the results of the research conducted, the lowest average temperature was 25.33 C and the highest was 33.70 C with the highest average light intensity of 920.26 w/m2 at 12.00 WIB. The relationship between temperature and light intensity with a value of R2 of 0.7594. The highest average electrical energy obtained by polycrystalline is 30.44Wh. The water lost from the hydroponic system is 0.03%. The efficiency of photovoltaic cells is 10.09%–15.72%. Keywords: DC pump, hydroponics, light intensity, photovoltaic

Luminescent solar concentrators (LSCs) are considered promising photovoltaic (PV) devices to circumvent practical issues of applying conventional solar panels to the built environment. However, LSCs suffer from low power conversion efficiencies (PCEs) (typically &lt, 2% for devices of over 1 m2), despite numerous efforts having been made to develop novel luminescent materials and optical techniques. In this report, we proposed to utilize photothermal (PT) energy of the LSCs to further improve the PCE. We conducted a preliminary investigation on the PV and PT properties of an LSC with dimensions of 300 mm × 300 mm × 5 mm. The results showed that the PT power (27.05 W) was much higher than the PV power (2.12 W). Further analysis indicated that the PCE could reach 3.41% for a device of 1 m2.

Software for simulation of photovoltaic (PV) systems is widely used for dimensioning and forecasting electrical production. A factor of losses in PV installations is the partial shading caused by surrounding elements, and these software allow the user to estimate this effect. However, the accuracy of these simulated results for shaded PV systems is not widely studied. The purpose of this article is to investigate the accuracy and quantify the differences between simulated and measured data of partially shaded PV systems, obtained with the widely used tools SAM and PVSyst. Measured data from a PV installation were compared to results from simulations performed using the different shading calculation options available in both tools. The simulated outputs were both underestimated and overestimated in the shading situations. This variation was related to the use of an hourly fraction of shading and, in the case of SAM, due to the limitations of the 3D tools available for representation. Another source of differences between simulated and measured values was the use of uniform shading factors for diffuse and albedo. In addition, the simplification of the 3D model had a significant impact on the predicted energy, mainly on cloudy days. Both software overestimated the electricity production for the entire measurement period, reaching differences between the predicted and the measured energy varying from 9% to 24%. Shaded PV systems must be carefully analyzed, and the simulated results may differ from the measured values, which may even influence the decision on the feasibility of an installation.

This paper presents a feasibility study of utilizing an on-grid photovoltaic (PV) system for electrification of Cedars hotel located in Amman in Jordan as a case study. The PV system has been designed, keeping in view the required electrical load and energy available from the sun in Jordan. The actual energy consumption of the hotel is estimated (444 MWh/year) for the design and simulation of the on-grid PV system using Photovoltaic Geographical Information System software (PVGIS) and photovoltaic software (PVsyst). The results showed that PV system required 912 panels distributed over 12 inverters, with a required area of 1757.3 m2. In addition, the on-grid PV system produced a total yearly energy of 541 MWh, with an average performance ratio of 0.828. The economic study for the proposed PV system showed that the system’s payback period was 4.1 year. Moreover, life cycle savings (LCS) and levelized cost of energy (LCOE) analysis have been carried out. The LCS and LCOE of the system were found to be $51,493 and $0.0199 /kWh, respectively. Therefore, installing a proposed on-grid PV system on the Cedars hotel will save $38,718/year. It is concluded that an on-grid PV system is a technically and economically viable technology for the electrification of residential hotel applications.

Photovoltaic technology is an alternative resource for renewable and sustainable energy and low costs organic photovoltaic devices such as bulk-heterojunction (BHJ) solar cells, which are selective candidates for the effective conversion of solar energy into electricity. Asymmetric phthalocyanines containing electron acceptor and donor groups create high photovoltaic conversion efficiency in dye sensitized solar cells. In this study, a new unsymmetrical zinc phthalocyanine was designed and synthesized including thiophene and amine groups at peripherally positions for BHJ solar cell. The structure of the targeted compound (4) was characterized comprehensively by FT-IR, UV-Vis, 1H-NMR, and MALDI-TOF MS spectroscopies. The potential of this compound in bulk heterojunction (BHJ) photovoltaic devices as donor was also researched as function of blend ratio (blend ratio was varied from 0.5 to 4). For this purpose, a series of BHJ devices with the structure of fluorine doped indium tin oxide (FTO)/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)/ ZnPc:[6,6]- phenyl-C61- butyric acid methyl ester (PCBM) blend/Al with identical thickness of ZnPc:PCBM layer were fabricated and characterized. Photo current measurements in 4 revealed that the observed photo current maximum is consistent with UV-vis spectra of the compound of 4. Preliminary studies showed that the blend ratio has a critical effect on the BHJ device performance parameters. Photovoltaic conversion efficiency of 6.14% was achieved with 4 based BHJ device.

