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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., (© 2024. The Author(s).)

The global transition towards clean and sustainable energy sources has led to an increasing interest in green hydrogen production. The present work focuses on the development and assessment of a solar-assisted green hydrogen production system. The basic objective of this work is to investigate the influence of solar radiation to drive the electrolysis process for green hydrogen production. The system design includes photovoltaic solar panel to capture solar radiation and convert it into electrical energy. This energy is further utilized to operate an electrolyzer with zinc electrodes that facilitates the water-splitting reaction resulting in the production of hydrogen gas. The solar panel outputs along with global radiation and other relevant climatic conditions are monitored. The hydrogen production is analyzed at three different voltages, i.e., 11 V, 12 V, and 13 V. After 60 min of operations, the maximum amount of hydrogen (2952 mL) is produced at 13 V. The fabricated electrolyzer has been found suitable and economically feasible., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Given the overexploitation of fisheries and the growing consumption of sea products, aquaculture is emerging as an alternative to meet the demand for protein at regional, national, and global levels. In northern Chile, the foothills of the Andes offer an opportunity for sustainable economic diversification. In this study, results of a rainbow trout ( Oncorhynchus mykiss ) culture in a recirculation system are presented, analyzing its growth and performance under altitude conditions. The research was carried out in Copaquilla, a small area in the foothills of northern Chile, 3000 m above sea level. Five thousand 15 g juvenile trout were acquired and transported by land from the Rio Blanco fish farm, successfully traveling more than 2100 km. During the 20-month-long culture, several growth parameters were evaluated, including specific growth rate, percentage of weight growth, feed conversion factor, survival, and Fulton's condition factor. All these parameters were within the normal growth range for trout, evidencing good-quality growth of the organisms. The results offer evidence that rainbow trout farming at 3000 m above sea level is viable and presents a viable performance, opening new opportunities for aquaculture in northern Chile.

In recent years, grid-connected multifunctional photovoltaic (PV) systems have proven to be highly efficient. This system integrates PV panels with a DC-DC boost converter (DC-DC-BC) and the electrical distribution grid (DEG). Linking the PV to the AC-DEG is accomplished through a three-level multifunctional voltage source inverter (MVSI). The DC-DC-BC component in this study is engineered to perform maximum power point tracking (MPPT) irrespective of normal or abnormal conditions. The conventional MPPT technique poses several challenges and constraints on system usage. Hence, the suggestion is to adopt synergetic control (SC) and sliding mode control (SMC) to enhance the MPPT technique's performance within the proposed system framework. Moreover, predictive direct power control is applied to the MVSI-based shunt active power filter, utilizing a phase-locked loop technique to achieve multiple objectives: minimizing energy fluctuations, injecting active power, correcting power factors, compensating reactive power, and mitigating harmonic currents. To implement the proposed system, the MATLAB is used for this purpose, with several tests used to study the behavior of the controls proposed in this work. Numerical results indicate significant reductions in active and reactive power fluctuations, with estimated rates of 38.46% and 15.30%, respectively, compared to traditional strategies. Moreover, the total harmonic distortion (THD) of the source current after filtering is reduced by 31.88% under solar irradiation of G = 1000 Wm 2 . Before filtering, the THD of current experiences a reduction estimated at 97.65%. These findings underscore the superior performance of the proposed control technique across all evaluated aspects., (© 2024. The Author(s).)

This study seeks to assess both environmental and economic effects associated with installing photovoltaic systems within construction waste landfills in Macau by employing an effective carbon emissions calculation methodology and benefit analysis method. Beginning by outlining characteristics and challenges associated with construction waste landfills, as well as photovoltaic systems used for this application in this paper. Here, we present a detailed outline of our methodology design, outlining its principles of life cycle analysis, data collection processes and the creation of carbon emissions calculation models. Subsequently, we examine photovoltaic systems within Macau's construction waste landfills by studying system design, component selection and operational strategies as well as carbon emission data collection during their operational time period. Under life cycle carbon emissions calculations, we assess the carbon emissions generated from photovoltaic systems as well as conduct an environmental and economic benefit analysis for carbon reduction benefit analysis purposes. This research incorporates sensitivity analysis and uncertainty consideration in order to conduct an extensive benefit analysis. The research results offer strong support for sustainable photovoltaic systems within Macau waste landfills as well as insights to inform planning and policy formation for similar future projects., (© 2024. The Author(s).)

