A key aspect for achieving a high-accuracy Photovoltaic (PV) power simulation, and reliable digital twins, is a detailed description of the PV system itself. However, such information is not always accurate, complete, or even available. This work presents a novel approach to learn features of unknown PV systems or subsystems using genetic algorithm optimization. Based on measured PV power, this approach learns and optimizes seven PV system parameters: nominal power, tilt and azimuth angles, albedo, irradiance and temperature dependency, and the ratio of nominal module to nominal inverter power (DC/AC ratio). By optimizing these parameters, we create a digital twin that accurately reflects the actual properties and behaviors of the unknown PV systems or subsystems. To develop this approach, on-site measured power, ambient temperature, and satellite-derived irradiance of a PV system located in south-west Germany are used. The approach proposed here achieves a mean bias error of about 10%... [more]

Mechanical properties of rock masses are dominated by the nonlinear response of joints and their arrangement. In this paper, combined influences of joint spacing (s) and joint inclination angle (β) on mechanical behavior of rock mass models with large open joints under uniaxial compression were investigated by PFC modeling. With a large amount of local measurement circles placed along the pre-defined measurement lines (ML), stresses and joint response parameters at different scales (the measurement circles, the MLs and the whole specimen) were defined and calculated. It was found that macroscopic behaviors of the jointed specimens, such as four types of deformation behaviors, four failure modes, strength, deformability modulus and ductility index, are dominated by nonlinear response of the joint system, especially the interaction between the joints and rock bridges. The joints may experience three stages, i.e., starting to close, closed and opening again. On the joint plane, the peak s... [more]

This paper presents an agent-based model (ABM) for residential end-users, which is part of a larger, interdisciplinary co-simulation framework that helps to investigate the performance of future power distribution grids (i.e., smart grid scenarios). Different modes of governance (strong, soft and self-organization) as well as end-users’ heterogeneous behavior represent key influential factors. Feedback was implemented as a measure to foster grid-beneficial behavior, which encompasses a range of monetary and non-monetary incentives (e.g., via social comparison). The model of frame selection (MFS) serves as theoretical background for modelling end-users’ decision-making. Additionally, we conducted an online survey to ground the end-user sub-model on empirical data. Despite these empirical and theoretical foundations, the model presented should be viewed as a conceptual framework, which requires further data collection. Using an example scenario, representing a lowly populated residential... [more]

Modeling flow and transport in fractured porous media has been a topic of intensive research for a number of energy- and environment-related industries. The presence of multiscale fractures makes it an extremely challenging task to resolve accurately and efficiently the flow dynamics at both the local and global scales. To tackle this challenge, we developed a computational workflow that adopts a two-level hierarchical strategy based on fracture length partitioning. This was achieved by specifying a partition length to split the discrete fracture network (DFN) into small-scale fractures and large-scale fractures. Flow-based numerical upscaling was then employed to homogenize the small-scale fractures and the porous matrix into an equivalent/effective single medium, whereas the large-scale fractures were modeled explicitly. As the effective medium properties can be fully tensorial, the developed hierarchical framework constructed the discrete systems for the explicit fracture−matrix sub... [more]

Digital rock physics is an often-mentioned approach to better understand and model transport processes occurring in tight nanoporous media including the organic and inorganic matrix of shale. Workflows integrating nanometer-scale image data and pore-scale simulations are relatively undeveloped, however. In this paper, a workflow is demonstrated progressing from sample acquisition and preparation, to image acquisition by Scanning Transmission Electron Microscopy (STEM) tomography, to volumetric reconstruction to pore-space discretization to numerical simulation of pore-scale transport. Key aspects of the workflow include (i) STEM tomography in high angle annular dark field (HAADF) mode to image three-dimensional pore networks in µm-sized samples with nanometer resolution and (ii) lattice Boltzmann method (LBM) simulations to describe gas flow in slip, transitional, and Knudsen diffusion regimes. It is shown that STEM tomography with nanoscale resolution yields excellent representation o... [more]

Southeast Asian region is fast growing in terms of economy with rapid population growth, high energy consumption, and pollution. Understanding these linkages are crucial to guidance of appropriate policy. This study aims to examine the causal relationship between energy consumption with economic growth and CO2 emissions of the four selected Asian countries, namely Indonesia, Malaysia, Philippines, and Thailand between the years 1971−2017 using Johansen cointegration method combined with Granger causality model. The results found the evidence of cointegration in all countries implying a long-run relationship among energy consumption, economy and pollution exists. The causality main results show the evidence of unidirectional causality running from economic growth to energy consumption in Indonesia, Malaysia, and Thailand, while the opposite direction was found in Philippines. The results of Indonesia, Malaysia, and Thailand support “conservative hypothesis” suggesting that energy conser... [more]

