Solar Irradiation Availability Research Articles

Hybrid Solar PV and WECS Power Quality Improvement by STATCOM

The increasing integration of off-grid energy sources in the utility load has ended up resulting in elevated standards regarding power quality, voltage stabilisation purposes, and efficient energy use. The electrical network Wind and solar energy have been considered to be among the most reliable renewable energy sources. However, the self-sufficient operation of either photovoltaic or wind energy systems does not offer a highly consistent source of electricity production owing to the unpredictability of the wind and solar irradiance availability. As a result of this, a variety of solar and wind power generation systems have the ability to produce a very reliable and promising electrical supply. In the present study, a hybrid wind and photovoltaic panels system model has been provided. This specific type of technology possesses plenty of possibilities for its users from afar. This particular kind of technology is highly beneficial in inaccessible or offshore locations where integrating with the grid is not very cost-effective. Nevertheless, integrating power electronics to dissipated generation (DG) systems brings substantial issues with power quality, which include reactive power adjustment and harmonic development, which throws off the system for power distribution. The present study proposes a simulation framework for a hybrid wind-photovoltaic generation system. The system's efficiency in gridconnected mode is assessed. Calculations of total harmonic distortion (THD) at various speeds of wind were used for assessing the wind-SPV hybrid system's power quality. This hybrid system's power quality has been enhanced owing to its employing of STATCOM.

Accelerating Renewable Energy Integration in Energy Planning Considering the PV Techno-Economics and Hourly Profile, Case Study: Indonesian Power Sector

In planning for the generation capacity expansion planning, it is crucial to consider the economics of scale and the availability of primary energy sources. Solar power generation or PV PP is a plant that is very dependent on the availability of solar irradiance and land. To achieve Net Zero Emission by 2060, the Indonesian government aims to increase PV capacity to 4.68 GW. To support the accelerated integration of PV power plants into the electrical system and fulfill economic and sustainable aspects, the ideal capacity of PV power plants needs to be considered. This study involves optimization and comparison with various scenarios to determine the optimal combination for PV power plant planning. In the optimization process, Mixed Integer Linear Programming (MILP) is used, assuming a load of 100 MW and various PV profiles. Based on the optimization results, to meet a 100 MW load, 138 MW of PV power plants are required, with a configuration of 125 MW for large-scale PV PP, 10 MW for medium-scale PV PP, and 3 MW for rooftop PV PP. The total cost needed is 11,445 thousand dollars, with an levelized cost of electricity (LCOE) of 4.75 c$/kWh. This value is significantly lower compared to other scenarios. To supply for 24 h, PV PP can utilize BESS, with an LCOE reaching 7.79 c$/kWh when optimal capacity and generation are achieved. The recommendation for determining the capacity of PV PP is to use the large-scale capacity scheme, both for daytime supply systems and for the 24-h scheme.

Optimal control of a solar-driven seasonal sorption storage system through deep reinforcement learning

Deep reinforcement learning (DRL) has demonstrated its effectiveness in the control of energy systems, although it has not yet been applied to sorption thermal energy storage (TES) systems. The operation of sorption TES systems is notably more complicated compared to other TES variants. The discharge of a sorption TES occurs at a particular desorption and evaporation temperature. Achieving a continuous and efficient discharge of a sorption TES is a challenging control task if heat required at the evaporator is obtained from the sun or the environment. Its operation is especially complicated during winter, because of the limited availability of solar irradiation and low ambient temperatures. Thus, this study analyzes for first time in the literature the competitiveness of deep reinforcement learning to control a solar-driven seasonal sorption TES system and compares it against traditional optimized rule-based control strategy. The system, located in Central Europe, supplied domestic hot water and space heating to a single-family house. Two DRL models were developed and trained to operate the system under two different sets of data: 120 winter consecutive days and 60 winter non-consecutive days. The results showed that the DRL control strategy reduced the system operational costs by 28% in a 60 winter days scenario. For a 120 winter days scenario, the operational cost savings decreased to 13% because the smart control performed worst once the sorption TES was fully discharged. These results were derived from a four-year validation data set, bolstering their robustness. The study demonstrates the successful application of DRL in controlling a solar-driven seasonal sorption TES system, yielding considerable economic savings compared to an RBC strategy. Subsequent work will consist of implementing the smart control strategy at prototype level to assess its performance.

