The use of low-emission combustion techniques in pulverized coal-fired (PC) boilers are usually associated with the formation of a reduced-gas atmosphere near evaporator walls. This increases the risk of high temperature (low oxygen) corrosion processes in coal-fired boilers. The identification of the dynamics and the locations of these processes, and minimizing negative consequences are essential for power plant operation. This paper presents the diagnostic system for determining corrosion risks, based on continuous measurements of flue gas composition in the boundary layer of the combustion chamber, and artificial intelligence techniques. Experience from the implementation of these measurements on the OP-230 hard coal-fired boiler, to identify the corrosion hazard of one of the evaporator walls, has been thoroughly described. The results obtained indicate that the continuous controlling of the concentrations of O2 and CO near the water wall, in combination with the use of neural netw... [more]

To study on the thermoelectric power generation for industrial waste heat recovery applied in a hot-air blower, an experimental thermoelectric generator (TEG) bench with the hexagonal heat exchanger and commercially available Bi2Te3 thermoelectric modules (TEMs) was established, and its performance was analyzed. The influences of several important influencing factors such as heat exchanger material, inlet gas temperature, backpressure, coolant temperature, clamping pressure and external load current on the output power and voltage of the TEG were comparatively tested. Experimental results show that the heat exchanger material, inlet gas temperature, clamping pressure and hot gas backpressure significantly affect the temperature distribution of the hexagonal heat exchanger, the brass hexagonal heat exchanger with lower backpressure and coolant temperature using ice water mixture enhance the temperature difference of TEMs and the overall output performance of TEG. Furthermore, compared w... [more]

Measuring systems are becoming increasingly sophisticated in order to tackle the challenges of modern industrial problems. In particular, the Multiphase Flow Meter (MPFM) combines different sensors and data fusion techniques to estimate quantities that are difficult to be measured like the water or gas content of a multiphase flow, coming from an oil well. The evaluation of the flow composition is essential for the well productivity prediction and management, and for this reason, the quantification of the meter measurement quality is crucial. While instrument complexity is increasing, demands for confidence levels in the provided measures are becoming increasingly more common. In this work, we propose an Anomaly Detection approach, based on unsupervised Machine Learning algorithms, that enables the metrology system to detect outliers and to provide a statistical level of confidence in the measures. The proposed approach, called AD4MPFM (Anomaly Detection for Multiphase Flow Meters), is... [more]

Operation and maintenance (O&M) activities represent a significant share of the total expenditure of a wind farm. Of these expenses, costs associated with unexpected failures account for the highest percentage. Therefore, it is clear that early detection of wind turbine (WT) failures, which can be achieved through appropriate condition monitoring (CM), is critical to reduce O&M costs. The use of Supervisory Control and Data Acquisition (SCADA) data has recently been recognized as an effective solution for CM since most modern WTs record large amounts of parameters using their SCADA systems. Artificial intelligence (AI) techniques can convert SCADA data into information that can be used for early detection of WT failures. This work presents a systematic literature review (SLR) with the aim to assess the use of SCADA data and AI for CM of WTs. To this end, we formulated four research questions as follows: (i) What are the current challenges of WT CM? (ii) What are the WT components to wh... [more]

Over time, oil production in a reservoir tends to decrease, which makes it difficult to flow through the reservoir to the well, making its production increasingly difficult and costly. Due to their physical properties, such as reducing the water/oil interfacial tension, surfactants have been used in enhanced oil recovery (EOR) processes, however, their adsorption presents as an undesirable and inevitable factor and can decrease the efficiency of the method. This work’s main objective is to evaluate the effect of glycerol in the adsorption of surfactants in sandstones, as well as in the recovery factor during EOR. Brine solutions containing the nonionic surfactant saponified coconut oil (SCO), with and without glycerol, were used in the adsorption and oil recovery tests in sandstone. Adsorption, recovery, rheological, and thermogravimetric analysis were carried out. Regarding the surfactant/glycerol/brine solution, there was an improvement in the oil mobility, as the glycerol contribute... [more]

In this study, a heat pump of 10 kW with vapor injection using refrigerant of R410A was developed. A vapor injection pipe connecting a gas−liquid separator at the outlet of the main expansion valve and the suction of a single-stage rotary compressor was designed. The heating performance of this vapor injection heat pump was investigated and analyzed at different compressor frequencies and primary temperatures. The experimental results show that for the heat pump without vapor injection, the heating capacity increased linearly with the compressor frequency, while the heating coefficient of performance (COP) decreased linearly with the compressor frequency for each tested primary temperature. The developed vapor injection technique is able to increase the heat pump system’s heating capacity and heating COP when the injection ratio R falls into the range 0.16−0.17. The refrigerant mass flow rate can be increased in the vapor injection heat pump cycle due to the decreased specific volume o... [more]