Maximum power point tracking (MPPT) is required to get the highest possible power generated from a photovoltaic (PV) cell. Numerous researchers have proposed different MPPT strategies to be able to collect maximum generated electricity from the photovoltaic cells. In this research paper, a MPPT model predictive control strategy for a grid-connected PV system is presented. Model predictive control (MPC) was used to develop and model the AC load energy tracking efficiency for the PV systems with a power rate of 20 kW at standard test conditions. For the purpose of obtaining the power tracking performance, a DC-DC boost converter, DC-AC two level three phase inverter, and control mechanism for a grid connected AC load system was examined and presented in this paper. To approximate the actual PV array properties, the PV model is used, and the MPPT approach is suggested as a way to regulate the DC-DC boost converter and get the most power possible from the PV array when compared to P&O and model predictive control system. A three-phase, two-level VSI is employed in this study that is controlled by a model predictive control system with SVPWM. The inverter's control structure is developed using a model predictive control system (inner loop current controller) with reference frame transformation (abc to dq) coordinates by utilizing PLL. The PLL is used to obtain critical information about the grid voltage. A RL filter is then used to lower the total harmonic distortion of the output and connect the inverter's output to the grid. The MATLAB R2019a environment is used to create the system model. The overall performance of the system for conventional perturb and observer is around 97.72%, while for Finite Control Set Model Predictive Controller is 99.80%, which is better than previous similar research with faster time response and less oscillation around maximum power point., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Particle Swarm Optimization (PSO) is considered as one of Maximum Power Point Tracking (MPPT) controller algorithm developed for PhotoVoltaic system (PV) to guarantee a maximum power extraction under different climatic conditions of temperature and irradiation. Classical MPPT algorithms like Perturbe and Observe (P&O), PSO, Adaptive Neuro-Fuzzy Inference System (ANFIS) are an effective method for tracking the maximum power point (MPP) for the PV systems, but the problems with these approaches that they are less stable, high oscillation around steady state and slower convergence to the MPP. Based on recent research, the purpose of this paper is to introduces a novel MPPT controller based on a modified version of heterogeneous multi swarm PSO algorithm using an adaptive factor selection strategy (FMSPSO), to overcome the previous shortcomings and compared with conventional PSO, ANFIS and classical P&O controllers. Simulation and experimental results revealed that the new FMSPSO algorithm can overcome the previous shortcomings providing the superior performance to track the MPP efficiently with a shorter convergence time and small oscillations compared to other algorithms. The experimental confirmation of the FMSPSO algorithm has been carried out using NI-myRIO-1900 card and shows that with the proposed MPPT approach efficiency can reach a value greater than 99% even in climatic variation of irradiation and temperature., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