This study aims to evaluate the performance of a photovoltaic module under some extreme climate conditions, and with a case study for Iraq. CFD model is developed for the analysis of the photovoltaic module using the commercial CFD software of COMSOL Multiphysics v5.3a for the transient conditions. The results are verified with the analytical solution to the one-dimensional non-linear energy balance equation using Matlab. The results are also compared with measurements reported in the literature for validation. The results reveal that the free convection currents in inclined and horizontal positions of the module were weaker relative to the vertical position. Also, the increase in the length of inclined photovoltaic module, up to 1.3 m, enhances the heat transfer rate. However, beyond this length, the temperature of the module becomes higher, and the convective heat transfer coefficients are reduced regardless of the inclination. In the horizontal position, the convective heat transfer rate is lower, particularly on the bottom surface of PV system.

Multi-branched molecules have recently demonstrated interesting behaviour as charge-transporting materials within the fields of perovskite solar cells (PSCs). For this reason, extended triarylamine dendrons have been grafted onto a pillar[5]arene core to generate dendrimer-like compounds, which have been used as hole-transporting materials (HTMs) for PSCs. The performances of the solar cells containing these novel compounds have been extensively investigated. Interestingly, a positive dendritic effect has been evidenced as the hole transporting properties are improved when going from the first to the second-generation compound. The stability of the devices based on the best performing pillar[5]arene material has been also evaluated in a high-throughput ageing setup for 500 h at high temperature. When compared to reference devices prepared from spiro-OMeTAD, the behaviour is similar. An analysis of the economic advantages arising from the use of the pillar[5]arene-based material revealed however that our pillar[5]arene-based material is cheaper than the reference.

Over the last few years, a growing interest has surfaced about the possibility of enhancing solar harvester efficiency by coupling photovoltaic (PV) cells with thermoelectric generators (TEGs). To be effective solutions, hybrid thermoelectric-photovoltaic (HTEPV) solar harvesters must not only increase the solar conversion efficiency but should also be economically competitive. The aim of this paper is to estimate the profitability of HTEPV solar harvesters with no reference to specific materials, relating it instead to their physical properties only and thus providing a tool to address research effort toward classes of HTEPV systems able to compete with current PV technologies. An economic convenience index is defined and used to assess the economic sustainability of hybridization. It is found that, although hybridization often leads to enhanced solar power conversion, power costs (USD/W) may not always justify HTEPV deployment at the current stage of technology. An analysis of the cost structure shows that profitability requires largely enhanced thermoelectric stages, concentrated solar cells, or PV materials with favorable temperature efficiency coefficients, such as perovskite solar cells.

The levelized cost of electricity (LCOE) is a techno‐economic parameter used to evaluate the cost of a kilowatt‐hour of energy produced from a selected power plant. The initial investment, annual operation and maintenance costs together with the annual energy production are some of the input data needed to determine the LCOE. The most typical approach to calculate the LCOE does not account for the interaction of the new power plant with the existing energy system, assuming indirectly the power plant as stand‐alone. This can be misleading in scenarios with high variable renewable energy sources (VRES) penetration as costs related to overproduction, reinforcement of the grid and additional efforts of existing fossil fuels power plants to satisfy the electricity demand that is not instantly covered by VRES production are not accounted for. The aim of this work is to define a general methodology of easy application for the estimation of these additional costs, called integration costs, of the photovoltaic (PV) technology with the corresponding parameter called system LCOE. In order to demonstrate the importance of the new definition, the methodology is applied to the future Italian energy system and PV sector foreseen for the year 2030. The Italian PV LCOE in 2030 calculated with the usual methodology ranges from 12.55 to 15.93 €/MWh, while the system LCOE can be as high as 22 €/MWh with a relevant increase by on average 50%. In case of addition of storage to PV systems, the system LCOE after the addition of the integration costs ranges from 45 to 51 €/MWh. However, even when batteries and integration costs are included, PV remains competitive compared to the market price.

