In a competitive electricity market, generation capacities can exactly cover their full costs. However, the real market deviates from this ideal in some aspects. One is the concern of non-existent or insufficient scarcity prices. We present an iterative method in a linear optimization model to investigate the profitability of assets in the absence of scarcity prices and how the system changes when this risk is incorporated into investors’ expectations. Therefore, we use a two-step optimization of capacity planning and unit commitment. Iteratively, mark-ups at the height of uncovered costs are added to investment costs. This typically leads to a system with better investment profitability while keeping the system cost increase low. The methodology is applied to a simplified brownfield generation system, targeting CO2-free power generation within 25 years. In a model with annual foresight of actors, iterations result in a generation system with significantly lower (or even no) uncovered... [more]

Best estimate system thermal-hydraulic codes in the nuclear engineering community, e.g., TRACE, RELAP3D, CATHARE-3, etc., were extended with 3D coarse-mesh components to better describe the 3D Thermal-Hydraulic (TH) phenomena taking place within the Reactor Pressure Vessel (RPV) and the core. The RPV is usually shaped like a cylinder while the core is mostly a cube. Hence, the TRACE code is equipped with a Cylindrical VESSEL and a Cartesian VESSEL. The former one is to represent the RPV (including core), pressurizer, and steam generator. The latter one is more appropriate to represent the core. The two components are connected by two Vessel-Junctions (VJ) at the core inlet and outlet. Due to the different nodalization between the two VESSELs, the analyst needs to do repetitive and error-prone work defining the cell-to-cell junctions and their TH parameters. To facilitate this process, the Karlsruhe Institute of Technology (KIT) has developed an automatic approach based on a mesh-constr... [more]

District heating and cooling (DHC) networks, and in particular, the fifth generation of DHC networks, offer great potential in increasing the overall system efficiency and reducing CO2 emissions in the heating and cooling of urban districts. Due to the growing complexity of these energy systems, the use of new planning methods, such as the use of dynamic simulation models based on Modelica, becomes more important. However, especially with large, complex thermal networks, there is a high effort for manual model construction and parameterization. For this reason, we present a framework for automated model generation of DHC networks based on simulation models in Modelica written in Python. The core function of the Python framework is to transform a graph representation of a district heating network into a dynamic simulation model. The authors briefly describe the workflow and demonstrate its applicability with three different use cases. We investigate the impact of different design decisi... [more]

In recent years, demand for electric energy has steadily increased; therefore, the integration of renewable energy sources (RES) at a large scale into power systems is a major concern. Wind and solar energy are among the most widely used alternative sources of energy. However, there is intense variability both in solar irradiation and even more in windspeed, which causes solar and wind power generation to fluctuate highly. As a result, the penetration of RES technologies into electricity networks is a difficult task. Therefore, more accurate solar irradiation and windspeed one-day-ahead forecasting is crucial for safe and reliable operation of electrical systems, the management of RES power plants, and the supply of high-quality electric power at the lowest possible cost. Clouds’ influence on solar irradiation forecasting, data categorization per month for successive years due to the similarity of patterns of solar irradiation per month during the year, and relative seasonal similarity... [more]

The geological sequestration of CO2 in deep saline aquifers is one of the most effective strategies to reduce greenhouse emissions from the stationary point sources of CO2. However, it is a complex task to quantify the storage capacity of an aquifer as it is a function of various geological characteristics and operational decisions. This study applies physics-based proxy modeling by using multiple machine learning (ML) models to predict the CO2 trapping scenarios in a deep saline aquifer. A compositional reservoir simulator was used to develop a base case proxy model to simulate the CO2 trapping mechanisms (i.e., residual, solubility, and mineral trapping) for 275 years following a 25-year CO2 injection period in a deep saline aquifer. An expansive dataset comprising 19,800 data points was generated by varying several key geological and decision parameters to simulate multiple iterations of the base case model. The dataset was used to develop, train, and validate four robust ML models—... [more]

Floor heaving is a phenomenon that occurs in almost all mining roadways and tunnels. It can restrain the advance of the heading face or cause serious problems during roadway use. The highest levels of floor uplifting are observed in coal mines, which can reduce the output or even stop it altogether. The floor heaving intensity depends on the rock type, the stress in the rock mass, and rocks’ mechanical properties. Floor deformation develops when the secondary state of stress is formed around the working, and it is much higher and more dynamic in the case of waterlogged rocks. The presence of water increases the floor’s propensity to heave, especially clay rocks, such as claystones or mudstones, if they include water-absorbed minerals. In this paper, we present a new modeling methodology for roadway floor heave. The modeling covers a dry floor condition in which the parameters of the Hoek-Brown failure criterion are gradually lowered over time, and a waterlogged floor condition, in whic... [more]