Microgrids are a promising solution for decentralized energy generation and distribution, offering reliability, efficiency, and resilience. These small-scale power systems can operate independently or connect to the main grid, providing greater reliability and resilience. However, integrating renewable energy into microgrids presents challenges due to their unpredictable nature and fluctuating load of electricity. Energy management strategies play a crucial role in optimizing the operation of microgrids, aiming to balance electricity supply and demand, maximize renewable energy utilization, and minimize operational costs. Various approaches have been proposed for energy management in microgrids, including optimization algorithms, machine learning techniques, and intelligent control systems. This study proposes an optimized and efficient strategy for microgrids operating in both independent and grid-connected modes, focusing on microgrids that utilize a combination of solar and green energy sources. The proposed approach, based on the Promoted Remora Optimization (PRO) algorithm, aims to meet load power requirements at the lowest possible cost while ensuring constant DC bus voltage and safeguarding batteries against overcharging and depletion. The CRO method effectively optimized the charging process, maintaining a consistent level of charge and achieving a final SoC of 33.37 %-33.60 %. It also demonstrated high system efficiency, with an average of 87.99 %, and a range of 87.80 %-88.03 %. The optimizer efficiency ranged from 83.12 % to 86.52 %, with an average of 86.46 %. The CRO method also achieved reasonable operating costs, with a cost per power of $0.1687/kW to $0.1699/kW and a daily cost of $1,379,595 to $1,479,998. Overall, the CRO method showed promise in optimizing the charging process in terms of efficiency and cost-effectiveness. Comparative analysis with existing literature is conducted to evaluate the effectiveness of the proposed approach, demonstrating its superior results compared to other energy management strategies for microgrids. This study contributes to the field of microgrid energy management by providing a novel approach based on the PRO algorithm and demonstrating its effectiveness through comparative analysis., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Photovoltaic power generation is developing rapidly with the approval of The Paris Agreement in 2015. However, there are many dust deposition problems that occur in desert and plateau areas. Traditional cleaning methods such as manual cleaning and mechanical cleaning are unstable and produce a large economic burden. Therefore, self-cleaning coatings, which have unique mechanisms and high adaptability, have attracted wide attention in the photovoltaic industry and scientific community, especially the super-hydrophobic and super-hydrophilic coatings. The paper systematically reviewed the theory, materials, preparation, and applications of the super-hydrophobic and super-hydrophilic coatings on the photovoltaic modules. Super-hydrophobic materials such as organosilicon compounds, fluorinated polymers, and some inorganic materials are popular. TiO 2 is widely used to prepare super-hydrophilic coatings on glass covers of photovoltaic panels due to its good photocatalytic activity. CVD-based surface treatment is suitable for preparing photovoltaic self-cleaning surfaces. These methods prepare self-cleaning surfaces by reacting gaseous substances with hot surfaces and depositing them on the surface. They are efficient but difficult to control accuracy. When applied to photovoltaic modules, it is crucial to consider the factors such as self-cleaning, transparency, anti-reflection, anti-icing, and durability. In future research, it is significant to improve the transparency, durability, and self-cleaning properties of coatings., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Water is a precious resource for agriculture and most of the land is irrigated by tube wells. Diesel engines and electricity-operated pumps are widely used to fulfill irrigation water requirements; such conventional systems are inefficient and costly. With rising concerns about global warming, it is important to choose renewable energy source. In this study, SPVWPS has been optimally designed considering the water requirement, solar resources, tilt angle and orientation, losses in both systems and performance ratio. A PVSyst and SoSiT simulation tools were used to perform simulation analysis of the designed solar photovoltaic WPS. After designing and performance analysis, farmers were interviewed during fieldwork to assess socioeconomic impacts. In the result section, performance of PV system is analyzed at various tilt angles and it is established that system installed at a 15° tilt angle is more efficient. The annual PV array virtual energy at MPP of designed photovoltaic system is 33342 kWh and the annual energy available to operate the WPS is 23502 kWh. Module array mismatch and ohmic wiring losses are 374.16 kWh and 298.83 kWh, respectively. The total annual water demand of the selected site is 80769 m³ and designed SPWPS pumped 75054 m³ of water, supplying 92.93% of the irrigation demand. The normalized values of the effective energy, system losses, collection losses and unused energy in the SPVWP system are 2.6 kW/kWp/day, 0.69 kW/kWp/day, 0.72 kW/kWp/day and 0.48 kW/kWp/day, respectively. The annual average performance ratio of the proposed system is 74.62%. The results of the interviews showed that 70% of farmers are extremely satisfied with the performance of SPVWPS and 84% of farmers indicated that they did not incur any operating costs. The unit cost of the SPWPS is 0.17 €/kWh, which is 56.41% and 19.04% less expensive than the cost of diesel and grid electricity., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

