Energy Yield Losses Research Articles

Agri-Solar Water Pumping design, energy, and environmental analysis: A comprehensive study in Tropical Humid climate

Agrivoltaics is an innovative approach where solar energy, water, land and biodiversity are integrated into the same area to maximize resource utilization for sustainable development, also known as Agrivoltaism. The combination of solar water pumping and agri-solar has led to the development of a new generation of irrigation systems that are highly sustainable and efficient. Agri-solar water pumping can irrigate crops, feed livestock, clean solar modules, cool the PV system, generate energy, store water, and provide community drinking water. This paper addresses the basic design and capacity requirements of solar water pumping systems for irrigating a 0.5-hectare Agrivoltaics system in Kuala Lumpur. The SISIFO tool has been used to simulate the Agri-solar water pumping performance for tropical humid climatic conditions. The various parameters like site details, climate data, type of PV modules, DC pump -motor and converters are used as input data to evaluate the energy yield parameters (output energy in DC and AC form), hydraulic parameters (volume of water pumped), loss parameters (capture and system losses) and efficiency parameters (performance of the system). Lettuce was chosen as it is fast growing with good yield per hectare. Based on the result, a detailed analysis of the agrivoltaic lettuce plant is performed. A detailed analysis of the solar resource assessment, system design, Key performance indicators, loss analysis and environmental analysis of the Agri-solar water pumping has been carried out. Considering their specific climatic conditions, this can significantly assist policymakers in selecting the optimal solar pumping station for agrivoltaic plants. The importance of considering various factors when choosing a solar pumping station for agrivoltaics is also highlighted

Energy Yield Modeling of Perovskite–Silicon Tandem Photovoltaics: Degradation and Total Lifetime Energy Yield

This study investigates the impact of degradation in perovskite‐silicon tandem solar cells by means of energy yield (EY) modelling over the entire lifetime. First, we assess the impact on EY of degradation in the individual solar cell parameters of the perovskite top cell. Our analysis reveals that degradation in fill factor, due to a decline in perovskite top cell shunt resistance (RSh), has the most severe impact on the EY, emphasizing the imperative to rectify perovskite imperfections in thin film processing causing RSh decline. Second, we investigate implications of degradation in the perovskite top cell on the EY of current mismatched tandem solar cells. Third, we examine critical thresholds for the “acceptable degradation levels” in the perovskite top cell with regard to degradation in each solar cell parameter, assuming that the total loss in EY must be comparable to the degradation in state‐of‐the‐art silicon. Overall, our study highlights that degradation of the perovskite top cell needs to be assessed with care when extrapolating the impact on the lifetime EY of perovskite‐silicon tandem solar cells. The severity of degradation for different degradation mechanisms in a single junction perovskite solar cell cannot be translated one‐to‐one to tandem devices.

Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation

Blades leading edge erosion can significantly reduce annual energy production of wind turbines. Accurate estimates of the resulting blade performance impairment are paramount to predict the resulting energy losses and enable cost-informed decisions on optimal maintenance and operational strategies, maximizing energy production and reducing maintenance costs. Computational Fluid Dynamics (CFD) is a robust approach for predicting the performance losses due to LEE. However, the impact of the damage on blade aerodynamics varies depending on damage pattern, extent and location. Therefore, direct CFD simulation of a sufficiently general set of damaged blades is computationally not viable in industrial applications, since the energy loss assessment needs to be performed for hundreds of turbines at many times of the wind farm operation. To address this issue, previous studies showed how CFD can be used to train machine learning metamodels of the perfomance of damaged blade sections, enabling the definition of multi-fidelity energy loss prediction systems. This study presents improved metamodels, using validated CFD to generate training datasets that cover a more general and wider range of erosion patterns, from low-amplitude roughness to severe grooves. In order to provide the industry with additional erosion geometry-linked tools for estimating energy yield losses, and foster further research and development in this area, the developed meta-models have been made available online with unrestricted access.

Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades

Leading edge erosion of wind turbine blades is a major contributor to wind farm energy yield losses and maintenance costs. Presented is a multidisciplinary framework for predicting rain erosion lifetimes of wind turbine blades. Key aim is assessing the sensitivity of lifetime predictions to: modeling aspects (material erosion model, blade aerodynamics), input data and/or their preprocessing (joint frequency distribution of wind speed and droplet size based on synchronous site-specific measurements versus frequency distribution generated with partly site-agnostic modeling standards, wind speed records of nacelle anemometer or extrapolated at hub height from met masts), and environmental conditions (UV weathering). The analyses consider a Northwest England onshore site where a utility-scale turbine is operational, focus on a reference 5 MW turbine assumed operational at the site, and use a typical leading edge coating material. It is found that the largest variations in erosion lifetime predictions are due to material erosion model (based on rain erosion test data or fundamental material properties) and wind and rain model (measurement-based joint wind speed and droplet size distribution or standard-based modeled distribution). The use of joint wind and rain distribution also enables identifying wind/rain states with highest erosion potential, knowledge paramount to deploying erosion-safe turbine control.

Assessing the progression of wind turbine energy yield losses due to blade erosion by resolving damage geometries from lab tests and field observations

Assessing the progression of wind turbine energy yield losses due to blade erosion by resolving damage geometries from lab tests and field observations

High-fidelity modelling of a six-turbine tidal array in the Shetlands

Micro-siting tidal stream turbines in a confined seabed area requires a extensive understanding of the flow dynamics over the water column at turbine deployment locations so that operating conditions are assessed, wake effects can be estimated to infer the energy yield [1], or bathymetry effects can be quantified. Tidal currents have the advantage of being highly predictable and mostly bidirectional but the uneven bathymetry found at most of sites introduces a high variability to the flow conditions within relatively short distances. Considering future tidal turbine arrays will comprise dozens of devices, deploying ADCPs at each turbine position would be very expensive or very time consuming, outlining the need for accurate modelling tools to be used as digital twins in micro-siting. Shallow-water models are widely adopted in preliminary design of tidal arrays but fail to capture the three dimensional nature of the flow and predict deflected wakes whose streamwise length is also over-predicted [2]. Thus, eddy-resolving method are required to fully capture the turbulence from the free-stream flow, induced by turbines and from bathymetry. \\
 This study provides a real-project application of the state-of-the-art large-eddy simulation (LES) code DOFAS (Digital Offshore Farms Simulator) [3] to the six 100kW-turbine array deployed by NOVA Innovation Ltd. in the Shetlands, UK [4]. The bathymetry data has been obtained from EMODnet database with the velocity profiles set at the inlet condition of both ebb and flood tides imported from Macleod et al. (2019) [4]. The deployment site is characterised by steep slopes with a maximum depth of 45 m at the cross-section where turbines are located. The bathymetry has a downwards slope when the flow goes in the ebb tide direction whilst upstream during flood tide. The tidal rose indicated a slight deviation of about 20$^{\circ}$ between ebb and flood directions. The turbines have a diameter ($D$) of 9 m attached to a 10 m long hub whose diameter is 1 m. Three array configurations have been studied: (i) single row of three turbines, (ii) two rows of turbines spaced 8$D$, and (iii) two rows of turbines spaced 12$D$. The computational domain extends over 600 m by 300 m in the horizontal plane yielding 540 million cells, requiring 32,500 CPU hours to compute 30 min of physical time.\\
 Results show that bathymetry effects at this site play a larger role when designing the location of the secondary row of turbines compared to wake effects from upstream turbines. During the ebb tide, the increase in water depth reduces the wake recovery far downstream so that the array with 12$D$ row spacing has a lower performance than the 8$D$ one with approx. 30\% decrease in energy yield. Conversely, the uphill shape of the bathymetry during the flood enables a fast wake recovery so that the downstream row experiences almost no energy yield loss due to wakes.