Renewable energy use can mitigate the effects of climate change. Solar energy is amongst the cleanest and most readily available renewable energy sources. However, issues of cost and uncertainty associated with solar energy need to be addressed to make it a major source of energy. These uncertainties are different for different locations. In this work, we considered four different locations in the United States of America (Northeast, Northwest, Southeast, Southwest). The weather and cost uncertainties of these locations are included in the formulation, making the problem an optimization-under-uncertainty problem. We used the novel Better Optimization of Nonlinear Uncertain Systems (BONUS) algorithm to solve these problems. The performance and economic models provided by the System Advisory Model (SAM) system from NREL were used for this optimization. Since this is a black-box model, this adds difficulty for optimization and optimization under uncertainty. The objective function and con... [more]

Temperature is an essential factor affecting the operation of light-emitting diodes (LEDs), which are often used in circuits containing multiple devices influencing each other. Therefore, the thermal models of such circuits should take into account not only the self-heating effects, but also the mutual thermal influences among devices. This problem is illustrated here based on the example of a module containing six LEDs forming on the substrate a hexagon. This module is supposed to operate without any heat sink in the natural convection cooling conditions, hence it has been proposed to increase the thermal pad area in order to lower the device-operating temperature. In the experimental part of the paper, the recorded diode-heating curves are processed using the network identification by deconvolution method. This allows for the computation of the thermal time constant spectra and the generation of device-compact thermal models. Moreover, the influence of the thermal pad surface area on... [more]

The electricity system is evolving due to three driven forces: decarbonization, digitalization, and decentralization (3 Ds). Should these three forces occur, electricity network tariffs must be revisited. In most countries, actual network charges incentivize inefficient network usage when volumetric or low granular (temporal and locational) charges are applied. This paper analyses the effect of 3 Ds on tariff design principles and proposes an efficient methodology for network tariff design that promotes efficient usage of the network as well as an equitable share of the costs for network users. The proposed network tariff consists of two components: a peak-coincident and a fixed charge. The peak-coincident forward-looking charge considers the cost of future network reinforcements required, calculated element-by-element, and assigned to customers during the peak utilization hours of each network element. Fixed charges allocate the residual part of the total network costs following equit... [more]

This paper investigates the applicability of Cone Penetration Test (CPT)-based axial capacity approaches, used for estimating pile static capacity, to the prediction of pile driveability. An investigation of the influence of various operational parameters in a driveability study is conducted. A variety of axial capacity approaches (IC-05, UWA-05 and Fugro-05) are assessed in unmodified and modified form to appraise their ability to be used in estimating the driveability of open-ended steel piles used to support, for example, offshore jackets or bridge piers. Modifications to the CPT-based design approaches include alterations to the proposed base resistance to account for the resistance mobilized under discrete hammer impacts and the presence of residual stresses, as well as accounting for the effects of static capacity increases over time, namely ageing. Furthermore, a study on the influence of various operational parameters within a wave equation solver is conducted to ascertain the... [more]

The aim of this study is to develop a reliable numerical model that provides additional information to experimental measurements and contributes to a better exploitation of hydraulic turbines during transient operation. The paper presents a numerical analysis of the flow inside a Kaplan turbine model operated at a fixed runner blade angle during load variation from the best efficiency point (BEP) to part load (PL) operation. A mesh displacement is defined in order to model the closure of the guide vanes. Two different types of inlet boundary conditions are tested for the transient numerical simulations: linear flow rate variation (InletFlow) and constant total pressure (InletTotalPressure). A time step analysis is performed and the influence of the time discretization over the fluctuating quantities is discussed. Velocity measurements at the corresponding operating points are available to validate the simulation. Spectrogram plots of the pressure signals show the times of appearance of... [more]

Energy-efficient buildings, sustainable buildings, smart buildings, nearly zero-energy buildings, passive and active buildings are construction concepts widely recognised as setting the latest trends. The purpose of their design is to create an optimal thermal microclimate by means of heat flows that are either formed within it or enter into it. This research paper presents an analysis of the measurements of the density of heat flows, their spread in building constructions, all of which is examined in laboratory conditions and confronted with calculation models. The hypothesis of this research is to confirm or refute whether the computational models match the laboratory simulations in terms of thermal-technical parameters. The research uses a methodology designed for examining building constructions under virtually stable conditions. Two variants of external sandwich walls based on prefab cross laminated timber panels (variant A) and structural insulated panel (variant B) were proposed... [more]

