The pitch controller of a floating offshore wind power system has an important influence on the power generation and movement of the floating body. It drives the turbine blade pitch using a hydraulic actuator, whose inherent characteristics cause a delay in response, which increases with the system capacity. As a result, the power generation is reduced, and the pitch motion of the floating body is increased. This paper proposes an advanced pitch controller designed to compensate for the delay in the hydraulic actuator response. The proposed pitch controller applies an artificial-intelligence-based deep learning algorithm to predict the delay time in the hydraulic actuator. This delay is compensated for by preferentially predicting the blade pitch control angle even if a delay occurs in the hydraulic actuator. The performance of the proposed pitch controller was analyzed using the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) v8 model developed by the US National Renewable En... [more]

Great progress has been made in the exploration of tight sandstone gas resources in Kuqa depression. Great progress has been made in Dibei structural belt, which proves the previously unproven favorable area for tight sandstone gas. The physical properties, controlling factors, and characteristics of tight sandstone from the Ahe (J1a) Formation in the Dibei gas reservoir are analyzed. The results show that the tight sandstone of the J1a Formation is mainly feldspar lithic sandstone, with low porosity (average 9.1%) and low permeability (average 0.09 mD). Compaction (average compaction rate 61.9%) reduces porosity more than cementation (average cementation rate 14.3%). Secondary dissolution pores (average thin section porosity is 3.4%) dominate. The homogenization temperature has two peaks; the first peak is 85−110 °C, and the other peak is 115−140 °C, indicating that oil and gas experienced two filling stages at 12 Ma and 4.5 Ma, respectively. Eodiagenesis, A substage of mesogenetic di... [more]

The use of a Doubly Fed Asynchronous Machine (DFAM) provides attractive characteristics and offers operational flexibility in many variable speed generation applications, such as in a hydroelectric pumped storage plant. In a variable speed hydroelectric pumped storage plant, the start-up process of DFAM is identical to the conventional singly fed asynchronous machine, wherein a significant amount of energy is wasted. This paper introduces an energy-efficient start-up strategy in DFAM based hydroelectric pump-turbine. The back-to-back voltage source converter connected to the rotor side is amenable for speed control (real power), braking (regenerative/dynamic), and starting the unit. Further, in this starting technique, the stator circuit of the machine is injected with a low voltage DC supply at starting instead of short-circuiting the windings. This DC injection reduces the slip losses and cuts down the magnetizing current requirement. The magnitude of the required DC supply is estima... [more]

Because generating electricity significantly contributes to global greenhouse gas emissions, meeting the 2015 Paris Agreement and 2021 Glasgow Climate Pact requires rapidly transitioning to zero or low-emissions electricity grids. Though the installation of renewables-based generators—predominantly wind and solar-based systems—is accelerating worldwide, electrical energy storage systems, such as pumped storage hydropower, are needed to balance their weather-dependent output. The authors of this paper are the first to examine the status and potential for pumped storage hydropower development in 24 Pacific Rim economies (the 21 member economies of the Asia Pacific Economic Cooperation plus Cambodia, Lao PDR, and Myanmar). We show that there is 195 times the pumped storage hydropower potential in the 24 target economies as would be required to support 100% renewables-based electricity grids. Further to the electrical energy storage potential, we show that pumped storage hydropower is a lo... [more]

The rapid development of artificial intelligence offers more opportunities for intelligent mechanical diagnosis. Fault diagnosis of wind turbines is beneficial to improve the reliability of wind turbines. Due to various reasons, such as difficulty in obtaining fault data, random changes in operating conditions, or compound faults, many deep learning algorithms show poor performance. When fault samples are small, ordinary deep learning will fall into overfitting. Few-shot learning can effectively solve the problem of overfitting caused by fewer fault samples. A novel method based on meta-analogical momentum contrast learning (MA-MOCO) is proposed in this paper to solve the problem of the very few samples of wind turbine failures, especially one-shot. By improving the momentum contrast learning (MOCO) and using the training idea of meta-learning, the one-shot fault diagnosis of wind turbine drivetrain is analyzed. The proposed model shows a higher accuracy than other common models (e.g.,... [more]

To combat global warming, “carbon neutrality” has gradually become a consensus. Some countries have constructed domestic and regional carbon trading markets, and links to global carbon markets are receiving increasing attention. Blue carbon, an important component of nature-based solutions (NbS), has not received the attention it deserves and is still isolated from the carbon trading market. Based on summarizing the existing achievements of blockchain application in carbon trading, this paper analyzes how to make each participating body provide services in the process of blue carbon production, circulation and trading, and designs the architectural diagram of the blue carbon system under peer-to-peer (P2P) transactions based on the theoretical framework of blockchain 3.0. Utilizing the advantages of decentralization, high transparency and non-tamperability of blockchain, we can realize a highly efficient, low-cost and intelligent blue carbon trading management system. Thus, we can make... [more]

