Increased focus on sustainability and energy decentralization has positively impacted the adoption of nanogrids. With the tremendous growth, load forecasting has become crucial for their daily operation. Since the loads of nanogrids have large variations with sudden usage of large household electrical appliances, existing forecasting models, majorly focused on lower volatile loads, may not work well. Moreover, abrupt operation of electrical appliances in a nanogrid, even for shorter durations, especially in “Peak Hours”, raises the energy cost substantially. In this paper, an ANN model with dynamic feature selection is developed to predict the hour-ahead load of nanogrids based on meteorological data and a load lag of 1 h (t-1). In addition, by thresholding the predicted load against the average load of previous hours, peak loads, and their time indices are accurately identified. Numerical testing results show that the developed model can predict loads of nanogrids with the Mean Square... [more]

Diesel engines are widely used in agricultural tractors. During field operations, the tractors operate at low speed and high load for a long time, the fuel efficiency is only about 15% to 35%, and the exhaust waste heat accounts for 38% to 45% of the energy released from the fuel. The use of tractor exhaust waste heat can effectively reduce fuel consumption and pollutant emissions, of which the organic Rankine cycle (ORC)-based waste heat recovery conversion efficiency is the highest. First, the diesel engine map is achieved through the test rig, a plate-fin evaporator is trial-produced based on the tractor size, and the thermodynamic and economic performance model of the ORC are established. Then, taking the thermal efficiency of ORC and the specific investment cost (SIC) as the objective function, the particle swarm optimization (PSO) algorithm and the technique for order of preference by similarity to ideal solution (TOPSIS) decision method were used to obtain the optimal operating... [more]

This paper presents the integrated optimal design of the powertrain of a hybrid regional aircraft using multidisciplinary design optimization (MDO). The sizing of the main components of the propulsion chain is performed over the flight mission under various scenarios regarding energy management strategies and technological assessments. For that purpose, a complete set of multidisciplinary surrogate models are integrated into the MDO process, taking account not only of the main electrical, thermal and mechanical aspects but also of environmental constraints such as partial discharges in electric motors regarding flight conditions. Several MDO formulations are investigated comparing local (i.e., motor mass minimization) and global optimizations (i.e., powertrain mass then fuel burn minimization at aircraft level). Results emphasize main systemic couplings showing that despite future technological progress, the series hybrid architecture is heavier than a conventional thermal aircraft. Ne... [more]

The calorific value of coal gangue is a critical index for coal waste recycling and the energy industry. To establish an accurate and efficient calorific value forecasting model, a method based on hybrid kernel function−support vector regression and genetic algorithms is presented in this paper. Firstly, key features of coal gangue gathered from major coal mines are measured and used to build a sample set. Then, the forecasting performance of single kernel function-based models is established, and linear kernel and Gaussian kernel functions are chosen according to forecasting results. Next, a hybrid kernel combined with the two kernel functions mentioned above is used to establish a calorific value forecasting model. In addition, a genetic algorithm is introduced to optimize critical parameters of SVR and the adjustable weight. Finally, the forecasting model based on hybrid kernel function−support vector regression and genetic algorithms is built to predict the calorific value of new c... [more]

The safety of power transmission systems in wind turbines is crucial to the wind turbine’s stable operation and has attracted a great deal of attention in condition monitoring of wind farms. Many different intelligent condition monitoring schemes have been developed to detect the occurrence of defects via supervisory control and data acquisition (SCADA) data, which is the most commonly applied condition monitoring system in wind turbines. Normally, artificial neural networks are applied to establish prediction models of the wind turbine condition monitoring. In this paper, an alternative and cost-effective methodology has been proposed, based on the group method of data handling (GMDH) neural network. GMDH is a kind of computer-based mathematical modelling and structural identification algorithm. GMDH neural networks can automatically organize neural network architecture by heuristic self-organization methods and determine structural parameters, such as the number of layers, the number... [more]

Over the past few years, there has been a significant increase in the interest in and adoption of solar energy all over the world. However, despite ongoing efforts to protect photovoltaic (PV) plants, they are continuously exposed to numerous anomalies. If not detected accurately and in a timely manner, anomalies in PV plants may degrade the desired performance and result in severe consequences. Hence, developing effective and flexible methods capable of early detection of anomalies in PV plants is essential for enhancing their management. This paper proposes flexible data-driven techniques to accurately detect anomalies in the DC side of the PV plants. Essentially, this approach amalgamates the desirable characteristics of ensemble learning approaches (i.e., the boosting (BS) and bagging (BG)) and the sensitivity of the Double Exponentially Weighted Moving Average (DEWMA) chart. Here, we employ ensemble learning techniques to exploit their capability to enhance the modeling accuracy a... [more]