Optimal Design of Multilayer Optical Color Filters for Building‐Integrated Photovoltaic (BIPV) Applications

Herein, the application of a comprehensive modeling framework that can help optimize the design of multilayered optical filters for coloring photovoltaic (PV) modules is presented based on crystalline silicon solar cells. To overcome technical issues related to the implementation of color filters (CFs) on PV modules, like glare and color instability, colorimetry metrics, such as the hue, chroma, luminance color space, and the quantitative concept of difference between two colors are extensively deployed. It is showcased in this work that designing colored modules with high hue and chroma stability is possible by using a front‐side texturing with edged geometry, like V‐shaped grooves and inverted pyramids, while obtaining colors with relatively high luminance values, indicating good brightness. Furthermore, it is argued that adapting the rear surface of the front glass with a random textured layout where the CF is applied can improve color and luminance stability without significant loss of chroma while eliminating glare. Finally, the models can be used to optimize the number of layers for a given CF, reducing unnecessary optical losses. Compared to a standard PV module, performance simulation of optimized, bright‐colored PV modules predicts relative energy yield losses ranging from 7% to 25%.

Torrefaction of Pine Using a Pilot-Scale Rotary Reactor: Experimentation, Kinetics, and Process Simulation Using Aspen Plus™

Biomass is an excellent sustainable carbon neutral energy source, however its use as a coal/petroleum coke substitute in thermal applications poses several challenges. Several inherent properties of biomass including higher heating value (HHV), bulk density, and its hydrophilic and fibrous nature, all contribute to challenges for it to be used as a solid fuel. Torrefaction or mild pyrolysis is a well-accepted thermal pretreatment technology that solves most of the above-mentioned challenges and results in a product with superior coal-like properties. Torrefaction involves the heating of biomass to moderate temperatures typically between 200 °C and 300 °C in a non-oxidizing atmosphere. This study focused on evaluating the influence of torrefaction operating temperature (204–304 °C) and residence time (10–40 min) on properties of pine. Tests were performed on a continuous 0.3 ton/day indirectly heated rotary reactor. The influence of torrefaction operational conditions on pine was evaluated in terms of the composition of torrefied solids, mass yield, energy yield, and HHV using a simulated model developed in Aspen Plus™ software. A kinetic model was established based on the experimental data generated. An increase in torrefaction severity (increasing temperature and residence time) resulted in an increase in carbon content, accompanied with a decrease in oxygen and hydrogen. Results from the simulated model suggest that the solid and energy yields decreased with an increase in temperature and residence time. Solid yield varied from 80% at 204 °C to 68% at 304 °C, and energy yield varied from 99% at 204 °C to 70% at 304 °C, respectively. On the other hand, HHV improved from 22.8 to 25.1 MJ/kg with an increase in temperature at 20 min residence time. Over the range of 10 to 40 min residence time at 260 °C, solid and energy yields varied from 77% to 59% and 79% to 63%, respectively; however the HHV increased by only 3%. Solid yield, energy yield, and HHV simulated data were within the 5% error margin when compared to the experimental data. Validation of the simulation parameters was achieved by the conformance of the experimental and simulation data obtained under the same testing conditions. These simulated parameters can be utilized to study other operating conditions fundamental for the commercialization of these processes. Desirable torrefaction temperature to achieve the highest solid fuel yield can be determined using the energy yield and mass loss data.

