Simulation Of Energy Production Research Articles

Evaluation of the Duration of Albedo Measurement Campaigns

Bifacial PV modules are increasingly used in commercial solar PV projects. With the use of the solar energy available at the module’s rear surface, the correct estimation of the albedo during the pre-construction phase of commercial projects becomes more important. The intention of the study is to determine the impact of the duration of a short-term albedo measurement campaign to reduce the uncertainty with respect to satellite albedo, thus providing a ‘beneficial campaign’. Albedo measurements from seven sites in the USA have been used to estimate the impact of 1-day and 7-day measurements (short-term measurements) on the simulated annual electrical energy production. Simulations based on monthly albedo data obtained from a recognised satellite provider have been compared with simulations where the albedo has been corrected based on short-term measurements. The study found that a 1-day campaign is often not beneficial, causing an increase in uncertainty with respect to satellite albedo. Measurement campaigns in winter do not generally reduce the error of the annual electrical energy production simulation, however, a 7-day campaign undertaken in summer appears to often reduce the uncertainty. It should be noted that the climate conditions, ground vegetation and measurement setup of the analysed seven sites in the USA may not be representative for other sites in the rest of the world.

Research on Maintenance Strategies for Different Transmission Sections to Improve the Consumption Rate Based on a Renewable Energy Production Simulation

Renewable energy consumption is one of the most important factors in meeting the goal of “30 and 60” in China. However, the maintenance of the transmission section affects the amount of generation transfer, further affecting the consumption of renewable energy. Hence, in this study, a time-series renewable energy production simulation (REPS) is proposed in order to accurately predict the power generation in a simulated situation. According to the results of the REPS, the sensitivity of the different sections’ maintenance can be calculated and determined. The appropriate maintenance strategies can be selected for different situations by comparing the consumption rate; as an example, we conducted a case study. The results show that the quota in the transmission section has higher sensitivity; a larger quota indicates a greater sensitivity to the consumption rate. The results also show that a larger quota is more suitable for maintenance in February or November, since the consumption rate is higher regardless of if it is in a single-transmission-section maintenance strategy or in a two-section simultaneous maintenance strategy.

An Empirical Correction Model for Remote Sensing Data of Global Horizontal Irradiance in High-Cloudiness-Index Locations

Facing the energy transition, solar energy, whether thermal or electric, is currently one of the most viable alternatives, due to its technological maturity and its ease of operation and maintenance compared to other renewable energies. However, before its implementation, it is necessary to assess its potential. Remote sensing represents one of the low-cost solutions for solar energy assessment. Nevertheless, cloud cover is a main problem when validating the data. This study identifies satellite GHI profiles that cannot be used in energy production simulation. The validation is performed using parametric and non-parametric statistical tests. From the profile identified as invalid for simulation purposes, a site-adaptation methodology is proposed based on statistical learning using the machine learning algorithms “Best subset selection” and “Forward Stepwise Selection”. Linear and non-linear heuristic models are also proposed. The final AS7 model is selected through RMSE, MBE and adjusted R2 indicators and is valid for any sky condition. The results show an increase in R2 from 0.607 to 0.876.

An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

AbstractFracture networks are abundant in subsurface applications (e.g., geothermal energy production, CO2 sequestration). Fractured reservoirs often have a very complex structure, making modeling flow and transport in such networks slow and unstable. Consequently, this limits our ability to perform uncertainty quantification and increases development costs and environmental risks. This study provides an advanced methodology for simulation based on Discrete Fracture Model approach. The preprocessing framework results in a fully conformal, uniformly distributed grid for realistic 2D fracture networks at a required level of precision. The simplified geometry and topology of the resulting network are compared with input (i.e., unchanged) data to evaluate the preprocessing influence. The resulting mesh‐related parameters, such as volume distributions and orthogonality of control volume connections, are analyzed. Furthermore, changes in fluid‐flow response related to preprocessing are evaluated using a high‐enthalpy two‐phase flow geothermal simulator. The simplified topology directly improves meshing results and, consequently, the accuracy and efficiency of numerical simulation. The main novelty of this work is the introduction of an automatic preprocessing framework allowing us to simplify the fracture network down to required level of complexity and addition of a fracture aperture correction capable of handling heterogeneous aperture distributions, low connectivity fracture networks, and sealing fractures. The graph‐based framework is fully open‐source and explicitly resolves small‐angle intersections within the fracture network. A rigorous analysis of changes in the static and dynamic impact of the preprocessing algorithm demonstrates that explicit fracture representation can be computationally efficient, enabling their use in large‐scale uncertainty quantification studies.

