The fluidized particle-in-tube solar receiver concept is promoted as an attractive solution for heating particles at high temperature in the context of the next generation of solar power tower. Similar to most existing central solar receivers, the irradiated part of the system, the absorber, is composed of tubes in which circulate the fluidized particles. In this concept, the bottom tip of the tubes is immersed in a fluidized bed generated in a vessel named the dispenser. A secondary air injection, called aeration, is added at the bottom of the tube to stabilize the flow. Contrary to risers, the particle mass flow rate is controlled by a combination of the overpressure in the dispenser and the aeration air velocity in the tube. This is an originality of the system that justifies a specific study of the fluidization regimes in a wide range of operating parameters. Moreover, due to the high value of the aspect ratio, the particle flow structure varies along the tube. Experiments were con... [more]

Although replacing biomass, (e.g., wood chips and pellets), with thinning wood and herbaceous biomass is eco-friendly and economically advantageous, their direct utilization in plant boilers is associated with ash-related challenges, including slagging and fouling. The aim of this study is to determine the effects of ash removal treatment (ashless biomass (ALB)) in the context of solid fuel power plant boilers. Ash was removed via neutralization of metal ions and carboxylic acids contained in the biomass ash. The ash removal rate of K, Na, Cl was indicated by assessing the total biomass before and after ash removal treatment, via XRF analysis. Co-combustion with sub-bituminous coal and ALB-treated biomass was analyzed using a drop tube furnace and revealed that NOx and SOx values converged converge toward an approximate 10 ppm error, whereas the Unburned Carbon (UBC) data did not exhibit a specific trend. Factors associated with slagging and fouling, (capture efficiency (CE), and energ... [more]

Since the slot opening is large in the uniform slot machine, the torque ripple generated by overlapping or misaligning with the rotor cavity is remarkably large in the case of interior permanent magnet (IPM) machine. In this work, it is observed that the magnitude of torque ripple depends strongly on the phase difference between air-gap field harmonics: The ripple is minimized when the two dominant harmonic components cancel each other. Based on this fact, a condition is developed to minimize torque ripple by adjusting the q-flux channel width and d-flux barrier width. The torque ripple minimizing solution is found from a level chart made by subdomain time-stepping analysis. Finite element analysis (FEA) also gives a very similar minimizing solution. A prototype machine is manufactured, and its performances are validated through experiments.

Cyclic solvent injection, known as solvent huff-n-puff, is one of the promising techniques for enhancing oil recovery from shale reservoirs. This study investigates the huff-n-puff performance in ultratight shale reservoirs by conducting large-scale numerical simulations for a wide range of reservoir fluid types (retrograde condensate, volatile oil, and black oil) and different injection gases (CO2, C2H6, and C3H8). A dual-porosity compositional model is utilized to comprehensively evaluate the impact of multicomponent diffusion, adsorption, and hysteresis on the production performance of each reservoir fluid and the retention capacity of the injection gases. The results show that the huff-n-puff process improves oil recovery by 4−6% when injected with 10% PV of gas. Huff-n-puff efficiency increases with decreasing gas-oil ratio (GOR). C2H6 provides the highest recovery for the black oil and volatile oil systems, and CO2 provides the highest recovery for retrograde condensate fluid typ... [more]

The major demand of energy in today’s world is fulfilled by the fossil fuels which are not renewable in nature and can no longer be used once exhausted. In the beginning of the 21st century, the limitation of the fossil fuels, continually growing energy demand, and growing impact of green-house gas emissions on the environment were identified as the major challenges with current energy infrastructure all over the world. The energy obtained from fossil fuel is cheap due to its established infrastructure; however, these possess serious issues, as mentioned above, and cause bad environmental impact. Therefore, renewable energy resources are looked to as contenders which may fulfil most energy requirements. Among them, hydrogen is considered as the most environmentally friendly fuel. Hydrogen is clean, sustainable fuel and it has promise as a future energy carrier. It also has the ability to substitute the present energy infrastructure which is based on fossil fuel. This is seen and projec... [more]

The penetration of solar energy in the modern power system is still increasing with a fast growth rate after long development due to reduced environmental impact and ever-decreasing photovoltaic panel cost. Meanwhile, distribution networks have to deal with a huge amount and frequent fluctuations of power due to the intermittent nature of solar energy, which influences the grid stability and could cause a voltage rise in the low-voltage grid. In order to reduce these fluctuations and ensure a stable and reliable power supply, energy storage systems are introduced, as they can absorb or release energy on demand, which provides more control flexibility for PV systems. At present, storage technologies are still under development and integrated in renewable applications, especially in smart grids, where lowering the cost and enhancing the reliability are the main tasks. This study reviews and discusses several active power control strategies for hybrid PV and energy storage systems that de... [more]