Probabilistic analysis of wind turbine performance degradation due to blade erosion accounting for uncertainty of damage geometry

Geometry alterations of wind turbine blades due to erosion reduce the blade aerodynamic performance, yielding turbine power and energy losses. This study proposes a novel probabilistic analysis framework combining computational fluid dynamics, probabilistic and deterministic uncertainty propagation, and high-performance computing to assess this performance degradation accounting for the unavoidable uncertainty on field records of blade erosion. This uncertainty presently prevents using erosion records for improving wind turbine maintenance planning, increasing energy yield, and thus further reducing the wind energy cost. The technology is demonstrated by quantifying the statistical moments of power and energy yield losses of an eroded utility-scale turbine at a North Sea offshore site and a southern European onshore site. The expectations of the offshore and onshore annual energy production losses are found to be 2 and 3% of the corresponding nominal values, respectively, with corresponding standard deviations of 0.1 and 0.15%. In the realistic scenario of erosion varying with high radial frequency, these low standard deviations result from partial compensation of the impact of mild and severe damages. These low standard deviations indicate that present uncertainty levels of erosion geometry records can be handled with uncertainty analysis in predictive maintenance for further reducing wind energy costs. With the frequent assumption of small or no radial variation of erosion, the standard deviation of the loss is misleadingly higher. For the first time, the study reports on the significant impact of turbulence intensity of the installation site on the turbine loss variability with the site wind characteristics.

Assessing the Progression of Wind Turbine Energy Yield Losses Due to Blade Erosion by Resolving Damage Geometries from Lab Tests and Field Observations

Assessing the Progression of Wind Turbine Energy Yield Losses Due to Blade Erosion by Resolving Damage Geometries from Lab Tests and Field Observations

Changes in sucrose metabolic enzymes to water stress in contrasting rice genotypes

Photosynthesis is the key process that controls metabolic movements in plants. Water stress reduces the rate of photosynthesis, leading to energy depletion and yield loss. Sucrose is the fundamental product of photosynthesis in plants, which acts as an important energy substrate and regulator of plant growth and developmental signals. In this study, two rice varieties, drought tolerant PTB7 (Parambuvattan) and drought susceptible PTB23 (Cheriya Aryan) were subjected to water deficit stress treatments to understand the changes in various physiological, biochemical mechanisms and sucrose metabolizing enzymes. Under water stress conditions, root biomass increased as compared to shoot biomass, which led to an increase in the root to shoot (R/S) ratio. Water stress enhanced the sucrose content in both leaves and roots of the rice plant, which may be due to the increased sucrose metabolism and transport under water stress conditions. Since then, there has been a notable increase in the activity of enzymes (α-amylase and β-amylase) and expression of genes such as sucrose transporter (SUC2) and sucrose synthase (OsSuSy) genes. In conclusion, the results showed that changes in sucrose distribution, metabolism, and transport in plants under water stress conditions contribute to tolerance in rice to water stress conditions.

Lithium-Sulfur Batteries with Robust Cycle Life For Space Applications

While lithium-ion (Li-ion) batteries offer tremendous performance advantages over their battery predecessors (e.g., nickel-cadmium, lead-acid), they are approaching an asymptotic limit in specific energy (~250 Wh/kg at cell level) and do not adequately address next generation space platform requirements (e.g., by NASA [1]). As a result, there has been intense research and development (R&D) on higher specific energy batteries that have been coined beyond Li-ion. Rechargeable lithium-sulfur (Li-S) battery is a particularly attractive beyond Li-ion battery chemistry because it offers a high theoretical specific energy of 2500 Wh/kg (at materials level) [2] and a demonstrated practical specific energy >300 Wh/kg (at cell level) [3], making it a promising battery chemistry for future space applications that demand higher specific energy in batteries.Currently, no commercial Li-S battery exists due to several significant technical challenges that have thus far prevented the realization of the Li-S chemistry’s tremendous performance potential. These technical challenges include: (i) Low practical energy yield and significant capacity loss with cycling, due to lithium polysulfide formation/dissolution/migration during discharge [4]. (ii) High self-discharge rates and low Coulombic efficiency, due to redox shuttle reactions of the dissolved polysulfides. (iii) Safety concerns, mainly due to Li dendrite growth from the unprotected Li anodes [5].We will present our efforts in the development of a high energy density, long cycle life, long shelf life and enhanced reliability/safety Li-S battery technology, using a holistic and comprehensive approach to overcome technical challenges that hinder commercialization of Li-S batteries. In particular, we will demonstrate impact of various battery testing parameters, such as depth-of-discharge, charge/discharge current C-rate, on Li-S cell cycle performance and shelf life.Our investigation results showed that, using material engineered (active and inactive) cell components, the resultant Li-S cells demonstrated excellent cycle life performance, while achieving high specific capacities and energies when cycled under optimized battery testing schemes. The advanced Li-S battery technology has shown a great promise to achieve unprecedented specific energy/energy density and long-term cycle/shelf life stability for future space applications. References 2020 NASA Technology Taxonomy, https://www.nasa.gov/offices/oct/taxonomy/index.htmlZhang, Sheng S., Power Sources, 231, 153-162, 2013.Weibing Xing, # A02-0364, 238th Electrochemical Society Meeting (PRiME), Honolulu, HI, October 4-9, 2020.Besenhard JO. Handbook of Battery Materials. Wiley: New York; 1998.James R. Akridge, Battery Power Products & Technology, October 2001. Acknowledgement We would like to acknowledge financial support from NASA Glenn Research Center for this R&D work.