This paper analyzes the economics of a grid-interactive rooftop solar photovoltaic (PV) system and the impact of the temperature on it. The analysis related to energy metrics, lifecycle costing, and environmental economics was performed considering the PV system's life as 30 years. The system economics is also compared at different conditions like theoretical, temperature-corrected, and real electricity generation data. The parameters like energy payback time (EPBT), energy return on energy invested (EROI), and lifecycle conversion efficiency are determined as 5.95 years, 5.04, and 0.078, respectively, based on actual generation. The unit electricity cost of the rooftop PV system was estimated as INR 5.37 at the 5% interest rate. The electricity cost varies with the interest rate variation and operation system life. The results show a reduction in overall economic performance on the increase in module temperature. The effect of temperature on the economics of the system is presented in terms of the per degree rise of module temperature. One degree increase of module temperature 8.5 days in EPBT of the PV system increases, and INR 0.021 increases in the unit cost of electricity considering a reference temperature 25 °C. A PV system has environmental benefits by reducing greenhouse gas emissions, which are also affected by the rise of module temperature. The system lost INR 355.93 in carbon credits at an increase of one-degree module temperature., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The proposed measured data combines PV plant electrical data with associated solar and meteorological data during normal and faulty conditions. Data are collected regarding a domestic rooftop PV plant of 4 kW, located in the La Réunion Island, in the South-West of Indian Ocean. The present dataset includes healthy behavior and different types of shading faults, identified and labelled by means of a numeric variable. The electrical data (voltage, current and power at AC and DC side as well as produced energy and grid frequency) are collected thanks to PV inverters. Global and diffuse irradiance, PV temperature and ambient temperature are acquired thanks to additional sensors. Electrical and meteorological data sampling frequencies are set to 0.2 Hz and 1 Hz respectively. At present, 12 months of data are available and the database is still being updated. The data streams from each connected device require proper techniques to ensure their persistence. To be able to provide both efficient ingestion and retrieval of these time series collections, the NoSQL database management system InfluxDB has been implemented. The whole dataset is available on Zenodo repository, and can be used, for instance, for PV modeling, PV plant behavior analysis, PV production forecasting and PV Fault Detection and Diagnosis (FDD) tool development., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Global Horizontal Irradiance was measured using a thermopile-type pyranometer during more than three years using a sample time of two seconds, with the purpose of capturing fast transient events of irradiance which are notable in tropical regions as the one where these data were collected: Bogotá, Colombia. The date and time of each measurement were registered along with the irradiance values. In addition, other related quantities were calculated and included for each one of the measurement instants: Optical Air Mass, Zenith angle, Extraterrestrial Solar Irradiance, and Clearness Index. Daily aggregated statistics of irradiance were calculated and are provided here too. Data points corresponding to nights were discarded. The raw data was analyzed to remove incomplete days, to guarantee that daily statistics are accurate and meaningful. After this data cleaning process, 1016 complete days remain, having a total of 21,959,912 data points. These data are useful for studying the effect of irradiance transients over photovoltaic systems, including power electronics, batteries and electric loads; it can also be used in studies about the stability of the radiative regime or the variability of irradiance such as Avila et al. (2019) (where part of these data was effectively used) and other related works cited there., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: There are not any other interests to declare., (© 2022 The Authors. Published by Elsevier Inc.)