This paper deals with in loop design of coupling elements of the wireless charging systems (WChS). The in-loop design is created as a script/User Interface (UI) in MATLAB environment, which is based on finite element models of WChS. Main aim of developed tool is to easily identify the optimal geometrical parameters of the coupling coils. The optimization of the coil’s geometrical and electrical parameters is specified by an algorithm, which is based on definition for transfer of required amount of power and on geometrical restrictions of the target application. The second part of the proposed script/UI is used for user guided design of the electromagnetic shielding. It enables to optimize the shielding parameters in order to reach the limits defined by international standards for safety levels with respect to human exposure. Proposed design methodology together with user interface have been verified though experimental validation. For this purpose, construction of WChS was realized bas... [more]

The simulation of electronic control function failure has been utilized broadly as an evaluation method when determining the Automotive Safety Integrity Level (ASIL). The driver model is quite critical in the ASIL evaluation simulation. A new driver model that can consider drivers of different driving skills is proposed in this paper. It can simulate the overall performance of different drivers driving vehicles by adjusting parameters, with which the impact of a certain electronic control function failure and the ASIL are evaluated. This paper has taken the function failure of regenerative braking as the simulation object in the double-lane-change driving scenario to simulate typical driving conditions with the designed driver model, and then has obtained the ASIL of regenerative braking function, which is applied to a BAIC new energy vehicle development project.

The most important thing to operate a power system is that the power supply should be close to the power demand. In order to predict the amount of electric power transaction (EPT), it is important to choose and decide the variable and its starting date. In this paper, variables that could be acquired one the starting day of prediction were chosen. This paper designated date, temperature and special day as variables to predict the amount of EPT of the Korea Electric Power company. This paper also used temperature data from a year ago to predict the next year. To do this, we proposed single deep learning algorithms and hybrid deep learning algorithms. The former included multi-layer perceptron (MLP), convolution neural network (CNN), long short-term memory (LSTM), gated recurrent unit (GRU), support vector machine regression (SVR), and adaptive network-based fuzzy inference system (ANFIS). The latter included LSTM + CNN and CNN + LSTM. We then confirmed the improvement of accuracy for pr... [more]

On the basis of a generalized interdisciplinary method that consists of a modification of Hamilton−Ostrogradski principle by expanding the Lagrange function with two components that address the functions of dissipation energy and the energy of external conservative forces, a mathematical model is presented of an electromechanical system that consists of the force section of a magneto-levitation non-contact maglev suspension in a prototype traction vehicle. The assumption that magnetic potential hole, generated naturally by means of cryogenic equipment, is present in the levitation suspension, serving to develop the model system. Contrary to other types of magnetic cushion train suspensions, for instance, maglev−Shanghai or Japan−maglev, this suspension does not need a complicated control system, and levitation is possible starting from zero train velocity. As high-temperature superconductivity can be generated, the analysis of levitation systems, including the effect of magnetic potent... [more]

The marine elastomeric bearing consists of an elastomer and several reinforcing inserted plates. Unlike land bearings that are to absorb high-frequency vibration during earthquakes, offshore elastomeric bearings are to support topside-module weight while efficiently absorbing wave-induced hull motions. The bearing is to receive three loads: compression, shear, and bending, and providing sufficient stiffness to resist the loads by inserting an adequate number of reinforcing plates is a major design issue for marine bearings. The stiffness of elastomeric bearings is largely influenced by the ratio of height to the area of the bearing and the number of laminated reinforcing plates. In this study, for the given size of the elastomeric bearing, the effect of the number of reinforcing plates on its compression, shear, and bending stiffness is investigated by using ANSYS Mechanical APDL, a commercial structural FE (finite element) analysis program. First, full analysis is done for the compres... [more]

In the present study, we perform numerical simulations considering various stable atmospheric conditions for a small-scale simple topography. Based on the obtained simulation results, we visualize the flow field and discuss drastic changes in the flow patterns. A flow pattern similar to the potential flow suddenly appears around an isolated hill as the stability increases, regardless of the inclination angle of the hill. We show that a critical Richardson number clearly exists. Furthermore, the effect of stable stratification on the evaluation of power generation is shown for typical complex terrain. We evaluate the capacity factor (%) of a 2 MW large wind turbine based on one-year virtual mast data and consider the effect of stable stratification. It is shown, in the case of stable stratification, that the capacity factor is 2.775 times greater than that under neutral stratification.