The transition from the use of fossil fuels to renewable and green energy is a worldwide challenge that must be seriously considered in order to ensure sustainable development and the preservation of the environment. The conversion of wet biomasses (i.e., sewage sludge) into energy through thermochemical processes in general and hydrothermal carbonization (HTC) in particular has been pointed out as an interesting and attractive approach for the energetic and agricultural valorization of the produced solid residues, named hydrochars. The success of such valorization options is highly dependent on these hydrochars’ physico-chemical and energetic properties that are influenced not only by the type of the sludge (urban or industrial) and its nature (primary, secondary, or digested) but also by the HTC parameters, especially temperature, pressure, and residence time. This editorial provides a summary of the latest studies regarding the impact of the cited above parameters on the properties... [more]

In order to explore the development characteristics and influencing factors of microscale pores in lacustrine organic-rich muddy shale, this study selected five shale samples with different mineral compositions from the Qingshankou Formation in the Songliao Basin. The oil content and mineralogy of the shale samples were obtained by pyrolysis and X-ray diffraction analysis, respectively, while the porosity of the samples was computed by micro-CT imaging. Next, based on the CT images, the permeability of each sample was calculated by the Avizo software. Results showed that the continuous porosity of Qingshankou shale in the Songliao Basin was found between 0.84 and 7.79% (average 4.76%), the total porosity between 1.87 and 12.03% (average 8.28%), and the absolute permeability was calculated between 0.061 and 2.284 × 10−3 μm2. The total porosity of the samples has a good positive correlation with the continuous porosity and permeability. This means higher values of total porosity suggeste... [more]

Using thermal insulation materials to reduce energy loss in buildings is a key action. For reducing the building’s energy use, firstly, the internal unheated spaces (attics, cellars) should be insulated, followed by the insulation of the external walls, and changing the doors and windows. Finally, the building can be completed with the renovation/maintenance of its service systems. Newly designed and constructed buildings are subject to increasingly strict regulations, which highlight the minimization and elimination of wasteful energy use and the resulting emissions of harmful substances. Therefore, the use of thermal insulation is the first step in making buildings more energy efficient. In this editorial, seven articles covering thermal insulation possibilities and topics are highlighted. This paper reflected on the use of thermal insulations both for internal and external applications. This editorial also promotes the use of super insulation materials such as aerogels and vacuum in... [more]

One of the by-products of a mechanical-biological waste treatment plant is the under-sieve fraction, which requires separation prior to further processing of municipal mixed waste. This stream usually follows the fate of landfilling. Instead, it could be introduced to the hydrothermal carbonization (HTC) process to improve its fuel properties and become solid recovered fuel. The organic fraction and high moisture content (approximately 26%) of under-sieve fraction are favorable properties for the HTC process. In this study, hydrochars, the solid product of HTC, were produced at 200 and 220 °C with residence times of 1, 4, and 8 h. The main aim of this investigation was to establish the influence of different process parameters on hydrochars’ fuel properties. Thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) were employed in the analyses. The results confirmed the positive effects of hydrothermal carbonization on the... [more]

Owing to the various sources of complexity in the electrical power system, such as integrating intermittent renewable energy resources and widely spread nonlinear power system components, which result in sudden changes in the power system operating conditions, the conventional PID controller fails to track such dynamic challenges to mitigate the frequency deviation problem. Thus, in this paper, a fuzzy PI controller is proposed to enhance the automatic generation control system (AGC) against step disturbance, dynamic disturbance, and wind energy disturbance in a single area system. The proposed controller is initialized by using Equilibrium Optimization and proved its superiority through comparison with a classical PI optimized base. Results show that the fuzzy PI controller can reduce the peak-to-peak deviation in the frequency by 30−59% under wind disturbance, compared to a classical PI optimized base. Moreover, a fuzzy PID controller is also proposed and EO initialized in this paper... [more]

Quantitative accounting of greenhouse gas (GHG) emissions has become an important global focus. GHG emissions from the waste sector have high potential in GHG emissions reduction. We analyzed the GHG emissions inventory in the waste sector of the European Union, Germany, the United Kingdom, the United States of America, and Canada from 1990 to 2019. Landfill disposal was the main category of GHGs from the waste sector, with a contribution rate between 69% and 95%. Landfill disposal also played a prominent role in emission reduction, with a contribution rate higher than 86%. GHG emissions from landfill sites in China were calculated using the inventory analysis method recommended by the IPCC and combined with actual situations. The results showed that the highest GHG emissions from landfill disposal in China occurred in 2020, with an estimated 165 million tons of carbon dioxide (CO2) equivalent. In 2019, the per capita GHG emissions from landfill sites in China was 117 kg CO2 equivalent... [more]

This book is the result of a concerted effort to shed scientific light on the timely theme of “Smart Photovoltaic Energy Systems for a Sustainable Future” [...]