Long-distance wireless energy transmission is realized by photoelectric conversion through lasers and photovoltaic cells. However, existing devices have low transmission power and low transmission efficiency. Exploring the main factors that limit the transmission efficiency during transmission is necessary to improve the transmission power and efficiency, and theoretically analyze these factors that affect transmission efficiency, such as beam quality, divergence angle, wavelength and so on. This will provide research directions for subsequent work. A multiwavelength laser wireless energy transmission experimental platform was built by using powersphere, laser with three different wavelengths and other devices. This platform was used for transmission efficiency verification experiment. The total electro-optical-electric conversion efficiency values obtained by the 532, 1030, and 808 nm lasers are 0.01%, 0.08%, and 0.11%, respectively. The corresponding laser-to-electric conversion efficiency values are 1.37%, 1.60%, and 0.73%, respectively. Experimental results show that the electro-optic conversion efficiency of the laser and the photoelectric conversion efficiency of the photovoltaic receiver is the main reasons for the low conversion efficiency of the system. In addition, factors such as the expansion ratio of the beam expander, laser collimation, laser uniformity at the photovoltaic receiver end, and circuit structure, affect the conversion efficiency of the system.

The sizing problem of the hybrid energy system (HES) is a crucial issue especially in rural communities because any wrong results can mislead the decision makers for building the new HES. Due to the intermittent nature of the renewable energy sources (RES) such as wind and PV, there will be a need for a high storage system and/or a standby diesel engine, which increase the investment, required, and increases the cost of energy (CoE). The use of smart grid concepts like the demand response (DR) using dynamic tariff can improve the system performance, enhance the stability, reduces the size and investments of HES components, reduces the customers’ bills, and increases the energy providers’ profits. The DR strategy will allow the customers to share the responsibility of the HES stability with the energy providers to maintain the stability of the HES. The DR strategies should be selected to ensure the balance between the available RES and the load requirements. In this article, a novel DR strategy is introduced to model the required change in the tariff with the battery state of charge and its charging/discharging power. The novel DR strategy is used in the sizing of the HES based on techno-economic objectives using three different soft computing optimization techniques. This article introduces modeling and simulation of the smart grid integrated with hybrid energy systems to supply a standalone load for a rural site in the north of Saudi Arabia. The sizing of the HES is built based on minimizing the CoE and the loss of load probability. The novel DR strategy introduced in this article reduced the size of the HES compared to the fixed load technique by 20.66%. The results obtained from this novel strategy proved its superiority in the sizing and operation stage of the HES.

The increasing number of electric vehicles (EVs) in today’s transport sector is gradually leading to the phasing out of petroleum-based vehicles. However, the rapid deployment of EVs largely depends on the coordinated and fast expansion of EV charging stations (EVCSs). The integration of EVCSs in the modern distribution network characterized by increased penetration of randomly distributed photovoltaic (PV) systems is challenging as they can lead to excessive power losses and voltage deviations beyond acceptable limits. In this paper, a hybrid bacterial foraging optimization algorithm and particle swarm optimization (BFOA-PSO) technique is proposed for the optimal placement of EVCSs into the distribution network with high penetration of randomly distributed rooftop PV systems. The optimization problem is formulated as a multi-objective problem minimizing active and reactive power losses, average voltage deviation index, and maximizing voltage stability index. The IEEE 69 node distribution network is used as the case network. The simulation is done using MATLAB to integrate the EVCSs in five cases of randomly sized and placed PV systems in the distribution network. For all five cases, a minimal increase in power losses is recorded with minor changes in the voltage deviation and stability indices due to the placement of the EVCSs. But for the voltages of nodes 29 to 48, the other node voltages remain unchanged upon placement of the EVCSs. The largest increase in power losses due to the EVCSs being brought into the network with PVs was noticed in case 3 (from 142.27kW, and 62.90kVar to 147.65kW, and 72.48kVar).

It is widely accepted that the integration of natural sources in distribution networks is becoming more attractive as they are sustainable and nonpolluting. This paper firstly proposes a modified Manta Ray Foraging Optimizer (MMRFO) to enhance the characteristic of MRFO technique. The modified MRFO technique is based on inserting the Simulated Annealing technique into the original MRFO to enhance the exploitation phase which is responsible for finding the promising region in the search area. Secondly, the developed technique is utilized for determining the best sizes and locations of multiple wind turbine (WT) and photovoltaic (PV) units in Radial Distribution System (RDS). The total system loss is taken as single-objective function to be minimized, considering the probabilistic nature of PV and WT output generation with variable load demand. Reactive loss sensitivity factor (QLSF) is utilized for obtaining the candidate locations up to fifty percent of total system buses with the aim of reducing the search space. Battery Energy Storage System (BESS) is used with PV to change it into a dispatchable supply. The changes in system performance by optimally integrating PV and WT alone or together are comprehensively studied. The proposed solution approach is applied for solving the standard IEEE 69 bus RDS. The obtained results demonstrate that installing PV and WT simultaneously achieves superior results than installing PV alone and WT alone in RDS. Further, simultaneous integration of WT and PV with BESS gives better results than simultaneous integration of WT and PV without BESS in RDS. The simulation results prove that the total system losses can be reduced by enabling the reactive power capability of PV inverters. The convergence characteristic shows that the modified MRFO gives the best solutions compared with the original MRFO algorithm.