Analysis of chemical, morphological, energy efficiency, and fuel properties of bamboo torrefaction

This study evaluates the outcome of torrefaction as a thermochemical pretreatment to biomass conversion on the properties of Bambusa vulgaris (Bamboo) under nitrogen-inert environment at atmospheric pressure. The dark solid torrefied products were produced by processing for 20, 30 and 40 min under the temperatures of 240, 260, 280 and 300 °C. The optimal torrefaction conditions are obtained at 300 °C for 40 min of residence time. The torrefaction at higher temperature results in severe loss of mass yield about 11.64% to 19.13% over its energy yield loss ranging from 6.88% to 14.81%, while the energy density increases upto 1.18 times. The bulk density decreases marginally to 0.24 g/cm3 under optimum torrefaction conditions. The consistent weight-loss structure enhances the higher heating value by about 18.62% from 19.80 MJ kg−1 to 23.25 MJ/kg tended to that of sub-bituminous coal. Hydrophobicity of torrefied bamboo is observed approximately 56.75% low moisture absorption. Torrefied bamboo shows upgraded proximate and elemental composition in contrast to raw bamboo. Finally, torrefaction benefitted the result more efficiently in combustion reactivity, thermal performance, porosity, and grindability of the bamboo samples through thermogravimetric analysis, differential thermal analysis, and scanning electron microscope analysis respectively in a comparable manner with untreated bamboo.

Machine learning-enabled prediction of wind turbine energy yield losses due to general blade leading edge erosion

Blade leading edge erosion is acknowledged to significantly reduce the energy yield of wind turbines. The problem is particularly severe for offshore installations, due to faster erosion progression boosted by harsh environmental conditions. This study presents and demonstrates an experimentally validated simulation-based technology for rapidly and accurately estimating wind turbine energy yield losses due to general leading edge erosion. The technology combines the predictive accuracy of two- and three-dimensional Navier–Stokes computational fluid dynamics with the runtime reductions enabled by artificial neural networks and wind turbine engineering codes using the blade element momentum theory. The main demonstration is based on the assessment of the annual energy yield of the National Renewable Energy Laboratory 5 MW reference turbine affected by leading edge erosion damage of increasing severity, considering damages based on available laser scans and previous leading edge erosion analysis. Results also include sensitivity studies of the energy loss to the wind characteristics of the installation site. It is found that the annual energy loss varies between about 0.3 and 4%, depending on the damage severity and the site wind characteristics. The study also illustrates the necessity of resolving the geometry of eroded leading edges rather than accounting for the effects of erosion with surrogate models, since, after an initial increase of distributed surface roughness, erosion yields leading edge geometry alterations causing aerodynamic losses exceeding those due to the loss of boundary layer laminarity consequent to roughness-induced transition. The presented technology enables estimating in a few minutes the amount of energy lost to erosion for many-turbine wind farms, and offers a key tool for predictive maintenance.