The implementation of model predictive controls (MPCs) in buildings represents an important opportunity to reduce energy consumption and to apply demand side management strategies. In order to be effective, the MPC should be provided with an accurate model that is able to forecast the actual building energy demand. To this aim, in this paper, a data-driven model realized with an artificial neural network is compared to a physical-based resistance−capacitance (RC) network in an operative MPC. The MPC was designed to minimize the total cost for the thermal demand requirements by unlocking the energy flexibility in the building envelope, on the basis of price signals. Although both models allow energy cost savings (about 16% compared to a standard set-point control), a deterioration in the prediction performance is observed when the models actually operate in the controller (the root mean square error, RMSE, for the air zone prediction is about 1 °C). However, a difference in the on-time... [more]

The article presents the recipe for ultra-lightweight cement slurry for wellbore sealing. In ordinary lightweight cement slurries, the addition of microspheres and a large amount of water are used to maintain rheological parameters. This is a problem because the light particles of microspheres segregate. The cement sheath from such a cement slurry has an anisotropic microstructure and does not stabilize the casing column. In the new ultra-light cement slurry, 60% aluminosilicate microspheres and a large amount of water were used. The ultra-light weight slurry has a density below 1.2 g/cm3. This cement slurry does not segregates and in the sedimentation stability test has the same density at all measuring points. The cement slurry, despite the larger amount of water, has the same filtration as the control sample. The technological parameters of the slurry are adapted to the borehole conditions. Cement slurry is a ready-made application to seal a borehole with poor wellbore stability und... [more]

For high-voltage and extra-high-voltage consumers, the electricity cost depends not only on the power consumed but also on the contract capacity. For the same amount of power consumed, the smaller the difference between the contract capacity and the power consumed, the smaller the electricity cost. Thus, predicting the future power demand for setting the contract capacity is of great economic interest. In the literature, most works predict the future power demand based on a symmetric loss function, such as mean squared error. However, the electricity pricing structure is asymmetric to the under- and overestimation of the actual power demand. In this work, we proposed several loss functions derived from the asymmetric electricity pricing structure. We experimented with the Long Short-Term Memory neural network with these loss functions using a real dataset from a large manufacturing company in the electronics industry in Taiwan. The results show that the proposed asymmetric loss functio... [more]

Non-intrusive load monitoring (NILM) has become an important subject of study, since it provides benefits to both consumers and utility companies. The analysis of smart meter signals is useful for identifying consumption patterns and user behaviors, in order to make predictions and optimizations to anticipate the use of electrical appliances at home. However, the problem with this kind of analysis rests in how to isolate individual appliances from an aggregated consumption signal. In this work, we propose an unsupervised disaggregation method based on a controlled dataset obtained using smart meters in a standard household. By using soft computing techniques, the proposed methodology can identify the behavior of each of the devices from aggregated consumption records. In the approach developed in this work, it is possible to detect changes in power levels and to build a box model, consisting of a sequence of rectangles of different heights (power) and widths (time), which is highly ada... [more]

As one of the most essential earth-moving equipment, cable shovels significantly influence the efficiency and economy in the open-pit mining industry. The optimal digging trajectory planning for each cycle is the base for achieving effective and energy-saving operation, especially for robotic excavation, in which case, the digging trajectory can be precisely tracked. In this paper, to serve the vision of cable shovel automation, a two-phase multi-objective genetic algorithm was established for optimal digging trajectory planning. To be more specific, the optimization took digging time and energy consumption per payload as objects with the constraints of the limitations of the driving system and geometrical conditions. The WK-55-type cable shovel was applied for the validation of the effectiveness of the multi-objective optimization method for digging trajectories. The digging performance of the WK-55 cable shovel was tested in the Anjialing mining site to establish the constraints. Bes... [more]

Electric vehicles (EVs) parking lots are representing significant charging loads for relatively a long period of time. Therefore, the aggregated charging load of EVs may coincide with the peak demand of the distribution power system and can greatly stress the power grid. The stress on the power grid can be characterized by the additional electricity demand and the introduction of a new peak load that may overwhelm both the substations and transmission systems. In order to avoid the stress on the power grid, the parking lot operators are required to limit the penetration level of EVs and optimally distribute the available power among them. This affects the EV owner’s quality of experience (QoE) and thereby reducing the quality of performance (QoP) for the parking lot operators. The QoE is represents the satisfaction level of EV owners; whereas, the QoP is a measurement representing the ratio of EVs with QoE to the total number of EVs. This study proposes a fuzzy logic weight-based charg... [more]

When planning the energy demand of ventilation, proper consideration should be given to the possible scenarios of indoor air quality and pollutant concentrations. The purpose of the present research is to create a practical method of prioritising indoor air pollutants, considering technical, economical and health aspects, in the Indoor Air Quality model (IAQ). In order to find the global weights for the combined IAQindex model sub-elements (in practice, air pollutant concentrations), the Multi-Criteria Decision Making (MCDM) approach is used. The authors have approached the problem of a weighting scheme in a model such as the complex model of the IAQ related to making decisions with many criteria and with the Multi-Attribute Decision Making MADM approach (specifically MCDM). The basis of the MADM method is a decision matrix constructed rationally by the authors, which includes six attributes: actual indoor air carbon dioxide concentration, total volatile organic compounds (TVOCs) and f... [more]