Many types of dense suspensions are complex materials exhibiting both solid-like and fluid-like behavior. These suspensions are usually considered to behave as non-Newtonian fluids and the rheological characteristics such as yield stress, thixotropy and shear-thinning/thickening can have significant impact on the flow and the engineering applications of these materials. Therefore, it is important to understand the rheological features of these fluids. In this paper, we study the flow of a nonlinear fluid which exhibits yield stress and shear-thinning effects. The geometries of interests are a straight channel, a channel with a crevice and a pipe with a contraction; we assume the fluid behaves as a Herschel-Bulkley fluid. The numerical simulations indicate that for flows with low Reynolds number and high Bingham number an unyielded plug may form in the center of the channel. In the case of a channel with a crevice, the fluid in the deep portion of the crevice is at an extremely high lev... [more]

Thermal energy storage (TES) technologies are becoming vitally important due to intermittency of renewable energy sources in solar applications. Since high energy density is an important parameter in TES systems, latent heat thermal energy storage (LHTES) system is a common way to store thermal energy. Though there are a great number of experimental studies in the field of LHTES systems, utilizing computational codes can yield relatively quick analyses with relatively small expense. In this study, a numerical investigation of a LHTES system has been studied using ANSYS FLUENT. Results are validated with experiments, using hydroquinone as a phase-change material (PCM), which is external to Therminol VP-1 as a heat transfer fluid (HTF) contained in pipes. Energy efficiency and entropy generation are investigated for different tube/pipe geometries with a constant PCM volume. HTF inlet temperature and flow rate impacts on the thermodynamic efficiencies are examined including viscous dissip... [more]

The EU aims to become the world’s first climate-neutral continent by 2050. In order to meet this target, the integration of high shares of Renewable Energy Sources (RESs) in the energy system is of primary importance. Nevertheless, the large deployment of variable renewable sources such as wind and photovoltaic power will pose important challenges in terms of power management. For this reason, increasing the system flexibility will be crucial to ensure the security of supply in future power systems. This work investigates the flexibility potential obtainable from the diffusion of Demand Response (DR) programmes applied to residential heating for different renewables penetration and power system configuration scenarios. To that end, a bottom-up model for residential heat demand and flexible electric heating systems (heat pumps and electric water heaters) is developed and directly integrated into Dispa-SET, an existing unit commitment optimal dispatch model of the power system. The integ... [more]

Energy, precision, and multi-functionality have become primary considerations in incubators. For example, if a part of an apparatus must be insulated, while other parts do not, then the specific part can be placed in the multi-functional incubator proposed in this paper to avoid wasting energy. The proposed incubator is composed of various parts including a platform, which is provided for debugging parts to meet the working accuracy of parts. The light windows are adjustable in height to accommodate different heights of light. The incubator is black to prevent stray light in optical experiments. This design can not only insulate but also debug optical or non-optical parts according working accuracy of parts. In this paper, an example incubator is used for an optical experiment was given and the incubator was optimized several times. The temperature fluctuations of the box of the third optimized incubator reached 0.045∘C. To reduce the temperature fluctuations, the relationship between... [more]

Presently, deep learning models are an alternative solution for predicting solar energy because of their accuracy. The present study reviews deep learning models for handling time-series data to predict solar irradiance and photovoltaic (PV) power. We selected three standalone models and one hybrid model for the discussion, namely, recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and convolutional neural network-LSTM (CNN−LSTM). The selected models were compared based on the accuracy, input data, forecasting horizon, type of season and weather, and training time. The performance analysis shows that these models have their strengths and limitations in different conditions. Generally, for standalone models, LSTM shows the best performance regarding the root-mean-square error evaluation metric (RMSE). On the other hand, the hybrid model (CNN−LSTM) outperforms the three standalone models, although it requires longer training data time. The most sig... [more]

With only less than 10% recovery, the primary production of hydrocarbon from shale reservoirs has redefined the energy equation in the world. Similar to conventional reservoirs, Enhanced Oil Recovery (EOR) techniques could be devised to enhance the current recovery factors. However, shale reservoirs possess unique characteristics that significantly affect the fluid properties. Therefore, we are adopting a molecular simulation approach that is well-suited to account for these effects to evaluate the performance of three different gases, methane, carbon dioxide and nitrogen, to recover the hydrocarbons from rough pore surfaces. Our hydrocarbon systems consists of either a single component (decane) or more than one component (decane and pentane). We simulated cases where concurrent and countercurrent displacement is studied. For concurrent displacement (injected fluids displace hydrocarbons towards the production region), we found that nitrogen and methane yielded similar recovery; howeve... [more]

A large-eddy simulation (LES) of a gaseous hydrogen/liquid oxygen (GH2/LOX) single-injector rocket combustor is performed in this study. The Redlich−Kwong−Peng−Robinson (RK−PR) equation of state is used to simulate the real-gas effect under high-pressure conditions, and the steady laminar flamelet model (SLFM) is implemented to simulate fast chemistry, such as a H2/O2 reaction. From the numerical simulation, the characteristics of time-averaged flow and flame fields are obtained, and their relationship with the real-gas effect is investigated. It is possible to investigate unsteady flame features and the mixing mechanism of propellants in detail by examining multiple snapshots of the field contour. Another purpose of the study is to investigate the differences in flow and flame structures according to the variation in the turbulent Schmidt number. By comparing the simulation result with the natural OH* emission image and temperature profiles from experimental data, the appropriate rang... [more]