Atmospheric air is a commonly used working fluid in turbomachinery. The air typically contains a certain amount of suspended solid particles, as well as water in the form of vapor or droplets. In the current paper, we focus on the numerical modeling of humid air transonic flow in turbomachinery. In this paper we demonstrate a rarely considered, but as presented herein important influence of air humidity, pollution and liquid water content on the performance of the first stage of the gas turbine compressor and turbofan engine fan (NASA rotors 37 and 67). We also discuss the impact of the interfacial heat transfer associated with steam condensation or water evaporation on the distribution of stagnation parameters at the rotor outlet, the rotor performance, and flow conditions, as well as losses. Results demonstrate the impact of the number of pollution particles and water droplets on the compression process in the analyzed rotors, especially on the Mach number distribution in the blade-t... [more]

Maintaining proper operation of adaptive protection schemes is one of the main challenges that must be considered for smart grid deployment. The use of reliable cyber detection and protection systems boosts the preparedness potential of the network as required by National Infrastructure Protection Plans (NIPPS). In an effort to enhance grid cyber-physical resilience, this paper proposes a tool to enable attack detection in protective relays to tackle the problem of compromising their online settings by cyber attackers. Implementing the tool first involves an offline phase in which Monte Carlo simulation is used to generate a training dataset. Using rough set classification, a set of If-Then rules is obtained for each relay and loaded to the relays at the initialization stage. The second phase occurs during online operation, with each updated setting checked by the corresponding relay’s built-in tool to determine whether the settings received are genuine or compromised. A test dataset w... [more]

The electrical power infrastructure of the modern world is advanced, efficient, and robust, yet power outages still occur. In addition to affecting millions of people around the world, these outage events cost billions of dollars to the global economy. In this paper, the revenue loss borne by electricity-supplying companies in the United States due to power outage events is estimated and predicted. Various factors responsible for power outages are considered in order to present an exploratory data analysis at the U.S. level, followed by the top ten affected states, which bear over 85% of the total revenue loss. The loss is computed using historic observational data of electricity usage patterns and the tariff offered by the energy suppliers. The study is supplemented with reliable and publicly available records, including electricity usage patterns, the consumer category distribution, climatological annotations, population density, socio-economic indicators and land area. Machine learn... [more]

The aim of the article is to present and analyze the processes occurring as a result of installing a long flashover arrester (LFA) and a multi-chamber arrester (MCA) as overvoltage protection of power networks. The numerical models of LFA and MCA will be made in order to carry out simulations in the scope of selected structural elements of the considered overvoltage protection device. The above research is a significant supplement to the information on the selection of an effective solution for overvoltage protection.

Oil drilling is the core process of oil and natural gas resources exploitation. Well overflow is one of the biggest threats to safety drilling. Prediction of the overflow in advance can effectively avoid the occurrence of this kind of accident. However, the drilling history has unbalanced distribution, and labeling data is a time-consuming and laborious job. To address this issue, an overflow-prediction algorithm based on semi-supervised learning is designed in this paper, which can accurately predict overflow 10 min in advance when the labeled data are limited. Firstly, a three-step feature-selection algorithm is conducted to extract 22 features, and the time series samples are constructed through a 500-width sliding window with step size 1. Then, the Mean Teacher model with Jitter noise is employed to train the labeled and unlabeled data at the same time, in which a fused CNN-LSTM network is built for time-series prediction. Compared with supervised learning and other semi-supervised... [more]

The study on the adsorption and micropore filling of water vapor in coal is significant for predicting coalbed methane content in coal seams. The primary purpose of this study is to explain the effects of coal pore structure and its surface chemistry on water vapor monolayer adsorption, micropore filling, and diffusion coefficient. First, X-ray diffraction (XRD) and mercury intrusion porosimetry (MIP) analyzed inorganic mineral components of two kinds of coal samples and pore fissures structures. Then, we divide pores and fissures according to the theory of fractal dimensions. Furthermore, we carried out the water vapor adsorption and desorption experiments on two kinds of coal; in particular, we set 14 points of relative pressure between 0 and 0.2. Guggenheim−Anderson−de Boer (GAB), Frenkel−Halsey−Hill (FHH), and Freundlich models were used to analyze the data of water vapor adsorption to obtain the boundary pressure points of the monolayer, multilayer adsorption, and capillary conden... [more]