Evaluation of the Solar Energy Nowcasting System (SENSE) during a 12-Months Intensive Measurement Campaign in Athens, Greece

Energy nowcasting is a valuable asset in managing energy loads and having real-time information on solar irradiation availability. In this study, we evaluate the spectrally integrated outputs of the SENSE system for solar irradiance nowcasting for the period of the ASPIRE (atmospheric parameters affecting spectral solar irradiance and solar energy) campaign (December 2020–December 2021) held in Athens, Greece. For the needs of the campaign, several ground-based instruments were operating, including two pyranometers, a pyrheliometer, a cloud camera, a CIMEL sunphotometer, and a precision spectral radiometer (PSR). Global horizontal irradiance (GHI) estimations were more accurate than direct normal irradiance (DNI). SENSE estimations are provided every 15 min, but when comparing bigger time intervals (hours-days), the statistics improved. A dedicated assessment of the SENSE’s inputs is performed in respect to ground-based retrievals, considering cloud conditions (from a sky imager), AOD, and precipitable water vapor from AERONET. The factor that established the larger errors was the visibility of the solar disc, which cannot be defined by the available sources of model inputs. Additionally, there were discrepancies between the satellite estimation of the clouds and the ground picture, which caused deviations in results. AOD differences affected more the DNI.

Anatomia foliar e mecanismos morfofisiológicos de aclimatação a alta irradiância em genótipos de helicônias

ABSTRACT The amount of solar irradiation available in the growing environment can cause significant changes in physiology and leaf anatomy that enable crops to acclimate to different light conditions. In this sense, the objective was to characterize the leaf anatomy and to elucidate the morpho-physiological mechanisms of acclimation to high solar irradiance of heliconia genotypes during the initial stage of development under semiarid conditions. The experiment was conducted in the municipality of Petrolina, Pernambuco state, Brazil (09° 19’ 14” S, 40° 32’ 40” W, and 387 m of altitude) and the behavior of three heliconia genotypes (Heliconia rauliniana; H. bihai cv. Lobster Claw Two, and H. rostrata) grown in full sun and shading (50%) environments were evaluated. At 30 days after the implementation of the experiment, leaf anatomy, chlorophyll index, plant height, number of leaves, and number of tillers were analyzed. Heliconia leaves are characterized as amphistomatous with tetracytic stomata. In its main vein there are aerenchyma structures and hypodermis on the abaxial and adaxial sides. The responses to different light conditions in plants of H. bihai, H. rauliniana, and H. rostrata are genotype-specific. Furthermore, the anatomical structures and physiological changes observed in H. bihai and H. rauliniana plants demonstrate that these genotypes present greater plasticity and consequently greater potential for acclimation to high solar irradiation conditions. Thus, the genotypes H. rauliniana and H. bihai emerge as a potential alternative for cultivation in gardens or in open areas and for exploration as cut flower in regions with high solar irradiation availability.

A spatial optimization approach to increase the accuracy of rooftop solar energy assessments

Recent years have seen a substantial increase in energy produced by renewable sources. The International Energy Agency (IEA) expects a large portion of future growth in renewable energy to come from solar, especially rooftop photovoltaic (PV) systems. Studies focused on estimating rooftop solar energy potential generally use the total area available for PV installation as determined by solar irradiance availability. This process can lead to substantial over- or under-estimation of energy estimates. Only a few studies have incorporated the spatial layout of PV panels in the solar energy generation estimates, and none have simultaneously considered PV panel size, orientation, and rooftop structure. We address this limitation with a new spatially explicit optimization framework to enhance the accuracy of rooftop solar energy assessments. We consider both the roof's structural configuration and the shape and size of the panels in a novel maximum cover spatial optimization model. After applying the framework to three different types of rooftops (flat roof, pitched roof, and complex roof), we find that conventional methods can lead to a nearly 60% overestimation of energy potential compared to the optimized panel layout. Our work illustrates the importance of considering panel size and rooftop characteristics and offers a mechanism for designing more efficient rooftop PV systems.