Since the widespread deployment of non-dispatchable, intermittent, and highly variable power production from renewable energy sources (RES), the demand for flexible power production has been steadily growing. As new-built dispatchable power plants have not been very quickly adapted to the emerging flexible operation, this task has been addressed by existing plants as well. Existing solid-fuel thermal power plants have undergone an extensive study to increase their flexible operation. Thermodynamic process-modeling tools have been extensively used for plant modeling. Steady- and transient-state simulations have been performed under various operating regimes, supplying valuable results for efficient power-plant operation. Flexibility aspects regarding low-load operation and steady operational conditions are mostly investigated with steady-state simulations. Flexibility aspects related to variation over time such as ramping rates are investigated with transient simulations. The off-design... [more]

The fast pyrolysis of coffee ground for bio-crude oil production was simulated in a tilted-slide reactor. The biochemical composition was derived by an extended biomass characterization method based on the elemental analysis. The simulation was performed in a steady-state and a Lagrangian multiphase model was adopted to describe the transport of sand and biomass particles together with a multistep kinetic mechanism for fast pyrolysis. When the secondary tar cracking reactions were not considered the volatile yield increased monotonically with temperature. The inclusion of secondary reactions could improve the prediction of volatile yield which turn to decrease at higher temperature. It was found that not only the maximum volatile yield but also the corresponding reactor temperature agreed well with the experimental results. At the temperature higher than 550 °C the trend of volatile yield is similar to that of experiment while it is larger at lower reactor temperature. The individual s... [more]

A Chinese traditional narrow street, named Cold-Lane, can create a microclimatic zone that provides pedestrian thermal comfort under hot and humid climate conditions. This phenomenon was observed through experimental measurement during the summer of 2016. The heat transfer rate over the pedestrian body surface was calculated to reveal why pedestrians experience a cool sensation, and computational flow dynamics (CFD) simulation was carried out to study the influence of the street aspect ratio on the shading effect. It was found that the perception of thermal comfort can be attributed mainly to the radiation between the relatively cool surrounding walls and the human body, and the wind velocity has little effect on sensible heat dissipation. The cool horizontal and vertical surfaces in the street canyon are mainly due to the shading effect as a result of the small aspect ratio, which is a typical characteristic of the traditional Chinese street. The shading effect of the high walls on bo... [more]

As the relative importance of renewable energy in electric power systems increases, the prediction of photovoltaic (PV) power generation has become a crucial technology, for improving stability in the operation of next-generation power systems, such as microgrid and virtual power plants (VPP). In order to improve the accuracy of PV power generation forecasting, a fair amount of research has been applied to weather forecast data (to a learning process). Despite these efforts, the problems of forecasting PV power generation remains challenging since existing methods show limited accuracy due to inappropriate cloud amount forecast data, which are strongly correlated with PV power generation. To address this problem, we propose a PV power forecasting model, including a cloud amount forecasting network trained with satellite images. In addition, our proposed model adopts convolutional self-attention to effectively capture historical features, and thus acquire helpful information from weathe... [more]

Geothermal heat exchangers (GHEs) represent a buried pipe system, which can be utilised to harness renewable thermal energy stored in the ground to improve the efficiency of heating and cooling systems. Two basic arrangements of GHEs have been widely used: vertical and horizontal. Vertical GHEs generally have a better performance in comparison with the horizontal arrangement, and these systems are particularly suitable for confined spaces. Nevertheless, the main technical challenge associated with GHEs, for either the vertical or the horizontal arrangement, is the performance deterioration associated with an increase in the operation times during summer or winter seasons. In this paper, a combined horizontal-vertical GHE arrangement is proposed to address the current challenges. The combined GHE arrangement can be operated in five different modes, corresponding to different thermal loading conditions. These five operation modes of the combined GHE are analysed based on the transient fi... [more]

Current transportation systems contributed to one quarter to the Greenhouse Gases (GhG) emissions and the mobility demand increases continuously. The transportation infrastructure design has to be optimized to mitigate these emissions. The methodology “Sloop” (acronym for Slope Optimization) has recently been set up to optimize the longitudinal road profile with respect to a Global Warming Potential (GWP) criterion calculated for both the construction and operational phases while incorporating accurate vehicle models. This paper proposes a customized optimization strategy that significantly improves the Sloop methodology. From an initial longitudinal profile generated by road designers, our algorithm identifies the optimized profile in terms of GWP. This optimization step is complex due to the large number of degrees of freedom, along with various constraints to obtaining a feasible solution and the computational cost of the operational phase assessment. The most stringent constraint e... [more]