An appropriate energy management strategy is essential to enhance the performance of hybrid electric vehicles. A novel modified equivalent fuel-consumption minimization strategy (ECMS) is developed considering the engine operating point deviation from the optimum operating line. This paper focuses on an all-inclusive evaluation of this modified ECMS with other state-of-art energy management strategies concerning battery ageing, engine switching along with fuel economy and charge sustenance. The simulation-based results of a hybrid two-wheeler concept are analysed, which shows that the modified ECMS offers the highest benefit compared to rule-based controllers concerning fuel economy and reduction in engine switching events. However, the improvement in fuel economy using modified ECMS has significant negative potential effects on critical battery parameters influencing battery ageing. The results are analysed and found consistent for two different drive cycles and three different powert... [more]

For several decades, constant research has been performed in the world in order to obtain more durable, tighter, or less environmentally harmful binding materials which could be used to seal casing strings in boreholes. There is an increasing search for innovative solutions allowing the production of the highest possible class of binding cements. Since the beginning of the 21st century, one thing which has become synonymous with development is nanotechnology—a dynamically growing branch of science involving both the design, production, and testing of structures with the size of billionths of a metre. Among other things, a set cement stone is made of the grains of hydrated calcium silicates and calcium aluminates, between which there are pore spaces. Fine grains of nanoparticles can successfully settle inside these spaces, causing a decrease in the porosity and permeability of cement matrix. The paper presents the results of laboratory tests performed for formulas of cement slurries con... [more]

In this paper, we consider a probabilistic microgrid dispatch problem where the predictions of the load and the Renewable Energy Source (RES) generation are given in the form of intervals. A hybrid method combining scenario-selected optimization and reserve strategy using the Model Predictive Control (MPC) framework is proposed. Specifically, first of all, an appropriate scenario is selected by the optimizer at each optimization stage, and then the optimal scheduling and reservation of system capacity are determined based on the selected scenario and possible variations in the future as provided by the predictors. In addition, a new reserve strategy is introduced to adaptively maintain system reliability and respond to variations in the hierarchical microgrid control. Simulations are conducted to compare our proposed method with the existing robust method and the deterministic dispatch with perfect information. Results show that our proposed method significantly improves the system eff... [more]

Electric power grids are a crucial infrastructure for the proper operation of any country and must be preserved from various threats. Detection of illegal electricity power consumption is a crucial issue for distribution system operators (DSOs). Minimizing non-technical losses is a challenging task for the smooth operation of electrical power system in order to increase electricity provider’s and nation’s revenue and to enhance the reliability of electrical power grid. The widespread popularity of smart meters enables a large volume of electricity consumption data to be collected and new artificial intelligence technologies could be applied to take advantage of these data to solve the problem of power theft more efficiently. In this study, a robust artificial intelligence algorithm adaptive neuro fuzzy inference system (ANFIS)—with many applications in many various areas—is presented in brief and applied to achieve more effective detection of electric power theft. To the best of our kn... [more]

Water-processable natural polymers represent a valuable alternative for the sustainable manufacturing of electrical double layer capacitors (EDLCs). Here, we demonstrate for the first time the feasibility of the use of pullulan to produce high mass loading electrodes (>10 mg cm−2) at low binder content (10%) for ionic-liquid based EDLCs. Pullulan has also been processed as a porous separator by electrospinning. Its ionic resistance and thermal stability have been evaluated in different electrolytes and were found to be superior compared to those of a cellulose triacetate electrospun separator. Pullulan-ionic liquid EDLCs were, thus, assembled and charged up to 3.2 V. The EDLCs delivered specific energy and power of 7.2 Wh kg−1 and 3.7 kW kg−1 and featured good cycling stability over 5000 cycles.

The emergence of electric vehicles offers the opportunity to decarbonize the transportation and mobility sector. With smart charging strategies and the use of electricity generated from renewable sources, electric vehicle owners can reduce their electricity bill as well as reduce their carbon footprint. We investigated smart charging strategies for electric vehicle charging at household and workplace sites with photovoltaic systems. Furthermore, we investigated the participation of an electric vehicle in the provision of positive automatic frequency restoration reserve (aFRR) in Germany from 30 October 2018 to 31 July 2019. We find that the provision of positive aFRR in Germany returns a positive net return. The positive net return is, however, not sufficient to cover the current investment cost for a necessary control unit. For home charging, we find that self-sufficiency rates of up to 48.1% and an electricity cost reduction of 17.6% for one year can be reached with unidirectional sm... [more]