Combustion of energy fuels or organic waste is associated with the emission of harmful gases and aerosols into the atmosphere, which strongly affects air quality. Air quality monitoring devices are unreliable and measurement gaps appear quite often. Missing data modeling techniques can be used to complete the monitoring data. Concentrations of monitored pollutants can be approximated with regression modeling tools, such as artificial neural networks. In this study, a long-term set of data from the air monitoring station in Zabrze (Silesia, South Poland) was analyzed. Concentration prediction was tested for the main air pollutants, i.e., O3, NO, NO2, SO2, PM10, CO. Multilayer perceptrons were used to model the concentrations. The predicted concentrations were compared to the observed ones to evaluate the approximation accuracy. Prediction errors were calculated separately for the whole concentration range as well as for the specified concentration subranges. Some different measures of e... [more]

Battery Management System (BMS) design for Lithium-ion batteries State of Charge (SoC) prediction has a crucial role in Electric Vehicles (EVs) and smart grids development. The need to design compact, light and fast devices requires finding a suitable trade-off between effectiveness and efficiency. In the literature, it is well emphasized that the application of electrochemical-based methods such as the Pseudo-Two-Dimensional (P2D) model is computationally prohibitive and requires significant simplifications. Conversely, plain Equivalent Circuit Models (ECM) are too simple and unable to represent the cell dynamics. The application of an Ensemble Neural Network (ENN) as Equivalent Neural Network Circuit (ENNC) emerged as a promising solution able to synthesize expressive and computationally efficient models. Indeed, with the support of a suitable dataset, an ENN can be configured to represent a given ECM, modeling each lumped parameter through an assigned Neural Network (NN). Accordingl... [more]

With recent advances in offshore floating wind and wave energy technology, questions have emerged as to whether the two technologies can be combined to reduce their overall levelised cost of energy. In this paper, the potential for combining a floating offshore wind turbine to a point absorbing wave energy converter is investigated. The focus of the investigation is how much power might be produced by a combined floating wind and wave energy converter system, and the resultant changes in motion of the floating wind platform. A model for the combined wave and wind system is developed which uses the standardised NREL OC3 5 MW spar type wind turbine and a cylindrical buoyant actuator (BA), which is attached to the spar via a generic wave power take-off system (modelled as a spring-damper system). Modelling is conducted in the frequency domain and the tests span a wide range of parameters, such as wave conditions, BA sizes, and power take-off coupling arrangements. It is found that the opt... [more]

This study assessed the entrained flow co-gasification characteristics of coal and biomass using thermodynamic equilibrium modelling. The model was validated against entrained flow gasifier data published in the literature. The gasification performance was evaluated under different operating conditions, such as equivalence ratio, temperature, pressure and coal to biomass ratio. It is observed that the lower heating value (LHV) and cold gas efficiency (CGE) increase with increasing temperature until the process reaches a steady state. The effect of pressure on syngas composition is dominant only at non-steady state conditions (<1100 °C). The variation in syngas composition is minor up to the blending of 50% biomass (PB50). However, the PB50 shows a higher LHV and CGE than pure coal by 12%and 18%, respectively. Overall, biomass blending of up to 50% favours gasification performance with an LHV of 12 MJ/kg and a CGE of 78%.

Control rods (CRs) have a significant influence on reactor performance. Withdrawal of a control rod leaves a region of the core significantly changed due to lack of absorber, leading to increased fission rate and later to Xe135 buildup. In this paper, an innovative concept of structured control rods made of tungsten is studied. It is demonstrated that the radial division of control rods made of tungsten can effectively compensate for the reactivity loss during the irradiation cycle of high-temperature gas-cooled reactors (HTGRs) with a prismatic core while flattening the core power distribution. Implementation of the radial division of control rods enables an operator to reduce this effect in terms of axial power because the absorber is not completely removed from a reactor region, but its amount is reduced. The results obtained from the characteristic evolution of the reactor core for CRs with a structured design in the burnup calculation using the refined timestep scheme show a very... [more]