Evaluation of the barriers to and drivers of the implementation of solar energy in Saudi Arabia

ABSTRACT Currently available evidence indicates that energy demand in the Kingdom of Saudi Arabia (KSA) is generally increasing and solar energy constitutes a promising new source of energy. Thus, this paper aims to identify and assess the most critical barriers and drivers of the implementation of solar energy in KSA. This study develops and employs a systematic decision-making framework based on the judgment of experts. The interactions between the barriers and drivers are evaluated using rough DEMATEL (integrated crisp DEMATEL and rough set theory) and interpretive structure modelling (ISM). Rough set theory serves to address the involvement of vagueness. Furthermore, this paper conducts MICMAC analyses to evaluate the driving and dependence power of the drivers and barriers. This paper finds that the most significant barrier to solar energy in KSA is the expensive electricity generated by solar energy while the most significant driver of solar energy in KSA is the availability of solar irradiation. This study will assist industrial managers who are working on the implementation of solar energy projects in KSA, enabling them to properly assess and evaluate the solar energy sector in the country. This study is amongst the first of its kind to address the barriers to and drivers of the implementation of solar energy in KSA by using the rough DEMATEL method.

Estimating storage needs for renewables in Europe: The correlation between renewable energy sources and heating and cooling demand

The inexhaustible availability of solar irradiance and wind speed makes these natural resources major contributors to a CO2 neutral energy system. Since these natural resources interact with temperatures, this paper aims at determining their correlation with temperature derived heating and cooling degree-hours (HDH and CDH) historically and based on climate projections towards 2100. The case study investigates demand and supply balancing requirements in three European climate regions Spain, Austria and northern Europe. Two approaches are used to analyse the hourly correlation on different time scales and the relationship of daily and weekly totals assuming storage. Understanding these interrelations provides a basis for appropriate planning and forecasting in smart energy systems. While solar irradiance does correlate strongly with CDH on hourly basis, achieving 0.80 in Spanish locations and 0.60 in Austria, the relation between wind speed and heating demand is more complex only reaching moderate (0.40–0.59) correlation with monthly storage in all regions. The relationship between solar irradiance and heating needs, by contrast, seems promising in central and southern Europe by applying daily storage to reach moderate to strong (0.40–0.79) results. While HDH will lose importance mostly in Madrid, but also in Vienna and Stockholm, CDH will increase. The implications for final energy demand, however, require consideration of additional parameters, such as energy efficiency measures on building insulation. Smart energy systems, therefore, should embrace the positive correlation between solar irradiance and CDH, and account for at least monthly storage of potential wind power to use VRE for heating and cooling efficiently.

A novel method to determine the optimal operating point for centrifugal pumps applied in photovoltaic pumping systems

Every centrifugal pump has an optimum efficiency duty point, known as Best Efficient Point (BEP), which is usually specified by the manufacturer. In conventional pumping systems, the centrifugal pump must operate at the rated speed and as close as possible to the BEP for optimal performance. This design approach, based on the BEP concept, is suitable only when the centrifugal pump is supplied by sources that can maintain the pump’s operation at the rated frequency (50 Hz or 60 Hz) and voltage (220 V or 380 V). In photovoltaic pumping systems, the conventional centrifugal pump works at different speeds according to the availability of solar irradiance. Therefore, the BEP concept does not offer the best performance in terms of efficiency. This paper presents a method to determine the operating point that provides maximum efficiency for a given photovoltaic pumping system composed of a conventional centrifugal pump driven by a power control system. This point, referred to as Solar Best Efficiency Point (SBEP), is calculated considering the entire operating range of the pump for a given irradiance and photovoltaic cell temperature profile. According to the results, the SBEP operation, compared to the BEP operation, can increase the daily efficiency of the photovoltaic pumping system by up to 6.7%, depending on the centrifugal pump used. Furthermore, the theoretical approach developed in this paper shows that the selection of the motor-pump set cannot be based solely on the pump’s characteristics, as the motor quality significantly influences system performance.

Numerical Simulation of Rock-bed Solar Thermal Storage Energy

Solar dryers are increasingly being applied to dry fruits and vegetables in order to increase their shelf-lives. In the sunny-belt countries, the availability of solar irradiance is taken for granted and the mean daily solar irradiation is often used as the design basis for a solar dryer. The predicted performance of the solar irradiance is therefore inherently inaccurate. Contemporary solar dryer designs incorporate thermal energy storage (TES) systems for application after sunset. The performance of such TES systems is often determined experimentally. In this study, mathematical models have been developed and by numerical simulation using the technique of Finite Differential Method (FDM) and MATLAB programming, the performances of solar irradiance as well as that of the TES system have been predicted. The simulation results were secured to inform the design of the solar dryer for fruits and vegetables in the sun-belt countries.