Experimentally validated three‐dimensional computational aerodynamics of wind turbine blade sections featuring leading edge erosion cavities

AbstractWind turbine blade leading edge erosion reduces the lift and increases the drag of the blade airfoils. This occurrence, in turn, reduces turbine power and energy yield. This study focuses on the aerodynamic analysis of large and sparse erosion cavities, observed in intermediate to advanced erosion stages, whose size and surface pattern do not lend themselves to experimental and numerical analysis by means of distributed roughness models alone. Making use of three‐dimensional Navier‐Stokes computational fluid dynamics enhanced by laminar‐to‐turbulent transition modeling, and geometrically resolving individual erosion cavities, the study validates this simulation‐based approach for predicting the aerodynamics and performance loss of blade sections featuring the aforementioned erosion cavities against available experimental data. It is found that the considered cavities can trigger transition, indicating the necessity of both resolving their geometry in the simulations and also modeling distributed surface roughness, of typically lower level, as this latter affects the properties of boundary layers and, if sufficiently high, may trigger transition over the entire spanwise length affected. The energy yield loss of a utility‐scale turbine due to the considered erosion pattern is found to be between 2.1% and 2.6% using measured and computed force data of the nominal and eroded outboard blade airfoil. A parametric analysis of the cavity geometry suggests that the geometry of the cavity edge has a much larger impact on aerodynamic performance than the cavity depth.

High-intensity illumination treatments against LeTID – Intensity and temperature dependence of stability and inline feasibility

We study the mitigation of light- and elevated temperature-induced degradation (LeTID) with high-intensity illumination treatments, placing special emphasis on inline feasibility. After the treatments, we investigate the stability upon degradation conditions close to the recently suggested standard, which allows estimating the LeTID behavior during the operating lifetime of solar modules in the field. Subsequently, we map the stability at different treatment intensities and temperatures achievable with an air-cooled tool. We show that, when applying short treatment times, the stability improves with increasing treatment intensity and deteriorates steeply with rising temperature above an optimum region around 250 °C. However, these intensity- and temperature-dependent differences largely vanish when increasing the treatment time sufficiently. We also investigate the significance of darkness/illumination during the cooling ramp from the treatment temperature in view of the LeTID stability. We discuss our results based on suggested defect models of LeTID, and provide hypotheses of the origin of the instabilities observed at the high treatment temperatures. After identifying optimal treatments, we demonstrate that the energy yield loss due to LeTID reduces by over 60% after an inline-feasible process consisting of only 30 s of high-intensity illumination, combined with cooling of the samples from the process temperature under a lower-intensity illumination.

Financial and Technical Analyses of Solar Boats as A Means of Sustainable Transportation

Abstract Because of the effects of climate change, a sustainable transportation system based on renewable energy resources needs to be developed to improve the quality of life. In this study, three sustainable transportation designs and an on-grid power plant design using photovoltaic (PV) panels were analyzed for their feasibility as an alternative to diesel-powered tourist boats. Various financial and technical aspects were considered, such as the local irradiation, energy yield, and system energy loss. As a case study, a solar-aided boat was considered, where an off-grid rooftop PV system with 9.8 kWh batteries was installed to meet the energy requirements for internal services and reduce diesel usage. The solar-aided boat was demonstrated to be an economical solution, where the PV system reduced the diesel consumption of the boat by 15% and produced an annual energy output of 5540 kWh. For fully electric solar boats, simulation results showed that a 60 kWh battery system covers the initial investment within 9 years, while a solar boat with 120 kWh a battery system covers it in 13 years. A 300 kW on-grid PV plant was analyzed for its ability to meet the energy demands of an entire tourist boat fleet, and the plant was estimated to reduce CO2 emissions by 330 tons each year. These findings show that various off-grid rooftop PV systems can be adapted for sustainable transportation while reducing the operating costs of the boat. This study also promotes the transition of boats to cleaner and more sustainable energy sources.