Warm plasma techniques are considered a promising method of tar removal in biomass-derived syngas. The fate of another problematic syngas impurity—hydrogen sulfide—is studied in this work. It is revealed that processing simulated syngas with a microwave plasma results in hydrogen sulfide conversion. For different gas flow rates (20−40 NLPM) and hydrogen sulfide concentrations ranging from 250 ppm to 750 ppm, the conversion rate varies from ca. 26% to 45%. The main sulfur-containing products are carbon disulfide (ca. 30% of total sulfur) and carbonyl sulfide (ca. 8% of total sulfur). Besides them, significantly smaller quantities of sulfates and benzothiophene are also detected. The main components of syngas have a tremendous impact on the fate of hydrogen sulfide. While the presence of carbon monoxide, methane, carbon dioxide, and tar surrogate (toluene) leads to the formation of carbonyl sulfide, carbon disulfide, sulfur dioxide, and benzothiophene, respectively, the abundance of hydr... [more]

Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare... [more]

The main idea of a circular economy (CE) is to separate economic growth from resource consumption and environmental impacts. The characteristic approach of a CE assumes the minimisation of the amount of waste generated at the design level and, as a standard, includes innovations throughout the value chain. From an agricultural point of view, agricultural biogas plants are particularly important because they enable the management of all waste biomass and its conversion into useful energy and agricultural fertiliser. This paper presents methods for assessing the economic effectiveness of an investment in an agricultural biogas plant. The research goal was to develop a financial model. The authors of this study used available examples of the profitability of commercial ventures. We considered the investment aspects of agricultural biogas plants. Exemplary solutions are discussed, allowing the reader to become acquainted with various methods and proposals for thus far estimated investments... [more]

The necessity for the utilization of microgrids emerges from the integration of distributed energy resources, electric vehicles, and battery storage systems into the conventional grid structure. In order to achieve a proper operation of the microgrid, the presence of a microgrid control system is crucial. The IEEE 2030.7 standard defines the microgrid control system as a key element of the microgrid that regulates every aspect of it at the point-of-interconnection with the distribution system, and autonomously manages operations such as the transitions of operating modes. In this paper, a microgrid control system is developed to achieve real-time monitoring and control through a centralized approach. The controller consists of a centralized server and advanced field units that are also developed during this work. The control functions of the centralized server ensure the proper operation during grid-connected and island modes, using the real-time data received via the advanced field un... [more]

Significant negative impact caused by climate changes, such as economy and life losses, has been experienced globally in recent years, which has called for imminent development and adoption of low carbon technologies in order to mitigate the impact. In 2020, the Chinese government outlined the ‘Dual Carbon’ Goal where its carbon emission will peak before 2030 whilst China will become ‘Carbon Neutral’ before 2060. In China, the amount of carbon emissions from the transportation industry stands in second place and it is predicted that the carbon emission of China’s automobile industry will reach between 21.5 and 30 billion tons in 2030. Actions should be taken as quickly as possible to facilitate the transition from traditional fossil fuel vehicles to low carbon vehicles such as electric vehicles in order to reduce carbon emissions effectively. Based on the questionnaire that is designed to survey the electrification of online ride-hailing vehicles, this paper first establishes a consume... [more]

Short-Term Load Forecasting is critical for reliable power system operation, and the search for enhanced methodologies has been a constant field of investigation, particularly in an increasingly competitive environment where the market operator and its participants need to better inform their decisions. Hence, it is important to continue advancing in terms of forecasting accuracy and consistency. This paper presents a new deep learning-based ensemble methodology for 24 h ahead load forecasting, where an automatic framework is proposed to select the best Box-Jenkins models (ARIMA Forecasters), from a wide-range of combinations. The method is distinct in its parameters but more importantly in considering different batches of historical (training) data, thus benefiting from prediction models focused on recent and longer load trends. Afterwards, these accurate predictions, mainly the linear components of the load time-series, are fed to the ensemble Deep Forward Neural Network. This flexib... [more]

This paper develops the coordination structure and method for utilizing flexibilities in a Micro-Grid (MG), an Active Distribution Network (ADN) and a Transmission Grid (TG), which can play an essential role in addressing the uncertainties caused by renewable energy power generation (REPG). For cooperative dispatching, both flexibilities and uncertainties on the interface of MG−ADN and ADN−TG are portrayed in unified forms utilizing robust optimization (RO), based on the modified equipment-level model of flexible resources. The Constraint-and-Column Generation method is adopted to solve the RO control problems. Simulations on the modified IEEE case-6 and case-33 systems are carried out. The results suggest that the proposed algorithm can exploit flexible resources in both an MG and an ADN, improving the economy and promoting REPG consumption within each level (MG, ADN and TG) while reducing uncertainties and providing flexibilities for superior operators.