Energy balance and performance assessment of PV systems installed at a positive-energy building (PEB) solar energy research centre

The energy balance and performance of all Photovoltaic (PV) systems installed at Fotovoltaica/UFSC solar energy laboratory (www.fotovoltaica.ufsc.br) in Florianópolis, Brazil (27° S; 48° W) were demonstrated over time, from Aug/2017 to Feb/2020. The laboratory was designed as a zero-energy building (ZEB) with PV systems installed on rooftops and façades, not maximising annual generation, but to achieve a compromise between aesthetic appeal and the energy output. Further PV systems were installed on the same site in the shapes of a carport, an electric bus (eBus) shelter and charging station, and different ground-mounted PV systems fixed at latitude tilt and single-axis tracking. Monthly analyses were carried out during the period, such as the solar irradiation availability on site, changes in the number of building occupants, the increase of installed capacity of PV systems, and energy generation and consumption. With 111 kWp, the total PV generation in the period could supply 148% of building energy needs and 97% of the Fotovoltaica/UFSC Laboratory (building plus eBus). However, there were some downtime events in certain PV systems due to R&D activities, which affected total energy production. If systems had operated at their optimal performance all the time, the laboratory could have generated 38% more energy, which means 134% of building plus eBus consumption. Therefore, the Fotovoltaica/UFSC Laboratory can be considered not only a ZEB, but a positive-energy building (PEB). The issues discussed in this paper apply not only to the particular case-study presented; they demonstrate the potential of BIPV in enabling energy positive buildings.

English

A solar photovoltaic (SPV) system generating power to run a 53-m3 storage for indirect air-cooling combined with evaporating cooling (IAC+EC) for providing a cool environment for storage of tomatoes under small-scale farming was evaluated. The experiment consisted of nine 330 W solar modules, twelve 230 AH Gel batteries, 145 VDC solar charge controller, 5 kW inverter, 290 W ventilation fan, 260 W water pump, psychrometric unit, and a 3.8-ton tomato storage chamber constructed and assembled on site. The psychrometric unit consisted of three-cooling pad layers and a 1760 W indirect heat exchanger. The solar modules were arranged in three series-three strings and were used in conjunction with a three string-48V bank facility. The performance evaluation of the system was conducted with full recirculation of air inside the storage chamber using solar module yield and efficiencies of inverter, battery and charge controller. Based on the experiment data the SPV system produced 2873.5 W that is 98% of the design power output at 80% probability of exceedance. The power yield of 2873.5 W was 24% higher than the power required in running the electrical appliances for IAC+EC system. Tracking the SPV system under ambient conditions with an average daily generation during the period of the experiment, the electrical power efficiency was 14.9%. The power output of modules increased with temperature of the module to 24°C and declined thereafter. The power generated by the SPV system depended on the solar irradiance availability, ambient temperature at the site and the time of the day. It was found that the SPV system could power the IAC+EC during daytime for the summer season, and the excess power stored in the battery could run the system until 22.00 h at night when temperatures were low enough for storage of tomatoes and SPV system was then switched off. Key words: Small-scale farming, design power, theoretical power, efficiencies, actual power.

Numerical Simulation of Rock-bed Solar Thrmal Storage Energy

Solar dryers are increasingly being applied to dry fruits and vegetables in order to increase their shelf-lives. In the sunny-belt countries, the availability of solar irradiance is taken for granted and the mean daily solar irradiation is oftn used as the design basis for a solar dryer. Th predicted performance of the solar irradiance is therefore inherently inaccurate. Contemporary solar dryer designs incorporate thermal energy storage (TES) systems for application aftr sunset. Th performance of such TES systems is oftn determined experimentally. In this study, mathematical models have been developed and by numerical simulation using the technique of Finite Diffrential Method (FDM) and MATLAB programming, the performances of solar irradiance as well as that of the TES system have been predicted. Th simulation results were secured to inform the design of the solar dryer for fruits and vegetables in the sun-belt countries.