This paper introduces a new single-phase AC-AC converter based on an impedance source circuit. Like the existing single-phase impedance source AC-AC converters, it has the buck-boost ability and direct ac conversion. The input and output voltage possesses the same ground, and the phase angle is maintained and reversed smoothly. The presented converter utilizes a coupled transformer which allows the designer to exploit the transformer’s turns ratio as a variable to attain the desired output voltage. Additionally, the used transformer provides an option to obtain higher voltage gain by decreasing the turns ratio. Hence, smaller size of the coupled inductors is required for the higher voltage cases. To eliminate the switching voltage and current spikes on the power switches, a safe commutation strategy is used instead of utilizing snubber circuits. Furthermore, the input current is continuous and sinusoidal with low harmonics thanks to embedding the input inductor in series with the input... [more]

This article analyzed the cost of capital under risk conditions for thermoelectric plants in Brazil, applying the Capital Asset Pricing Model—CAPM and the Weighted Average Capital Cost—WACC. To estimate the local CAPM, we used information from the Electric Energy Index—IEE of publicly traded companies in the electricity sector in Brazil and for the global CAPM, we observed the companies associated with the Edison Electric Institute—EEI, listed on the New York Stock Exchange—NYSE and at the National Association of Securities Dealers Automated Quotations—NASDAQ—USA. The risk conditions for capital costs were represented by Monte Carlo simulation using, as a basis, the WACC of a fuel oil thermoelectric plant and the local and global CAPM. The main results show that the IEE and EEI companies obtained a positive average daily return. Due to the Brazil risk, under deterministic conditions, the local WACC (11.13% p.a.) was more attractive to investors when compared to the global WACC (10.32%... [more]

Wind resource assessment is a key factor for the development and implementation of wind farms with the purpose of generating green, eco-friendly and clean electricity. The Bolivian Andes, as a large dry region, represents an important source of renewable energy. However, the altitude and high wind energy resources of the Bolivian Andes require further knowledge and understanding of the wind energy resources. In this study, the GWA have been used to determine the total area available to install wind farms considering the protected areas, roads, cities and transmission lines. In addition, the Weather Research and Forecasting (WRF v3.8.1) model is employed to complement the results of the GWA based on the validation of WRF simulations with measurements from Qollpana wind farm. The main purpose is to estimate the wind power potential along the Bolivian Andes and its variability in time. The wind power simulations have been compared with the power generated by the Qollpana wind farm to veri... [more]

To acquire a satisfying cutting effect during medium-length hole blasting driving of rock tunnels, an improved wedge cutting blasting method with supplementary blasting of the center holes was proposed. Initially, the cavity forming mechanism of the improved cutting method was analyzed theoretically. The results suggested that cutting hole blasting could realize the ejection of rock within the range from free face to critical cutting depth, and hence reduce the restraining force of the center hole blasting, and the supplementary blasting of the center holes could further accomplish the expulsion of the residuary rock. Subsequently, simulation of the improved cutting method was implemented to exhibit the stress wave evolution and reveal the stress field distribution. The simulation results indicated that cutting hole blasting could cause the preliminary failure of the residuary rock, and center hole blasting could strengthen the stress field intensity in 1.8−2.5 m in order to aggravate... [more]

The incineration process in waste-to-energy plants is characterized by high levels of inertia, large delays, strong coupling, and nonlinearity, which makes accurate modeling difficult. Therefore, an intelligent modeling method for the incineration process in waste-to-energy plants based on deep learning is proposed. First, the output variables were selected from the three aspects of safety, stability and economy. The initial variables related to the output variables were determined by mechanism analysis and the input variables were finally determined by removing invalid and redundant variables through the Lasso algorithm. Secondly, each delay time was calculated, and a multi-input and multi-output model was established on the basis of deep learning. Finally, the deep learning model was compared and verified with traditional models, including LSSVM, CNN, and LSTM. The simulation results show that the intelligent model of the incineration process in the waste-to-energy plant based on dee... [more]

The paper presents in an applicative manner a parameter-based methodology about design, modeling and optimization of a spur gear pump, currently under production in a Romanian company. Wanting to expand their product range, the company asked for a parameter-based design of this type of pump, FEM simulations and optimization of its conception to cover a wider range of flow rates, as required by current beneficiaries. The purpose of this research was to find improved alternative solutions via parametric design, mathematical validation and finite element simulation of the manufacturing solutions. The pump model is well known and has been manufactured for decades in many countries, under various licenses and constructive variants. The research process analyzed the functional role of the gear pump, its structure, its 3D model, which was reconstructed from the last manufactured solution, while identifying certain dimensions to be optimized and used in parametric design relations. The author... [more]