Water-, energy-, and food (WEF) related practices, such as low impact development (LID), residential solar panels, and rooftop urban agriculture, have been applied to improve urban sustainability and resilience under climate change and urbanization. However, most practices require space. This requirement may result in competition for land. In addition, not all newly built practices benefit the environment from the life cycle perspective. Therefore, this study aims to develop a systematic WEF-related practice planning method to improve urban sustainability and resilience in a limited space. The core method is a multi-objective optimization model that considers the performance and environmental impacts of the selected practices. The assessment was conducted in a densely populated area in Taipei, the capital city of Taiwan, to describe the planning processes and demonstrate the feasibility of the methods. In the Taipei case, five goals were defined: the supply of WEF, the sponge city development target, and the greenhouse gas reduction target. The optimal results of the multi-objective optimization model indicated the closeness of the optimal implementation of WEF-related practices to achieving the goals. The results showed that the optimal arrangement of WEF-related practices could provide water supply benefits and was favorable for developing a sponge city. According to the sensitivities, to achieve urban sustainability and resilience, the priorities in order of importance are as follows: establish a rainwater harvesting system for buildings, encourage the implementation of rooftop photovoltaic systems, and improve the materials and processes used solar panel and bioretention cell production. The systematic planning method provides a quantitative assessment and delivers practical cross-sectoral integrated strategies for decision-making., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

With the recent focus marked on energy efficiency and solar energy development, much research is being dedicated to the development of enhanced maximum power point tracking (MPPT) algorithms for photovoltaic applications. However, the main criteria with regard to tracking performances and circuit implementation are still considered as a major challenge under rapid varying weather conditions. In this paper, a T-S Fuzzy-integral backstepping-based hybrid MPPT technique is proposed for rapid, accurate and efficient tracking. The proposed technique enables reliable and stable operation under fast dynamic environmental changes. Besides, it is simple as it does not require extra atmospheric sensors. The theoretical analysis addressed in this study is verified through simulations via Matlab/Simulink and experimental outdoor tests. A comparison with different other MPPT techniques is provided to highlight the performances of the developed MPPT method., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is one of the biggest public health issues in the last years. The WHO has reported more than 50,000 confirmed cases and more than 1,000,000 confirmed deaths around the world. Early diagnosis is essential for an appropriate patient care and infection control, so laboratory where molecular tests are held plays a main role. However, laboratory facilities for testing are limited in rural areas. Therefore, it is important to have an effective and practical point-of-care diagnostic system in order to be implemented in developing countries with limited energy access. The objective of this research is to develop an energetically autonomous point-of-care diagnostic system for molecular detection of SARS-CoV-2. This design consists of a retractable system with an area of 15.79 m 2 and 3 well-distributed interior areas to guaranty appropriate sample processing. Our point-of-care diagnostic system can be installed at a fixed place (stationary), and it can also be transported to various strategic places (itinerant). The off-grid photovoltaic system feasibility was evaluated using the PVsyst software, presenting an installed capacity of 2.79 KWp, consisting of 4 monocrystalline photovoltaic modules, a 45 A charge regulator and 4 batteries (6 V, 453 Ah). The results showed a performance ratio of 0.522, with higher losses by the full battery (31.77%). This research determines that the proposed point-of-care diagnostic system meets all requirements to set and operate molecular techniques to diagnose infectious diseases, such as COVID-19, with good laboratory conditions, secure and eco-efficient energy, supporting the health scheme to prevent and control the spread of the virus., Competing Interests: Conflict of interestNot applicable., (© The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021.)

Pristine thermally evaporated nickel-(II)-tetraphenyl-21H,23H-porphyrin (NiTPP) thin films are amorphous, but after 4 and 8 h of UV illumination, the films become crystalline with preferred orientations of (112), (103) and (004) and crystallite sizes of (13, 18, 16) and (42, 31, 38) nm after 4 and 8 h, respectively. After UV illumination for 4 and 8 h, the NiTPP thin films are characterized by blueshifted absorption coefficients, increasing the optical and fundamental gap values and decreasing the dispersion parameter values. The dielectric properties display energy storage regions corresponding to the peak values of optical conductivity, which provides an elegant confirmation of the tailoring and tuning of band gaps, energy storage properties and optical conductivity by UV illumination time. Therefore, NiTPP films may be good candidates for environmental and energy storage applications., Competing Interests: Conflict of interestAuthors declare that there no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.)