Validation of wind resource and energy production simulations for small wind turbines in the United States

Abstract. Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, MyWindTurbine.com, and Global Wind Atlas 3 (GWA3), which are seen to overestimate actual annual capacity factors by 2.5, 4.2, 11.5, and 7.3 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produces more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

Performance Analysis of Crystalline Silicon and CIGS Photovoltaic Modules in Outdoor Measurement

Abstract The outdoor measurements (during two months experiment) of photovoltaic silicon and CIGS modules as well as simulation of energy production during the period experiment are presented in this paper. This paper offer comparison of construction and electrical characteristics of multicrystalline silicon based modules and CIGS based modules. The measuring system for PV modules efficiency research is shown. The nominal power of installed modules is 250 W for m-Si and 280 W for CIGS modules. The energy production in outdoor conditions at direct current side and alternating current side of each photovoltaic panel was measured. Each PV panel was also equipped with temperature sensor for screening panel temperature. The photovoltaic panels were connected to the electrical network with micro inverters. To determine the influence of irradiance at sunshine on power conversion efficiency of PV panels, the pyranometer was installed in the plane of the modules. Measurement of the instantaneous power and irradiance gave the information about the efficiency of a particular photovoltaic panels. In the paper all data from research installation were analysed to present the influence of solar cell technology on the power conversion efficiency. The results of energy production show that m-Si module produced more energy from square meter (30.9 kWh/m2) than CIGS module (28.0 kWh/m2). Thin film module shows the higher production per kWp than multicrystalline module: 217.3 kWh/kWp for CIGS and 201.9 kWh/kWp for m-Si. The energy production simulation (made by PV SOL software and outdoor measurements test are in the good agreement. Temperature power coefficient for the CIGS module is twice lower than for the multicrystalline silicon module: 0.56%/°C and 0.35%/°C for m-Si and CIGS modules, respectively. The obtained results revealed strong influence of irradiance and temperature on energy production by PV panels. Performed studies have a large field of potential application and could improve designing process of PV installation.

Application of Stochastic Methods to Double Cyclostationary Processes for Hourly Wind Speed Simulation

In this paper, we present a methodology to analyze processes of double cyclostationarity (e.g. daily and seasonal). This method preserves the marginal characteristics as well as the dependence structure of a process (through the use of climacogram). It consists of a normalization scheme with two periodicities. Furthermore, we apply it to a meteorological station in Greece and construct a stochastic model capable of preserving the Hurst-Kolmogorov behaviour. Finally, we produce synthetic time-series (based on aggregated Markovian processes) for the purpose of wind speed and energy production simulation (based on a proposed industrial wind turbine).

Simulation of Energy Production in Grid-Connected Photovoltaic Systems From Measured and Calculated Data From Clear-Sky Radiation Model

This paper presents a comparison of the energy production in grid-connected photovoltaic systems (GCPPS) from measured and calculated radiation data. The Linke turbidity (TL) factor for the region of Porto Alegre, Brazil, was extracted considering the data of direct solar radiation from the typical meteorological year (TMY). The average annual turbidity value obtained of 4.03 agrees with the wet climate of the region which presents only 17.26% of clear-sky days. There was a difference of 27.5% in the results of the produced energy, which drops to 6.5% when compared with only sunny days in the region, suggesting that the model in the current configuration for this type of estimate is barely adequate.