Quantifying effects of the built environment on solar irradiance availability at building rooftops

Solar radiation significantly impacts the performance of buildings and integrated renewable energy technologies. Surrounding buildings may reduce the amount of radiation reaching urban building rooftops, but may also enhance solar energy availability through scattering and reflections. These effects are difficult to quantify due to the complexity of urban geometries. Here, a new parameterization that quantifies the role of urban form on the availability of rooftop solar radiation, including the effects of mutual reflections and shading, is developed and tested. We find that available rooftop solar energy may be parameterized by a simple model using only plan area fraction, average building height, and building height standard deviation. The new model is developed using the building-resolving, ray-tracing based radiation transfer model QESRadiant to simulate incident solar irradiation in 125 city models over 11 latitudes for 13 days (18,000 simulations). The parameterization error is less than 5% for latitudes that encompass 95% of the world's population.

Multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle power plant based on NSGA-II

Non-dominated sorting genetic algorithm (NSGA-II) was deployed in this paper for multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle (ORC) power plant. The existing plant consists of a field of linear Fresnel collectors (LFC), integrated directly with two-tank thermal energy storage (TES) system, which interfaces with ORC power block. The real solar-ORC plant currently runs at Ottana, Italy, albeit with some technical challenges basically due to inconsistent availability of solar irradiation. In order to upgrade the plant, a novel scheme had been proposed to install a biomass unit in parallel to the solar field, such that both LFC/TES and biomass furnace could directly and independently satisfy fractional thermal input requirement of the ORC. Being a retrofit system, existing design parameters of all the already operating units were imposed as equality constraints in this study, and the combustion excess air, as well as pinch point temperature difference of furnace heat exchangers that optimize the hybrid plant were investigated. Results showed that biomass mass flow rate of 0.133 kg/s and investment cost rate of 57 €/h are optimal for the studied biomass retrofit scheme. At this optimum point, excess air was obtained as 56%, furnace heater pinch point temperature difference as 28.8 °C and air pre-heater pinch point temperature difference as 38.5 °C. More generally, results showed that excess air value of less than 100%, furnace heater pinch point temperature difference of less than 80 °C, and air pre-heater pinch point temperature difference of less than 80 °C would optimize the studied biomass retrofit scheme.

Study of Aerosol Impact on the Solar Potential Available in Burkina Faso, West Africa

This paper is an assessment of aerosols impact on solar potential available in Burkina Faso in 2017. Three measurement stations were selected from the North to the South according to the climatic zones, with sites at Dori (14.035°N, 0.034°W) in the North, Ouagadougou (12.20°N, 1.40°W) in the Center and Gaoua (10.29°N, 3.25°W) in the Southwest, respectively. This study is based on in-situ measurements, satellite observations and a tropospheric standard model of the Streamer radiative transfer code of atmospheric particles. The results show a high availability of solar irradiation with average monthly values ranging between 4.46 kWh/m²/d and 6.82 kWh/m²/d. The most favorable periods with maximum radiation are observed in Spring in March and in Fall in October. Yet, the qualitative comparison between the evolution of aerosols and that of solar potential clearly shows aerosols capacity to influence the radiation at the crossing of the atmosphere. Thus, the aerosols maxima correspond to the solar potential minima. Moreover, a comparison between the day cycles of solar radiation and those of the simulation model shows a good accuracy of the Streamer code to estimate the solar flows at the surface in a standard atmosphere without clouds in Burkina Faso.However, a quantification of the aerosol impact by the Streamer code reveals a reduction in the normal direct flow compared to clear days defined by aerosol optical depth (AOD) less than 0.2 (AOD<0.2) of nearly 75.04% at the Dori site in the North, 57.33% at the Ouagadougou site in the Center and 40.89 % at the Gaoua site in the Southwest during polluted days corresponding to AOD higher than 0.8.This corresponds to an increase in the diffuse flow of 279.69 W/m², 246.05 W/m² and 226.09 W/m², respectively calculated on the same sites. In case of a mixed day (0.2 <AOD <0.8), this decrease in direct solar flow is estimated at 41.25%, 22.11% and 37.13% with an increasein the diffuse solar flux of 115.04 W/m², 150.43 W/m² and 79.58 W/m² at the sites of Dori, Ouagadougou and Gaoua, respectively.