A nonlinear sliding mode controller is proposed for a single stage grid-connected photovoltaic system with a novel nonlinear sliding surface. The proposed controller is designed to ensure maximum power extraction with unity power factor. There are two main advantages of the proposed sliding surface. The new surface will results in a first order sliding mode controller. The second advantage is that maximum power extraction is achieved by tracking DC-link voltage (V dc ) of the PV system. The proposed controller is also compared with the existing sliding mode controller in terms of both numerical simulation and experimental results. It is found that, the proposed controller's performance is better than the existing controller in terms of power extraction and more robust when there are uncertainties and disturbance in PV system., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier Ltd.)

The conventional maximum power point tracking (MPPT) algorithm shows best performance under uniform insolation but when photovoltaic (PV) array is partially irradiated, the Power vs Voltage (P-V) plot consists of multiple local maxima power point (LMPP) and one global maxima power point (GMPP). The conventional MPPT algorithm may track local peak and fluctuate around it, resulting in lower power tracking. To eradicate this drawback of conventional algorithm, the solar PV system requires the synthesis of modified controller which is able to discriminate between local and global peak point. Along with implementing modified MPPT controller, to minimise the adverse effect of partial shading on PV system, different PV array arrangements like series-parallel (SP), honey comb (HC), total cross tied (TCT) etc. may be used. Author(s) in the present study, has proposed asymmetrical interval type-2 fuzzy logic control (IT-2 AFLC) based MPP algorithm for tracking global peak in partial shading condition (PSC) with different PV array arrangements. The presented algorithm has been compared with other approaches viz. perturb & observe (P&O) and type-1(T-1) FLC for GMPP tracking, fill factor, shading losses, mismatch loss and efficiency to establish its superiority. For evaluating the efficiency of different algorithms, the EN50530 MPPT efficiency test has been performed under dynamic condition. The proposed algorithm has been developed under MATLAB/Simulink environment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 ISA. Published by Elsevier Ltd. All rights reserved.)

Abstract: This paper examines the environmental impact of a grid-connected PV system in Kocaeli, Turkey, supported by East Marmara Development Agency to contribute local economic and environmental sustainability goals. For this purpose, energy payback time and greenhouse payback time analysis is carried out in terms of calculated total embodied data and measured annual operation data. The results indicate that the system spends approximately 12.68% of its lifetime to payback its total embodied energy and 10.67% to save its total embodied greenhouse gas emissions., (© Springer-Verlag GmbH Germany, part of Springer Nature 2020.)

When the photovoltaic (PV) and solar thermal energy (STE) systems, which share the rooftop area, are installed in the same building, a trade-off problem occurs in terms of the energy, economic, and environmental aspects, and thus, steps need to solve this problem. Therefore, this study aimed to develop a multi-criteria decision support system of the PV and STE systems using the multi-objective optimization algorithm. This system was developed in the following six steps: (i) database establishment; (ii) designing the variables of the PV and STE systems; (iii) development of the analysis engine of the PV and STE systems; (iv) environmental and economic assessment from the life cycle perspective; (v) integrated multi-objective optimization (iMOO) with a genetic algorithm; and (vi) establishment of a multi-criteria decision support system. To verify the robustness and reliability of the developed model, an analysis of "D" City Hall and "I" Airport as target facilities was performed. The optimal PV and STE systems that consider the energy, economic, and environmental aspects at the same time were determined with respect to the 1.23 × 10 15 and 1.05 × 10 16 installation scenarios, respectively, in terms of effectiveness. The iMOO scores of the existing PV and STE systems installed in "D" City Hall and "I" Airport were 0.358 and 0.346, respectively, whereas those of the optimal solutions were 0.249 and 0.280, showing score improvements. In terms of efficiency, the times required for determining the optimal solutions were 20 and 30 min, respectively. The developed model makes the final decision-maker to find the optimal solution in introducing the PV and STE systems in the early design phase at the same time., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Maximum power point tracking (MPPT) is necessary to achieve an optimal exploitation of photovoltaic (PV) system. This paper presents a novel voltage-oriented MPPT (VO-MPPT) method, where the conventional perturb and observe (P&O) algorithm is combined with the proposed external voltage control based on an adaptive integral derivative sliding mode (AIDSM). It is designed with new sliding surface, in addition, the derivative and integral terms are chosen to eliminate the overshoot during fast changes in solar irradiation and to minimize the steady-state fluctuation. Furthermore, an adaptation mechanism is joined to adjust the controller gains under each irradiation level. The proposed MPPT is tested and compared with the most widely used MPPT methods by simulations using MATLAB/Simulink TM and real time hardware in the loop (HIL) implementation. The results obtained with the proposed MPPT show excellent dynamic performance under fast irradiation changes., (Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.)