The implementation of real-time price-based demand response program and integration of renewable energy resources (RESs) improves efficiency and ensure stability of electric grid. This paper proposes a novel intelligent optimization based demand-side management (DSM) framework for smart grid integrated with RESs. In the intelligent DSM framework the artificial neural network (ANN) forecasts energy usage behavior of consumers and real-time price-based demand response program (RTPDRP) of electric utility company (EUC). The smart energy management controller of the proposed intelligent DSM framework adapts forecasted energy usage behavior of consumers using forecasted RTPDRP to create operation schedule. The consumers implement the created schedule to minimize energy cost, peak load, carbon emission subjected to improving user comfort and avoiding rebound peaks. Simulations are conducted using our proposed hybrid genetic ant colony (HGAC) optimization algorithm to create schedule for three cases: EUC without RESs, EUC with RESs, and EUC with both RESs and storage technologies. To endorse the applicability and productivity of the proposed DSM framework based on HGAC optimization algorithm with five existing algorithms based frameworks. Simulation results show that the proposed DSM framework is superior compared with the existing frameworks in terms of energy cost minimization, peak load mitigation, carbon emission alleviation, and user discomfort minimization. The proposed HGAC optimization algorithm reduced electricity cost, carbon emission, and peak load by 12.16%, 4.00%, and 19.44% in case I; by 26.8%, 20.71%, and 33.3% in case II; and by 24.4%, 16.44%, and 37.08% in case III, respectively, compared to without scheduling.

Several wired and wireless advanced communication technologies have been used for coordinated voltage regulation schemes in distribution systems. These technologies have been employed to both receive voltage measurements from field sensors and transmit control settings to voltage regulating devices (VRDs). Communication networks for voltage regulation can be susceptible to data falsification attacks, which can lead to voltage instability. In this context, an attacker can alter multiple field measurements in a coordinated manner to disturb voltage control algorithms. This paper proposes a machine learning-based two-stage approach to detect, locate, and distinguish coordinated data falsification attacks on control systems of coordinated voltage regulation schemes in distribution systems with distributed generators. In the first stage (regression), historical voltage measurements along with current meteorological data (solar irradiance and ambient temperature) are provided to random forest regressor to forecast voltage magnitudes of a given current state. In the second stage, a logistic regression compares the forecasted voltage with the measured voltage (used to set VRDs) to detect, locate, and distinguish coordinated data falsification attacks in real-time. The proposed approach is validated through several case studies on a 240-node real distribution system (based in the USA) and the standard IEEE 123-node benchmark distribution system. The results show that the proposed approach can detect low margin attacks (as low as 1% of actual measurements) with up to 99% accuracy. All of the developed source codes of the proposed solution are publicly available at Github. https://github.com/nbhusal/Data-Attack-on-Voltage-Regulation.

The cooling of the surface of the solar photovoltaic (PV) system is a major operative factor in achieving greater efficiency. Correct cooling can improve electrical efficiency and reduce cell degradation rates over time. This results in increasing the life of the solar PV modules. In industrial and domestic utilization, the cooling system is used for the removal of excess heat. This paper presents a new method for cooling systems for solar PV which results in the improvement in the collection of the solar insolation. The additional feature of the method has been the tracking of sunlight for efficient power generation. Further, the extra heat can be utilized for other purposes including heating and power generation through thermal means. The concept of the proposed system has been explained in detail with the pictorial representation. Also, for the validation of the improved performance of the proposed system, a detailed comparison with the conventional methods have been provided for five different cities of Saudi Arabia and an improvement of twice collection of insolation has been estimated compare to the conventional systems. The proposed system shows improved performance for all operating conditions.