The problem of global warming is still a major issue, alongside shrinking oil reserves. A great alternative to fossil fuels is offered by biofuels, such as bioethanol from lignocellulosic plants. The sorghum biomass can be effectively used in many industrial directions. It is possible to use every part of this plant; the grain can be used for food production and straw can be used for energy purposes, i.e., for bioethanol. The aim of this study was to analyze the possibilities of bioethanol production from five varieties of sorghum biomass, which is a waste product of seed harvesting. The yields of sorghum cultivars in a three-year vegetation period; the amount of cellulose, hemicellulose, and lignin in the biomass of sorghum; and the amount of ethanol obtained per hectare were evaluated. It was observed that the highest average yield for all cultivars, except GK Emese, was found in the second year of the study. The bioethanol yield per hectare from this biomass was the highest for Swee... [more]

In the present study, continuous measurements of solar global (G) and ultraviolet-B (UVB) radiation are taken in Kuwait for 2014−2019 for all weather conditions. Hourly curves show a sinusoidal behavior for both G and UVB radiation. Statistical analysis indicates that there is a good agreement between hourly G and hourly UVB as the coefficients of determination (R2) for all years are larger than 0.91 and the root-mean-square error (RMSE) and mean bias error (MBE) are very small. The hourly percentage ratio (UVB/G) is found to decrease with G due to cloudy sky conditions. In addition, the ratio (UVB/G) tends to decrease with global clearness index (KT), indicating that a higher ratio of (UVB/G) can be obtained for a cloudier atmosphere. Another interesting finding is that KT and the UVB index (KTUVB) are directly proportional, and a third-order polynomial fit gives an acceptable formula (R2 = 0.859). Daily G and UVB values are very well correlated as R2 is very close to unity for all ye... [more]

The power electronic transformer (PET), as a main topology for the energy router in the energy internet, consists of the rectifiers, the dual active bridge (DAB), and the inverter, and these three parts are connected by two dc buses. So, the performance of the dc bus voltages is very important because it can totally affect the output waveforms of the dc and ac voltage, especially for the voltage-sensitive loads. Compared with the proportion integration (PI) control scheme, the energy control method utilizes the energy as the control variable, and the control strategy derived from the energy relationship, including the passive elements and all the interfaces, is more direct and explicit. In this paper, considering the energy between the dc bus capacitors and the input inductor and the load and the source in the PET topology, the energy balance control (EBC) strategy is proposed. For the two dc bus voltages, the energy balance relationship of the different time scales is used to decouple... [more]

With the increasingly prominent environmental problems in the world today, the development of an integrated energy system and the introduction of a carbon-trading mechanism have become important means to realize the low carbonization of the energy industry. Based on this, this paper introduces the carbon-trading mechanism into the research on the optimal dispatch of an integrated energy system. The mechanism of integrated energy demand response participating in low-carbon economic dispatch is analyzed. The relationship between carbon emissions and carbon-trading price in carbon-trading mechanism is described. On the basis of considering the commodity attributes of the electricity and gas load and the flexible supply characteristics of the thermal load, an incentive-type comprehensive energy demand response model is established. Finally, aiming at the lowest comprehensive operating cost, a comprehensive energy system model considering the power balance and equipment constraints of the e... [more]

The shunt active power filter (SAPF) system oscillation is a massive threat to the security and stability of the power grid. This study classifies SAPF oscillation into two categories according to the difference in mechanisms. The SAPF oscillation in one category is caused by the resonant characteristics of a switching noise filter and is called external loop amplification. The SAPF oscillation in the other category is induced by the presence of a capacitor in the load current for SAPF and is called self-excited oscillation. Unlike previous studies, this study tried to reveal the internal relationship between the two kinds of SAPF oscillation, present a general shunt virtual-damping-based SAPF oscillation suppression strategy covering the previous resonant damping method, and provide the discrete domain stability criterion of the control system. The sampling frequency was at least six times the resonant frequency. The stability region was enlarged with an increase in the sampling frequ... [more]

Considering increasingly ambitious pledges by countries and various forms of pressure from current international constellations, society, investors, and clients further up the supply chain, the question for companies is not so much whether to take decarbonisation action, but what action and by when. However, determining an ideal mix of measures to apply ‘decarbonisation efficiency’ requires more than knowledge of technically feasible measures and how to combine them to achieve the most economic outcome: In this paper, working in a ‘backcasting’ manner, the author describes seven aspects which heavily influence the composition of an ‘ideal mix’ that executive leadership needs to take a (strategic) position on. Contrary to previous studies, these aspects consider underlying motivations and span across (socio-)economic, technical, regulatory, strategic, corporate culture, and environmental factors and further underline the necessity of clarity of definitions. How these decisions influence... [more]

To detect the aging of power cables in the TOKAMAK power supply systems, this paper proposed a deep neural network diagnosis model and algorithm for power cable aging, based on logistic regression according to the characteristics of different high-order harmonics generated by different aging parts of the power cable. The experimental results showed that the model has high diagnostic accuracy, and the average error is only 2.35%. The method proposed in this paper has certain application potential in the CFETR power cable auxiliary monitoring system.