Economic feasibility analysis is essential in the decision-making process regarding investment in photovoltaic projects. Project profitability must be measured based not only on the costs and revenues, but also on the climatic particularities of the different locations. Therefore, performing simulations of technical and economic performance of photovoltaic models is fundamental. Thus, the objective of this study was to analyze deterministic and stochastic models of investments in two types of photovoltaic systems, one incorporated into the enterprise’s architecture (a BIPV system) and the other, a conventional one, in different Brazilian locations, covering the predominant climatic factors in the country. The methodological proposal consisted of choosing a city in Brazil with each predominant climate type and compiling its data on irradiation, monthly sunshine hours, and tariffs of the electric power concessionaire, to simulate the electrical generation performance of the proposed phot... [more]

In order to analyze the influence of uncertainty and an operation strategy on the reliability of a standalone microgrid, a reliability evaluation method based on a sequential Monte Carlo (SMC) simulation was developed. Here, the duty cycles of a microturbine (MT), the stochastic performance of photovoltaics (PV), and wind turbine generators (WTG) were considered. Moreover, the time-varying load with random fluctuation was modeled. In this method, the available capacity of an energy storage system (ESS) was also comprehensively considered by the SMC simulation. Then, the reliability evaluation framework was established from the perspectives of probability, frequency, and duration, and reliability evaluation algorithms under different operation strategies were formulated. Lastly, the influence of WTG and PV penetration and equipment capacity on the reliability was evaluated in the test system. The results showed that the complementary characteristics of wind and solar and the enhancement... [more]

An important engineering challenge is the design of a wind turbine’s pitch angle controller. The dependability, safety, and power output maximization of a wind turbine are all impacted by this controller. In this study, a 2 MW doubly fed induction generator wind turbine’s blade angle controller design with a novel fuzzy logic controller is tested in a simulated environment. The evolutionary algorithm technique is used to optimize the fuzzy logic controller with three inputs. A genetic algorithm is used to optimize the specified pitch angle controller for a number of coefficients. After the optimization process, the controller’s performance is assessed in terms of power output, overshoot, and steady-state error characteristics.

The modern power system is experiencing transformation from the rotational-generation-equipment-dominated system to a power-electronics-converter-dominated system, with the increasing penetration of renewable energy resources such as wind and photovoltaic. The power-electronics-based renewable generation, as well as energy storage system, can lead to the reduction of system inertia. As dc systems such as dc microgrids are attracting more attention, the low-inertia issues will challenge their stability. In this paper, a comprehensive review of inertia-enhancement methods in dc power systems is presented. The concept and significance of the inertia in dc systems is firstly introduced, and then the types of inertia-providing sources in dc systems are discussed. After that, the different virtual inertia control strategies applied in power electronics converters are classified and investigated. These virtual inertia control methods are proven to have a great ability to enhance the inertia o... [more]

The so-called porpoising is a well-known problem similar to bouncing that is affecting the dynamic behavior of basically all the field of 2022 Formula 1 racing cars. It is due to the extreme sensitivity of aerodynamic loads to ride height variations along a lap. Mid-way through the season race engineers are still struggling to cope with this phenomenon and its consequences, with regard to either physiological stress experienced by the drivers or to overall vehicle performance and stability. The paper introduces two kinds of models based on real-world chassis and aerodynamic data, where the above-mentioned downforce sensitivity has been arbitrarily recreated through the application of a decay function to aero maps. The first one is a quasi-static model, usually adopted as a trackside tool for controlling ride heights and aero balance, while the second, a fully dynamic model, recreates the interaction between oscillating aerodynamic loads and suspension dynamics resulting in a visible po... [more]

Capacity loss over time is a critical issue for lithium-ion batteries powering battery electric vehicles (BEVs) because it affects vehicle range and performance. Driving cycles have a major impact on the ageing of these devices because they are subjected to high stresses in certain uses that cause degradation phenomena directly related to vehicle use. Calendar capacity also impacts the battery pack for most of its lifetime with a capacity degradation. The manuscript describes experimental tests on a lithium-ion battery for electric vehicles with up to 10% capacity loss in the WLTP CLASS 3B driving cycle. The lithium-ion battery considered consists of an LMO-NMC cathode and a graphite anode with a capacity of 63 Ah for automotive applications. An internal impedance variation was observed compared to the typical full charge/discharge profile. Incremental capacitance (IC) and differential voltage (DV) analysis were performed in different states of cell health. A lifetime model is describe... [more]