Renewable Energy Systems have been in the spotlight of the academic and industrial research for more than two decades, thanks to the development of several fields related to the Electrical Engineering. More recently, with the increasing complexity of the individual renewable energy systems and the interconnection to the grid, the scientific panorama has been witnessing to a convergence of different topics, which span across several IEEE-IES thematic areas: power electronics, electrical machines, smart grids, energy storage, transportation electrification and aerospace. After a brief overview of the renewable energy technologies, this work deals with how the convergence of multiple technologies developed to provide marginal support to the grid has evolved into the foundation of the future utility grid and expanded to transportation sector. It will be shown how the design of a renewable energy system cannot prescind anymore from the electrical grid and from the ancillary services that are requested. Example of convergence are given for a smart transformer application and for a transportation application.

The renewable energy becomes the second-largest source of global electricity worldwide. However, the intermittent nature of RESs (RES)causes great challenges and severed problems regarding system security and reliability. Combining two or more RES in hybrid renewable topologies can overcome these problems and improve the power quality, reliability and increasing the overall system efficiency especially when the combined sources have a complementary nature for each other. For example, Solar Photovoltaic and Wind energy have a complementary nature since they can complement each other in partial failure time and in turn, increases the reliability of the overall system. Optimization techniques are essentially required to optimally coordinate between the combined energy sources, reduce the total system cost, and maximize the extracted power and consequently increasing the total efficiency. Therefore, this paper has a twofold aim which is conducting comprehensive review of the optimization techniques, Software and tools, topologies of hybrid renewable energy systems (HRES)and then applying data mining and statistical calculations to predict the most suitable optimization techniques for a hybrid system composed of Solar PV, Wind Turbine, and battery bank.

The use of photovoltaic power plants is gradually increasing in order to reduce energy costs and greenhouse gas emissions at airports. Airports are suitable settlements for the installation of photovoltaic power plants as they have vast and free of shade areas that are not used in aviation activities. In this study, a 1 MWp photovoltaic power plant is proposed for Gaziantep Airport, Turkey. Performance, economic and environmental benefits of the proposed system were analyzed using the PVsyst simulation tool developed by the University of Geneva in Switzerland. The study demonstrates that Gaziantep Airport is suitable to installation of a grid-connected photovoltaic system and has a high solar energy resource. The proposed photovoltaic power plant at Gaziantep Airport is predicted to operate with an annual electricity generation of 1702.09 MWh, 78.6 % annual average performance ratio (PR), 19.43 % average capacity factor (CF) and 4.67 [h/d] annual average daily final yield.

In this study an intelligent energy supply system is developed. Energy is obtained by wind or solar radiation and stored to cover the electricity and heat demand of a detached house in Germany. For this a heat pump and a storage tank is used. The simulation shows strategies to integrate renewable energies in different regions of Germany while diminishing the need to turn off a wind turbine or feed energy to the grid. For this, the energy consumption in a single house is modelled. Different wind turbines and PV systems are introduced as an energy source. The profitability of these systems is calculated and compared to conventional systems with gas or oil. The analysis shows that at the moment small wind turbines are a feasible option for cover the energy demand under the given conditions. On the other hand, currently PV plants are not suitable for the heat demand coverage as the specific costs outgo the ones for conventional systems. Further research is necessary to look at different case scenarios, taking into account future climate developments.

The concept of zero-energy buildings was developed due to the high cost of electricity and the availability of renewable energy. This study presents detailed design steps for a zero building using a grid-connected photovoltaic (PV) system with a battery to supply the load demand for a building in Egypt (31.0409°N, 31.3785°E). In the system design, the sizes of the system components are determined, including the sizes of the PV cells, batteries, chargers, and controllers, such that they fulfill the load requirements. Maximum power tracking is designed to achieve maximum utilization of solar energy. In addition, a cooling model for the PV system is introduced to increase its efficiency. The PV performance with and without the thermal absorber is theoretically investigated and compared using a three-dimensional conjugate heat transfer model. A coupled thermal-electrical iterative model is also used to estimate the system’s hourly performance. Findings show that increasing the cooling flow rate for the proposed PV system from 0 L/min to 1 L/min significantly decreases the temperature of the PV module from 60 °C to 41 °C at a solar radiation of 650 W/m2. The theoretical results show that using the PV thermal technology at a coolant flow rate of 2 L/min /module generates the highest electrical power along with enough thermal energy for residential building heating. The outlet warm water from the cooling process has been used household uses to achieve a zero-building theory. This thermal energy can also be used in floor heating radiant systems with high energy efficiency and good thermal comfort. Furthermore, the proposed system can sell 33.5 and 61.9 kWh energy to the grid per day in summer and winter, respectively.