Scheduling energy consumption for residential stand-alone photovoltaic systems

Among various renewable energy sources, solar energy is considered an effective solution to the shortage of energy in the future. A stand-alone photovoltaic (PV) system can be particularly impactful in an isolated area where access to the grid is limited or unavailable. Because solar energy generation primarily depends on the availability of solar irradiance over time, energy management is crucial, which in turn can also satisfy user comfort and system efficiency. In this paper, we propose an energy consumption scheduling model for a residential house with a stand-alone PV system and battery. We develop a mixed-integer optimization model that uses consumption patterns and appliance priority to schedule the use of appliances. We test our model under four scenarios based on region and season. The results demonstrate that the proposed model provides optimal schedules for operating the appliances. In addition, we conduct a sensitivity analysis on the PV array size and the battery capacity. We compare the optimized case with the non-optimized case.

The role of seasonal thermal energy storage in increasing renewable heating shares: A techno-economic analysis for a typical residential district

European renewable energy developments have so far focussed on electricity generation, with relatively modest progress in renewable heating. Partly this is due to the temporal mismatch between solar irradiation availability and residential heating demand profiles. Seasonal thermal energy storage (STES) has been proven in several pilot projects and is market ready, albeit not currently economical. This paper sets out to assess the potential contribution of STES to increasing the renewable heating fraction in residential buildings. An existing mixed integer linear program (MILP) is extended to consider STES and applied to optimize the energy supply system for a typical residential district with efficient new-build apartment buildings, in the context of five contrasting scenarios. Achieving 100% renewable heat supply requires significant capacities of seasonal storages and is associated with substantially (14%) higher cost than in the reference scenario. To achieve a 60% renewable heat supply fraction under today's framework conditions, the cost increase compared to the reference scenario is only marginal (1%). The results in three future scenarios reflecting possible conditions in 2030 demonstrate that even higher levels of renewable heat supply could soon become economical. Overall the recommendation is to aim for renewable heat supply levels of around 60–80% combined with demand side measures such as improved insulation. Further work should focus on more systematically exploring the relationship between the grid renewable electricity fraction, available solar collector area and the optimal renewable heat integration strategy.

Demand-Side Management of Air-Source Heat Pump and Photovoltaic Systems for Heating Applications in the Italian Context

Matching demand profile and solar irradiance availability is necessary to meet space heating and domestic hot water needs by means of an air-source heat pump and photovoltaic system in a single-family house. Demand-side management, with smart control of the water storage set-point, is a simple but effective technique. Several studies in the literature pursue demand-side matching and self-consumption goals through system adjustments based on the model predictive control. This study proposes a rule-based control strategy, based on instantaneous photovoltaic (PV) power production, with the purpose of enhancing the self-consumption. This strategy exploits the building’s thermal capacitance as a virtual battery, and the thermal storage capacity of the system by running the heat pump to its limit when PV surplus power is available, and by eventually using an electric heater in order to reach higher temperatures. Results of annual dynamic simulations of a building and its heating system show that the proposed rule-based control strategy is able to reduce significantly the energy exchanges between the system and the grid. Despite the enlarged renewable energy share, economic analysis points out the pursuit of the self-consumption goal may lead to a diminution of the economic advantage in the Italian context (Italian weather data and the electric power pricing scheme).

Optimization and design of a low-cost, village-scale, photovoltaic-powered, electrodialysis reversal desalination system for rural India

This paper presents the cost optimization of a photovoltaic-powered electrodialysis reversal (PV-EDR) system for village-scale applications in rural India based on current component costs and performance. A PV-EDR alternative was explored because it requires half the specific energy (and thus half the power system cost), and reduces water wastage from 60% to less than 10%, compared to small-scale reverse osmosis (RO) systems for groundwater salinity levels commonly found in India. Through co-optimization of the PV and EDR subsystems, the optimal system was predicted to cost $23,420 (42% less than a system designed using conventional engineering practice). A key to the cost reduction was flexible water production that accommodates daily changes in solar irradiance with overproduction on sunny days and water buffer storage tanks. A sensitivity analysis revealed that the capital cost of the total system is most sensitive to membrane area; reducing membrane cost by 87% would half the system capital cost. The optimization method presented here, as well as the cost saving strategies of time-variant operation and load matching with solar irradiance availability, provide design strategies that are relevant to other PV-EDR architectures and general off-grid desalination applications.