Sketch of Renewable Energy Production Simulation Platform

Renewable Energy Production Simulation Platform (REPS) is developed by China Electric Power Research Institute (CEPRI) to simulate the operation of renewable energy in the power system. REPS takes into account the characteristics of China’s electric power system, it can assess the accommodation of renewable energy power and simulate the impact of different renewable energy capacity on the operation of power system. Assessment model and calculation process of REPS V1.3 is introduced in this article, and annual consumptive capacity in one provincial power grid of China is evaluated with the platform. REPS is of great guiding significance to electrical source planning. With the sustained and rapid growth of renewable energy in China, power system will be more and more dependent on REPS.

Simulation of Energy Production by Bifacial Modules with Revision of Ground Reflection

Bifacial solar modules are becoming increasingly more attractive stimulated by the development of new solar cell structures enabling to capture solar insolation on both front and rear surfaces. The possibilities to be installed in the conventional south facing orientation or even vertically are further advantages. Although the potential of bifacial modules have been already shown in specific time intervals and for various ground albedos there is a lack in simulation studies up to now. In this study, we simulated the annual energy yield (AEY) of south facing bifacial modules using a rigorous calculation method of the ground reflected radiation reaching the rear module surface. The necessary tilt angle optimization is done incorporating the influence of module elevation and considering the inherent albedo coefficient. These simulations are able to reproduce measurement observations and show that at optimum tilt angles produced annual energy can be increased by 30% compared to a standard module simply by positioning modules two meters above ground instead of a close to ground installation. Furthermore, a linear relationship between albedo coefficient and AEY is demonstrated.

Steady state simulation of energy production from biomass by molten carbonate fuel cells

This paper presents an integrated approach to the steady state simulation of biomass gasification, fuel cells and power generation processes. Attention is devoted to molten carbonate fuel cells (MCFC) due to the relative low cost, simpler construction and flexibility in the use of fuel. A steady state model simulating a global MCFC power plant based on real plants data is described and the simulations are selected according to real operating conditions. The software developed allows to study ‘ìn silico’ the effect of variations of the process conditions as well as modification of the input fuel, thus providing a useful tool for supporting technical decisions and feasibility study on the use of fuel cells in developing countries. The paper reports results of computer simulation focusing on macroscopic quantities of interest such as stack efficiency, global process electrical efficiency, cogenerative efficiency. The computer simulation is applied to a feasibility study of a MCFC coupled with a biomass gasification module focusing on the energy consumption of the process and reporting comparison of the energy efficiency for three kinds of biomass.

Modeling and simulation of lactic acid fermentation with inhibition effects of lactic acid and glucose

An unstructured mathematical model for lactic acid fermentation was developed. This model was able to predict the inhibition effects of lactic acid and glucose and was confirmed to be valid with various initial concentrations of lactic acid and glucose. Simulation of energy production was made using this mathematical model, and the relationship between the kinetics of energy metabolism and lactic acid production was also analyzed.

Correction to "An Investigation of Two Methods for the Probabilistic Energy Production Simulation"

Correction to "An Investigation of Two Methods for the Probabilistic Energy Production Simulation"

Correction to "An Investigation of Two Methods for the Probabilistic Energy Production Simulation"

Correction to "An Investigation of Two Methods for the Probabilistic Energy Production Simulation"

An Investigation of Two Methods for the Probabilistic Energy Production Simulation

An Investigation of Two Methods for the Probabilistic Energy Production Simulation

An Investigation of Two Methods for the Probabilistic Energy Production Simulation

Two methods for the calculation of expected energy generation have been proposed. These methods differ from the Baleariaux-Booth probabilistic simulation in that the concept of unserved demand is used. The PDF of hourly loads serves as the starting statistic. In one of the proposed methods, this has been approximated by multiple normal densities. The proposed methods were found to be computationally mere efficient than any of the existing methods including those presently developed ones using moments and cumulants. In addition, the accuracy of one of the new methods was found to be superior to the conventional methods using moments and cumulants.