Transparent Electrodynamic Screen (EDS) Films - Industrial Production and Lamination onto PV Modules and CSP Mirrors for Self Cleaning Function

Electrodynamic screens (EDS) are transparent dielectric films, consisting of embedded, interdigitated parallel conducting electrodes that can be integrated onto the optical surface of a photovoltaic (PV) module or concentrated solar power (CSP) mirror for their self-cleaning function to mitigate the energy yield losses caused by soiling. The EDS film removes dust particles using electrostatic forces thus eliminating the need for water or robotic devices to clean the solar devices. In this paper we report the methods experimented to produce EDS film stacks integrated onto individual PV modules (33 cm × 28 cm) for solar field applications using an industrial vacuum lamination process for the purpose of outdoor testing. Steps taken to optimize the lamination process to provide high optical transparency, resistance against moisture ingress and to withstand dust abrasion are described. The experiments performed to arrive at the optimal curing temperature, curing time, and vacuum pressure maintenance for the lamination process are elaborated. Details on the construction, functionality and operation of the outdoor testing units are provided. Measurements of the optical transmission efficiency (TE) and output power restoration (OPR) of the EDS film stack laminated onto PV modules are presented along with a model for full-scale lamination with an aim for advancing the EDS film technology as a commercially available product.

Impact of field design and location on the techno-economic performance of fixed-tilt and single-axis tracked bifacial photovoltaic power plants

In the design phase of the photovoltaic field for a bifacial photovoltaic power plant (B-PV), the influence of installation parameters on both the energetic and economic performance must be considered, which makes determining the cost-optimal field design a challenge. Although some studies have dealt with this topic, many questions remain unanswered.Therefore, this work investigated the site-dependent impact of the installation parameters row spacing, module elevation, tilt angle and soil reflectivity of a fixed-tilt and a single-axis tracked B-PV with an east–west and north south-axis on the energy yield, the levelized cost of electricity (LCOE) and the bifacial gain. Based on the results, the magnitude of the influence of an installation parameter on the energy yield and LCOE could be quantified for all three system designs. However, three findings are particularly noteworthy: 1. in the case of the fixed-tilt design, the relative energy yield gain caused by a larger row spacing increases with increasing latitude; 2. depending on PV field’s configuration, soil brightening measures can significantly increase the energy yield of all three system designs, practically independent of location, and at the same time reduce the LCOE; 3. the choice of a too high module elevation can lead to small yield losses. Finally, the simulation model used was validated with the Swiss BIFOROT test array.In summary, it can be said that the complex interactions of installation parameters must be thoroughly investigated in order to avoid energy yield losses and unnecessarily high LCOE.

Tuning electricity generation throughout the year with PV module technology

Abstract Currently, photovoltaic (PV) installations target a maximization of annual energy yield. However, as the grid penetration of PV is increasing, PV electricity generation will need to match better with local load profiles. Especially the seasonal variabilities remain challenging. While wind and PV tend to have complementary seasonal variability, wind turbine installation faces limitations especially in densely populated areas. In this paper, we discuss how this challenge may be addressed with climate- and consumption-specific PV module technology. In particular, we demonstrate how the temperature coefficient of a PV system can impact the energy yield throughout the year. In colder climates, higher temperature coefficients allow for a better energy balance, favoring production in colder seasons without a significant reduction of yearly energy yield. Simulations for locations at high latitude, and colder climates, indicate that higher temperature coefficients and improved low-light behavior not only enable a higher energy yield in cold seasons, but also negligible losses in the overall yearly energy yield compared to lower temperature coefficients and slightly better low-light behavior. Simulations show that these results can be obtained using commercial PV modules. More broadly, they indicate how PV module technology may be optimized depending on the location and climate.