The authors have developed a simple, cheap and reproducible technology for obtaining thin-film heterostructures based on CdTe with a given surface morphology during vacuum deposition, which contributes to their low cost [1, 2]. The critical dimensions (thicknesses) of individual layers of the heterostructure were substantiated, a simulation was performed and a wide range of optical properties was investigated [3]. It is shown that for the deposited CdS / CdTe heterostructure on glass it is possible to obtain an efficiency of 15.8%. Given that thin films are relatively new systems, their study can offer much wider opportunities for technological improvement of photovoltaic energy converters. According to the analysis of modern literature data, the efficiency can be increased by performing deposition on ITO films and introducing nanoparticles of controlled sizes.

Among the next-generation photovoltaics (PVs), hybrid organic–inorganic perovskite solar cells (PeSCs) have drawn tremendous attention from both academic and industrial communities, because of their compelling combination of high performance, high cost-effectiveness, and broader feasibility. Despite the rapid growth and importance of scientific progress in the PeSC field, there have been no systematic and bibliometric analyses of the PeSC research outputs. In this study, we systemically investigate the scientific publications of the PeSCs with bibliometric routes to map research trends and collaboration status. A total of 6,581 documents published during 2009–2018 are analyzed. For effective investigation, the commercialization factors are categorized by considering levelized cost of electricity and environmental impact; Cost, Efficiency, Stability, Scaling-up, and Public Acceptability. Furthermore, the combined bibliometric methods are employed as follows: statistical analyses of publication outputs, topic modeling based on publication abstracts with time-series and commercialization factors, and social network analysis of co-authorships at institute level. From the analyses of research trends, although the researches on Efficiency takes a large part in all periods, the researches on Scaling-up, Stability, and Public Acceptability have become more active over time. In the analyses of co-authorship network, the level of collaboration in the PeSC research is already globalized, which is led by European, Chinese, and Korean institutes. The comprehensive results not only track the changes in the PeSC field, but also provide useful information on the future direction for the market entry of the PeSCs and the next-generation PVs.

Summarization: The significance of the temperature effect on the performance of photovoltaics (PVs) has implied the necessity to develop PV cooling methods in recent years. In this research, the inclusion of phase change materials (PCMs) through an alternative type of enclosure in tubular shape was proposed and investigated as an option of mitigating the PV operating temperature to enhance their efficiency and lifetime. Two PVs incorporating different PCMs (PV + PCM systems) and a conventional PV module (reference case) were experimentally tested to assess their energy performance under the Mediterranean conditions in Chania, Crete. As PCMs employed were selected Paraffins RT 27 and RT 31. The results indicated that a peak temperature decrement of 6.4 °C and 7.5 °C could be observed by using 260 g of PCM27 and PCM31, respectively. Hence, PV + PCM27 and PV + PCM31 systems exhibited increased energy generation by 4.19% and 4.24%, respectively, while the increment in the PV conversion efficiency by PCM integration ranged from 2.86 to 4.19%. The proposed configuration of PCM enclosures took advantage of the synergistic effect of wind, as demonstrated by the recorded daily temperature profiles of the PV + PCM27 and PV + PCM31 systems, even after the time of complete PCMs' melting. Presented on: Solar Energy

This article aims to propose and study a new system design for renewable energy called photovoltaic/ solar pond. This new system involves cooling the arrays of the photovoltaic/thermal collectors, which are installed beside the salinity gradient solar pond with a heat exchanger that is installed behind each solar cell. Thermal energy gained by the photovoltaic/thermal collectors was stored in the heat storage zone using a heat exchanger system. An experimental assessment was performed to examine the thermal performance of the mini PV/solar pond. The experiments were carried out for five months, starting from September 2019 and ending in January 2020, in Kirkuk, Iraq. During this period, temperature, salinity, and power generation were recorded in real-time. The experimental results confirmed that the maximum total efficiency value of the system was 37.67% which was recorded in September. Besides, the highest value of the daily thermal efficiency was 30% for September, while the ultimate value of the daily electrical efficiency was 9.357% as recorded in December. The current result agrees well with other experimental studies in the same field.