It is well established that renewable energy resources for electricity generation are free. In hot areas, solar energy has become one of the major interests of researchers and specialists. This paper aims to experimentally investigate the maximum voltage generation of a thermoelectric generator (TEG) panel. This panel was built from many TEG modules that are connected in series and in parallel. The panel was exposed to high heat due to solar radiation during summer, either directly or through a Fresnel lens. The other side of the TEG panel was cooled using tap water that was passed through aluminum heat exchangers in an active cooling method. It was found that the maximum open-circuit voltage of this TEG panel using a Fresnel lens was 9.35 V. With no lens, it was 11.75 V at 14:00 h local time. The experiments were done during a sunny July period in Iraq.

Estimating the quantity of seepage through the foundation and body of a dam using proper health and safety monitoring is critical to the effective management of disaster risk in a reservoir downstream of the dam. In this study, a deep learning model was constructed to predict the extent of seepage through Pakistan’s Tarbela dam, the world’s second largest clay and rock dam. The dataset included hydro-climatological, geophysical, and engineering characteristics for peak-to-peak water inflows into the dam from 2014 to 2020. In addition, the data are time series, recurring neural networks (RNN), and long short-term memory (LSTM) as time series algorithms. The RNN−LSTM model has an average mean square error of 0.12, and a model performance of 0.9451, with minimal losses and high accuracy, resulting in the best-predicted dam seepage result. Damage was projected using a deep learning system that addressed the limitations of the model, the difficulties of calculating human activity schedules,... [more]

This paper proposes a method to improve the output torque of a six-phase permanent-magnet synchronous machine (PMSM) within the same current peak limit through a fifth-harmonic injection into each phase current of the stator. Compared to the fifth + seventh-harmonic current-injection method used to improve the output torque of the six-phase PMSM, the control system can be stably controlled, and the controller design complexity decreased. This is because the harmonic component was converted into a direct current (DC) component and controlled by a proportional-integral (PI) controller instead of the fifth + seventh-harmonic injection method, which converts the harmonic component into an alternating current (AC) component and controls it with a resonance controller. The appropriate fifth-harmonic ratio for maximum output torque through fifth-harmonic injection was selected through optimization using values analyzed via fast Fourier transform (FFT) for stator phase harmonic current terms c... [more]

Additive manufacturing offers several opportunities for thermoelectric energy harvesting systems. This new manufacturing approach enables customized leg geometries, minimized thermal boundary resistances, less retooling, reduced thermoelectric material waste, and strong potential to manipulate microstructure for higher values of figure of merit. Although additive manufacturing has been used to fabricate thin thermoelectric films, there has been comparatively limited demonstrations of additive manufacturing for bulk thermoelectric structures. This review provides insights about the current progress of bulk thermoelectric material and device additive manufacturing. Each additive manufacturing technique used to produce bulk thermoelectric structures is discussed in detail along with future directions and challenges.

Wireless power transfer (WPT) is currently sparking more attention towards the application of wireless charging for mobile devices and electric vehicles [...]

The automotive market has been developing very dynamically recently. Contemporary trends focus on the development of the so-called intelligent vehicles, often combined with modern technology and supporting systems. Cars with a large scope of operation in terms of driving autonomy can increasingly be found. These types of solutions can lead to changes in production processes through the emergence and growing importance of new concepts and technologies. The article presents the concept of BEV (Battery Electric Vehicle) and PHEV (Plug-in Hybrid Electric Vehicle) vehicles in relation to modern solutions and their levels of autonomy. The research was conducted in various groups of respondents, while the analyses were carried out mainly with the use of two grouping variables: gender and place of residence. Based on our own research, it can be concluded that due to many different factors, most respondents believe that PHEV hybrid vehicles and electric vehicles (BEV) are currently, and will mo... [more]