This paper proposes an effective approach to solve renewable distributed generators (RDGs) and electric vehicle charging station (EVCS) allocation problems in the distribution system (DS) to reduce power loss (PLoss) and enhance voltage profile. The RDGs considered for this work are solar, wind and fuel cell. The uncertainties related to RDGs are modelled using probability distribution functions (PDF). These sources’ best locations and sizes are identified by the voltage stability index (VSI) and political optimization algorithm (POA). Furthermore, EV charging strategies such as the conventional charging method (CCM) and optimized charging method (OCM) are considered to study the method’s efficacy. The developed approach is studied on Indian 28 bus DS. Different cases are considered, such as a single DG, multiple DGs and a combination of DGs and EVs. This placement of multiple DGs along with EVs, considering proper scheduling patterns, minimizes PLoss and considerably improves the volt... [more]

The paper discusses the problem of cooperation between multiple model predictive control (MPC) systems. This approach aims at improving the control quality in electrical energy generation and forms the next step in a series of publications by the authors focusing on the optimization and control of electric power systems. Cooperation and cooperative object concepts in relation to a multi MPC system are defined and a cooperative control solution for a nuclear power plant’s turbine generator set is proposed. The aim of enabling information exchange between the controllers is to improve the performance of power generation. Presented and discussed simulation tests include various variants of information exchange between the turbine and synchronous generator MPC controllers of the nuclear power plant.

In this paper, a novel one-way single-wire power transfer structure is proposed. Different from the traditional single-wire power transfer system, power is one-way transmitted from the power source to the load, and no loop is constituted. The structure of one-way single-wire power transfer is studied in detail, and the influences of its length and shapes on the transmission efficiency are determined. Research shows that the length of the receiving structure plays a key role in improving the system’s efficiency, while the transmitting structure has a little effect. Based on ensuring transmission efficiency, the space volume optimization method is further applied. The expression of electromagnetic field distribution is derived theoretically, and the proposed structure is verified by simulation and experimental results.

As one of the key components, low-speed direct-drive in-wheel machines with high compact volume and high torque density are important for the traction system of electric vehicles (EVs). This paper introduces four different types of outer-rotor permanent magnet motors for EVs, including one five-phase SPM machine, one three-phase IPM machine with V-shaped PMs, one seven-phase axial flux machine (AFM) of sandwich structure and finally one hybrid flux (radial and axial) machine with a third rotor with V-shaped PMs added to the AFM. Firstly, the design criteria and basic operation principle are compared and discussed. Then, the key properties are analyzed using the Finite Element Method (FEM). The electromagnetic properties of the four fractional slot tooth concentrated winding in-wheel motors with similar dimensions are quantitatively compared, including air-gap flux density, electromotive force, field weakening capability, torque density, losses, and fault tolerant capability. The result... [more]

This paper presents an overview of the emerging trends in the development of electrical generators for large wind turbines. To describe the developments in the design of electrical generators, it is necessary to look at the conversion system as a whole, and then, the structural and mechanical performances of the drive train need to be considered. Many drive train configurations have been proposed for large wind turbines; they should ensure high reliability, long availability and reduced maintainability. Although most installed wind turbines are geared, directly driven wind turbines with permanent magnet generators have attracted growing interest in the last few years, which has been in parallel to the continuous increase of the per unit turbine power. The aim of this work is to present the recent commercial designs of electrical generators in large wind turbines. Both the strengths and weaknesses of the existing systems are discussed. The most emerging technologies in high-power, low-s... [more]

The Permian igneous rock in Shunbei Oilfield exhibits high rock strength, which results in a low rate of penetration (ROP) and shortens the cutter’s service life. It is necessary to analyze and evaluate the rock breaking effect of cutters. However, at this stage, the evaluation of the rock breaking effect has been limited to comparing the sizes of the mechanical specific energy (MSE), and the change in the rock breaking efficiency caused by the difference in the shape of the cutters’ surface has not been considered. Therefore, through the establishment of numerical simulation models of a circular cutter, bevel cutter, axe cutter, wedge cutter, and triangular cutter, the evaluation of the rock breaking efficiency of special-shaped cutters was completed. The results show that the triangular cutter and the wedge cutter are suitable for the front row cutter of the polycrystalline diamond compact bit (PDC); the triangular cutter is suitable for drilling into medium−hard formations, the wedg... [more]