In this paper, a zeta-zeta coupled non-isolated multiport converter is proposed and implemented. The new dc-dc multiport converter discussed here facilitates the access of two renewable energy sources in the input side and a single output. Zeta converter topology facilitates high voltage gain with a reduced output voltage ripple. Multiport converters have become very prominent in recent past due to the prevalent establishments of distributed energy resources. Therefore in research arena there is no literature evidence for Zeta –Zeta converters used in multiport converters. This research work emphasize on suggesting a Zeta-Zeta multiport converter with reduced number of switches. The proposed converter is simulated in MATLAB/ Simulink environment and is also realized as a hardware prototype. The voltage gain and efficiency of the proposed circuit is compared with its counterpart multiport topologies. The simulation and hardware results show that the proposed topology is having a clear edge on its counter parts in voltage gain and efficiency. The proposed converter indisputably assures the utmost use of renewable energy resources.

This article presents a non-conventional design approach of high order passive filters incorporated with distributed energy grid integration systems based on particle swarm optimization (PSO) as one of multi-objective evolutionary search algorithms. Two topologies of passive grid filters (third order passive damped LCL-filter and trap filter) are chosen as case studies. The presented grid filter design is based searching the optimum values of filter passive elements that can optimize an objective function composed of several terms such as harmonic attenuation factor and size (value) of passive elements (inductors and capacitors). The employed multi-objective design approach has three main advantages: (1) The PSO algorithm offers several groups of solutions to the same optimization problem. Accordingly, the most convenient solution can be chosen based on several factors such as cost of realization, availability in the market and the corresponding THD of grid current. (2) Multi-objective design approach is flexible enough to include other factors in the customized objective function to achieve different design criteria in accordance with new (or updated) versions of grid codes. (3) The PSO algorithm converges to the optimum solution(s) regardless the initial search values (initial guess). Consequently, the algorithm does not need any prior knowledge about filter numerical values The PSO algorithm has been developed in Matlab®, while the overall hardware grid-integration system has been modeled and studied using PSIM® software package. The obtained results demonstrate the effectiveness of the proposed approach to get practical and applicable values of filter components that result in good harmonic attenuation and satisfy the related codes of grid integration such as the IEEE standard 519. The main contribution of this paper is the utilization of evolutionary optimization technique to achieve an optimum design of passive grid filters that can optimize simultaneously several contradictory goals such as achieving the maximum possible harmonic attenuation at the lowest possible filter size. Compared with conventional design approach, the PSO-based filter design approach results in lower numerical values of filter components, which leads to considerable reduction in the size and cost of the passive grid filter. Moreover, grid filter design based on evolutionary search approach permits accommodation of several design criteria in the customized objective function with arbitrary weighting factors upon system design requests and new grid codes constrains.

The presence of certain toxic pollutants in water and wastewater such as chlorophenol must be eliminated, as they have negative effects on human health and the environment. Based on the state of the art, the reverse osmosis (RO) coupled with photovoltaic (PV) was chosen for wastewater treatment. The aim of this article is to evaluate the optimal operating conditions of RO-PV system that maximize chlorophenol rejection with minimal energy consumption. Two complementary approaches were followed combining physical models with statistical ones. The physical model used for the simulation is based on the equations of diffusion and matter balance. After demonstrating the reliability of this model, it was used for parametric sensitivity analysis, performing numerical experiments using a program developed under Python. The data obtained were used for operating parameters optimization, using artificial neural network method coupled with the desirability function. The results showed that the optimal values obtained, relating to feed pressure of 9.713 atm, water recovery rate of 40%, operating flow rate of 10−4 m3/s and temperature of 40 °C could remove 91% of chlorophenol with an energy consumption of 0.8 kWh/m3. This consumption allowed us to deduce that photovoltaic solar panel with a peak power of 280 Wp and a battery capacity of 9.22 kWh is sufficient to produce 1 m3/day.

Rapid exhaustion of fossil fuels followed by inherent climatic effects arising out of their use has forced the world to search for alternative energy sources. So, almost all nations including developing countries tend to harness renewable energies for the benefit of mankind. One such source is the sun offering clean, and environment-friendly energy. Solar energy can be changed into electricity and as well combined with other energies. This study is intended to model solar energy potential, delineate suitable grid-connected solar photovoltaic (PV) farms, and calculatetheir power generating capacity in the East Shewa Zone of Ethiopia using GIS-based approach combined with analytical hierarchical process. Results showed that 1129 km2 of area in the zone is ideal for the development of large PV solar farms.The findings suggest that as much as 2.2 TW of solar PV electric power can be fed to the grid system.The output of this study is thus useful to the government agencies and entrepreneurs engaged in the exploitation, production and promotion of non-conventional solar energy source in the region.