Acoustic process tomography is a powerful tool for monitoring multiphase flow and combustion. However, its capability of revealing details of the interrogation zone is restricted by the ill-posed and rank deficiency problems. In each projection, a probing sound beam only passes the pixels along its propagation path, resulting in a large number of zero-valued elements in the measurement matrix. This is more pronounced as the resolution of the imaging zone becomes gradually finer, which is detrimental to image reconstruction. In this study, a mathematically explicable reconstruction algorithm of regularization is proposed by assigning each zero-valued pixel with a combination of the values of the neighboring pixels, ruled by the appropriate regularization factors. The formula to determine the regularization factors is also derived. Simulations are carried out to verify this new approach, and some representative cases are presented. As a result, the ambiguity of the inverse process is rem... [more]

Building occupancy is one of the relevant variables to understand the energy performance of buildings and to reduce the current gap between simulation-based and actual energy performance. In this study, the occupancy of a classroom in an educational center monitored over a full year was experimentally assessed. The classroom had different occupancy levels during the school year, with a theoretical minimum of eleven students, and no occupancy during vacations and weekends. Different variables such as indoor air temperature, relative humidity, CO2 concentration, overall electrical energy consumption of the educational center, electrical energy consumption of the building in which the monitored classroom is located, and heating energy consumption were recorded. We analyzed which of these variables were possible indicators of classroom occupancy, using the school timetable as a theoretical reference value for the validation of the results. Based on previous studies, one-hour moving average... [more]

The exhaust air glass unit (EAGU) can be treated as an integration of multilayer glazing unit and heat recovery device to utilize the exhaust air from conditioned space with a fresh air ventilation system to improve the thermal performance of window system. However, compared with the conventionally used mechanical ventilation with a heat recovery (MVHR) system, whether the use of EAGU is energy-efficient or not has not been estimated. In this paper, a numerical model, validated by experimental measurement, was used to calculate the hourly cooling and heating loads and annual energy demand of EAGU. This study compared the annual energy performance of EAGU and MVHR under various conditions, and further discusses the applicability of EAGU for different climates. The results indicate that the energy saving potential of EAGU ranges from 26.8% to 38.2% for different climate conditions. In the cooling season, the energy saving potential of EAGU performed much better than that of the commonly... [more]

In an energy harvesting wireless sensor node (EHWSN), balance of energy harvested and consumption using dynamic energy management to achieve the goal of perpetual operation is one of the most important research topics. In this study, a novel fuzzy Q-learning (FQL)-based dynamic energy management (FQLDEM) is proposed in adapting its policy to the time varying environment, regarding both the harvested energy and the energy consumption of the WSN. The FQLDEM applies Q-learning to train, evaluate, and update the fuzzy rule base and then uses the fuzzy inference system (FIS) for determining the working duty cycle of the sensor of the EHWSN. Through the interaction with the energy harvesting environment, the learning agent of the FQL will be able to find the appropriate fuzzy rules in adapting the working duty cycle for the goal of energy neutrality such that the objective of perpetual operation of the EHWSN can be achieved. Experimental results show that the FQLDEM can maintain the battery... [more]

With the increasing proportion of Li-ion batteries in energy structures, studies on the estimation of the state of charge (SOC) of Li-ion batteries, which can effectively ensure the safety and stability of Li-ion batteries, have gained much attention. In this paper, a new data-driven method named the probabilistic threshold compensation fuzzy neural network (PTCFNN) is proposed to estimate the SOC of Li-ion batteries. Compared with other traditional methods that need to build complex battery models, the PTCFNN only needs data learning to obtain nonlinear mapping relationships inside Li-ion batteries. In order to avoid the local optimal value problem of traditional BP neural networks and the fixed reasoning mechanism of traditional fuzzy neural networks, the PTCFNN combines the advantages of a probabilistic fuzzy neural network and a compensation fuzzy neural network so as to improve the learning convergence speed and optimize the fuzzy reasoning mechanism. Finally, in order to verify t... [more]

To understand the effect of hydrogen addition on the laminar burning velocity (LBV) of ethanol−air mixtures, experiments were conducted in a constant volume combustion chamber with the high-speed schlieren photography technique. The experiments were carried out under the equivalence ratios (ERs) of 0.7−1.4, an initial temperature of 400 K, an initial pressure of 0.1 MPa, and hydrogen fractions of 30% and 90% by volume, respectively. The effects of ER, initial temperature, initial pressure, and hydrogen fractions on the LBV were investigated. Moreover, adiabatic flame temperature (AFT), heat release rate (HRR), flow rate sensitivity analysis, and ROP (rate of production) analysis were also performed. Results showed that LBV increased with increasing hydrogen addition and temperature but decreased with increasing pressure. The hydrogen addition significantly increased the HRR of ethanol−hydrogen−air flames. The sensitivity analysis showed that R5 (O2 + H = O + OH) significantly influence... [more]