Dairy farms have been widely acknowledged as a source of greenhouse gas (GHG) emissions. The need for a more environmentally friendly milk production system will likely be important going forward. Whereas methane (CH 4 ) enteric emissions can only be reduced to a limited extent, CH 4 manure emissions can be reduced by implementing mitigation strategies, such as the use of an anaerobic digestion (AD). Furthermore, implementing a photovoltaic (PV) electricity generation system could mitigate the fossil fuels used to cover the electrical needs of farms. In the present study to detect the main environmental hotspots of milk production, a Life Cycle Assessment was adopted to build the Life Cycle Inventory according to ISO 14040 and 14044 in a conventional dairy farm (1368 animals) provided by AD and PV systems. The Intergovernmental Panel on Climate Change tiered approach was adopted to associate the level of emission with each item in the life cycle inventory. The functional unit refers to 1kg of fat-and-protein-corrected-milk (FPCM). In addition to milk products, other important co-products need to be considered: meat and renewable energy production from AD and PV systems. A physical allocation was applied to attribute GHG emissions among milk and meat products. Renewable energy production from AD and PV systems was considered, discounting carbon credits due to lower CH 4 manure emissions and to the minor exploitation of fossil energy. The CF of this farm scenario was 1.11kg CO 2 eq/kg FPCM. The inclusion of AD allowed for the reduction of GHG emissions from milk production by 0.26kg CO 2 eq/kg FPCM. The PV system contribution was negligible due to the small dimensions of the technology. The results obtained in this study confirm that integrating milk production with other co-products, originated from more efficient manure management, is a successful strategy to mitigate the environmental impact of dairy production., (Copyright © 2017 Elsevier B.V. All rights reserved.)

This paper presents an adaptive super-twisting sliding mode control (STC) along with double-loop control for voltage tracking performance of three-phase differential boost inverter and DC-link capacitor voltage regulation in grid-connected PV system. The effectiveness of the proposed control strategies are demonstrated under realistic scenarios such as variations in solar insolation, load power demand, grid voltage, and transition from grid-connected to standalone mode etc. Additional supplementary power quality control functions such as harmonic compensation, and reactive power management are also investigated with the proposed control strategy. The results are compared with conventional proportional-integral controller, and PWM sliding mode controller. The system performance is evaluated in simulation and in real-time., (Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.)

This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems., (Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.)

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in . The application of these files can be generalized to variety of communities interested in investing on PV systems.

In the present paper, a fuzzy controller applied to a Variable-Speed Drive (VSD) for use in Photovoltaic Pumping Systems (PVPS) is proposed. The fuzzy logic system (FLS) used is embedded in a microcontroller and corresponds to a proportional-derivative controller. A Light-Dependent Resistor (LDR) is used to measure, approximately, the irradiance incident on the PV array. Experimental tests are executed using an Arduino board. The experimental results show that the fuzzy controller is capable of operating the system continuously throughout the day and controlling the direct current (DC) voltage level in the VSD with a good performance.