This paper developed a 3D physical model of the hydraulic end of a high-pressure liquid hydrogen reciprocating pump to research the dynamic characteristics of the pump valve system. Based on dynamic mesh technology, we analyzed the coupling characteristics of pump valve and plunger motion and spool force considering the leakage model, closure model of valve gap, and compressibility of liquid hydrogen. Further, we analyzed the effect of the spring stiffness and preload force on the laws of motion of the pump valve. Finally, a liquid hydrogen pressurization test was conducted to revise the simulation model and verify the accuracy of the simulation. The results of the simulation and test show that the simulation method in this paper can simulate the liquid hydrogen pressurization process more accurately and obtain the motion law of the suction and discharge valves. Both the suction and discharge valves have an opening hysteresis angle of about 40°, and there is a strong coupling relations... [more]

Previous micro-scale studies of the effect of pore structure on spontaneous imbibition are mainly limited to invariable-diameter capillaries. However, in real oil and gas reservoir formations, the capillary diameters are changing and interconnected. Applying the lattice Boltzmann color gradient two-phase flow model and the parallel computation of CPUs, we simulated the spontaneous imbibition in variable-diameter capillaries. We explored the reasons for the nonwetting phase snap-off and systematically studied the critical conditions for the snap-off in spontaneous imbibition. The effects of pore-throat aspect ratio, throat diameter, and the pore-throat tortuosity of the capillary on spontaneous imbibition were studied. Through analyzing the simulated results, we found that the variation in the capillary diameter produces an additional resistance, which increases with the increase in the pore-throat ratio and the pore-throat tortuosity of a capillary. Under the action of this additional... [more]

Accurately detecting oil leakage from a power transformer is important to maintain its normal operation. Deep learning (DL) methods have achieved satisfactory performance in automatic oil detection, but challenges remain due to the small amount of training data and oil targets with large variations in position, shape, and scale. To manage these issues, we propose a dual attention residual U-net (DAttRes-Unet) within a U-net architecture that extensively uses a residual network as well as spatial and channel-wise attention modules. To overcome the vanishing gradient problem due to deeper layers and a small amount of training data, a residual module from ResNet18 is used to construct the encoder path in the U-net framework. Meanwhile, to overcome the issue of training difficulty for the network, inspired by the advantage of transfer learning, initial network parameters in the encoder are obtained from the pre-trained ResNet18 on the ImageNet dataset. Further, in the decoder path, spatial... [more]

Flue gas produced by biomass fuel combustion contains various chlorine-containing substances and is an important factor causing biomass boiler corrosion. The corrosion processes of chlorine, hydrogen chloride and water on iron covered with an intact/damaged oxide film were investigated under the high temperature of 1300 K through reactive molecular dynamics simulation. The results show that the diffusion processes of oxygen and chlorine are similar and can be divided into three stages: rapid diffusion, continuous diffusion, and no oxide film (stable). Oxygen diffusion in Fe2O3 into a pure iron layer is the main cause of gas corrosion in iron/iron oxide systems. A complete oxide film can hinder iron corrosion by chlorine and hydrogen chloride. Damage in an oxide film significantly affects oxygen and chlorine diffusion and iron corrosion. However, such influence is gradually reduced. The integrity of a protective film is the key to alleviating corrosion. Water facilitates the dissociatio... [more]

The air leakage in sintering machines affects the technological and economic indexes of the sintering process. It is of great significance to monitor and estimate the key areas. Mathematical models of sintering air leakage through holes in the steady-state process are given based on the fluid mechanics to predict the flow rate and effect on the key area. It was found that the hole model is the application of constant orifice outflow in the computation of sintering air leakage. The counter-flow bed model is suitable for predicting the flow rate through a complete break in sintering wind boxes. Furthermore, This paper proposes a new hole−bed generalized model to cover all the possible hole diameters for further high-precision application. The model connects the leakage hole diameter with the sintering process for the first time and establishes their coupling relationship. The pressure state in the sintering system depends on the ratio of the leakage hole area to the sintering bed area. T... [more]

The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and... [more]

For the first time, the Weather Research and Forecast (WRF) model with the Wind Farm Parameterization (WFP) modeling method is utilized for a short-range wind power forecast simulation of 48 h of an offshore wind farm with 100 turbines located on the east coast of the China Yellow Sea. The effects of the horizontal multi-grid downsize method were deployed and investigated on this simulation computation. The simulation was validated with the field data from the Supervisory Control and Data Acquisition (SCADA) system, and the results showed that the horizontal mesh downsize method improved the accuracy of wind speed and then wind power forecast. Meanwhile, the wind power plant aerodynamics with turbine wake and sea−land shore effects were investigated, where the wake effects from the wind farm prolonged several miles downstream, evaluated at two wind speeds of 7 m/s and 10 m/s instances captured from the 48 h of simulation. At the same time, it was interesting to find some sea−land atmos... [more]