A photovoltaic array is environmentally friendly and a source of unlimited energy generation. However, it is presently a costlier energy generation system than other non-renewable energy sources. The main reasons are seasonal variations and continuously changing weather conditions, which affect the amount of solar energy received by the solar panels. In addition, the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays. To address this problem, the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm (MPPT) and the operating point of the photovoltaic system can be forced to its optimum value. This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power. However, the tracking algorithms are not equally effective in all areas of application. Therefore, selecting the correct MPPT is very critical. This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems, with consideration of the following key parameters: photovoltaic array dependence, type of system (analog or digital), need for periodic tuning, convergence speed, complexity of the system, global maxima, implemented capacity, and sensed parameter(s). In addition, based on real meteorological data (irradiance and temperature at a site located in Addis Ababa, Ethiopia), a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied. Finally, the study clearly validates the considerable energy saving achieved by using these algorithms.

Photovoltaic is a main device in solar power generation systems. The performance of this component needs to be improved to get the maximum power point. Many methods for maximizing power in photovoltaic have been developed and implemented in various algorithms. In fact, the algorithm has a lot of complexity and it requires a signal processing system that has a high speed and expensive one in the implementation. To overcome this problem, an algorithm based on power and voltage correlation inthe capacitors is developed to get maximum power. If the voltage across the capacitor is controlled according to the maximum power point voltage (VMPP), the maximum power (PMPP) value would be achieved. This concept is verified through computational simulations anda voltage control algorithm would be implemented using the Arduino Uno microcontroller for the final verification. The efficiency of the simulation is 99.88%–99.92% and an experimental is 92.84%–94.78%.

This article proposes an Artificial Neural Network (ANN) controller of Dynamic Voltage Restorer (DVR) to improve the performance of a stand-alone hybrid renewable energy system that is feeding a new community located in Egypt. The hybrid system consists of three renewable energy sources, namely, solar PV cells, a wind turbines based-permanent magnet synchronous generator, and fuel cells. These three sources are tied to a common DC link by three boost converters, one for each source. The common DC link is connected to the AC side via a DC/AC inverter. The optimal size of the three proposed renewable sources is calculated using the HOMER software package. The DVR control is attained through regulating the load voltage at different anomalous working conditions. These conditions are three-phase fault, voltage sag/swell, and unbalanced loading. Two ANNs are utilized to adjust the IGBT pulses of the voltage source inverter (VSI) used to control DVR by regulating the D-Q axes voltage signals. These D-Q axes components at any loading condition represent the inputs to the two ANNs. The outputs of the two ANNs represent the IGBT pulses. The input/output data used for training ANNs are obtained by two optimized PI controllers, introduced for regulating the load voltage through DVR-VSI pulses at different abnormal operating conditions, and accordingly convert the static optimized PI controller into adaptive one based ANN. The system performance with the proposed ANN-DVR controller is enhanced through improving the current, voltage, and power waveforms of each generating source. With compensation of the faulty line voltage, the system retains an uninterrupted operation of the three renewable sources during fault events and consequently increases the low voltage ride through (LVRT) capability. Moreover, the total harmonic distortion is reduced.

A high gain three port converter with a unidirectional port for photovoltaic (PV) side and two bidirectional ports one each for the battery and the DC bus for PV integration to DC microgrid is presented. High gain is achieved by a coupled inductor with switched capacitor, whereas single stage conversion is used between the ports to achieve high efficiency. The proposed converter is modelled in PLECS/MATLAB and the simulated results for various operational modes are validated using a 500 W prototype. For main operating mode, i.e., single input single output (SISO), the efficiency is calculated to be as high as 96 %. Similarly, owing to the reduced number of components, the losses are reduced considerably for different operation modes.

Concentrating solar power (CSP) technology has received increasing attention in recent years because of its distinct advantage for dispatchable power generation from solar energy. However, owing to its highly levelized costs of electricity, CSP plants are less competitive than photovoltaic (PV) power plants. To overcome this drawback and suppress PV power fluctuations, the concept of a hybrid CSP/PV power plant is proposed and developed. A capacity configuration method based on filtering and checking is proposed to seek a relationship between the capacity configuration of a hybrid CSP/PV system and the cost of solar energy. Co-content hybrid systems with different ratios of CSP capacity and PV capacity are modeled, and their comprehensive performance is investigated. Simulations and comparisons with a standalone CSP system focused on annual energy generation, capacity factor, levelized cost of electricity, and possibility for loss of power supply show that the hybrid CSP/PV systems possess different features depending on their capacity configurations. The results indicate that the proposed method can supply a convenient and simple operation pattern that favors engineering utilization and extension.