Metal−air batteries are a promising technology that could be used in several applications, from portable devices to large-scale energy storage applications. This work is a comprehensive review of the recent progress made in metal-air batteries MABs. It covers the theoretical considerations and mechanisms of MABs, electrochemical performance, and the progress made in the development of different structures of MABs. The operational concepts and recent developments in MABs are thoroughly discussed, with a particular focus on innovative materials design and cell structures. The classical research on traditional MABs was chosen and contrasted with metal−air flow systems, demonstrating the merits associated with the latter in terms of achieving higher energy density and efficiency, along with stability. Furthermore, the recent applications of MABs were discussed. Finally, a broad overview of challenges/opportunities and potential directions for commercializing this technology is carefully di... [more]

This paper focuses on the methods that ensure the rotor angle stability of electric power systems, which is most frequently analyzed with small-signal models. Over the past several decades, power system stabilizers (PSSs) for conventional excitation systems were the main tools for improving the small-signal stability of electromechanical oscillatory modes. In the last decade, power oscillation damping (POD) control implemented in photovoltaic (PV) inverters has been considered an alternative to PSSs. As PV generation undergoes massive rollout due to policy directions and renewable energy source integration activities, it could potentially be used as a source of damping, which is crucial for sustaining the rotor angle stability of the remaining in-service synchronous generators. Several studies have already been dedicated to the development of different damping strategies. This paper contributes to the existing research in power system stability by providing a comprehensive review of th... [more]

This study evaluated the CO2 sequestration potential with combustion ashes in the aqueous phase. The aim was to provide a cost-effective carbon sequestration method for combustion unit operators (flue gas cleaning) or biogas producers (biogas upgrading). Therefore, two separate test series were executed to identify the carbonation efficiency (CE) of bottom wood ash (1) at different mixing ratios with water in batch experiments and (2) under dynamic flow conditions. It was furthermore evaluated whether subsequent use of the carbonated wood ash for soil amendment could be possible and whether the process water could be passed into the sewage. The batch test series showed that different mixing ratios of wood ash and water had an influence on the CE. The flow series showed that the mean CE varied between approximately 14% and 17%. Thus, the ash proved to be suitable for carbonation processes. The process water was dischargeable, and the carbonated wood ash has potential for chalking, as no... [more]

The focus of this work is to computationally obtain an optimized neural network (NN) model to predict battery average Nusselt number (Nuavg) data using four activations functions. The battery Nuavg is highly nonlinear as reported in the literature, which depends mainly on flow velocity, coolant type, heat generation, thermal conductivity, battery length to width ratio, and space between the parallel battery packs. Nuavg is modeled at first using only one hidden layer in the network (NN1). The neurons in NN1 are experimented from 1 to 10 with activation functions: Sigmoidal, Gaussian, Tanh, and Linear functions to get the optimized NN1. Similarly, deep NN (NND) was also analyzed with neurons and activations functions to find an optimized number of hidden layers to predict the Nuavg. RSME (root mean square error) and R-Squared (R2) is accessed to conclude the optimized NN model. From this computational experiment, it is found that NN1 and NND both accurately predict the battery data. Six... [more]

To research the chaotic motion problem of the direct-drive permanent magnet synchronous generator (D-PMSG) for a wind turbine with uncertain parameters and fractional order characteristics, a control strategy established upon fuzzy state feedback is proposed. Firstly, according to the working mechanism of D-PMSG, the Lorenz nonlinear mathematical model is established by affine transformation and time transformation. Secondly, fractional order nonlinear systems (FONSs) are transformed into linear sub-model by Takagi−Sugeno (T-S) fuzzy model. Then, the fuzzy state feedback controller is designed through Parallel Distributed Compensation (PDC) control principle to suppress the chaotic motion. By applying the fractional Lyapunov stability theory (FLST), the sufficient conditions for Mittag−Leffler stability are formulated in the format of linear matrix inequalities (LMIs). Finally, the control performance and effectiveness of the proposed controller are demonstrated through numerical simul... [more]

Power electronics medium-voltage (MV) systems must comply with the requirements defined in grid codes. These systems’ compatibility with the standards can be validated by specialized testing equipment: grid simulators. This paper presents a hardware in the loop (HiL) implementation and the simulation results of a MV multiphase DC/DC converter designed for MV DC grid emulation. By using ABB’s reliable, patented power converter hardware topology (US 10978948 B2) and by applying advanced control algorithms, the presented system can be used for special purposes, such as the emulation of fault events in a DC-grid used for the certification of other devices, or for other research goals. The presented concept of a power electronics DC-grid simulator (PEGS-DC) is characterized by high power capability and high voltage quality. In this paper, the general idea of a power electronics grid simulator applied for the testing of MV electrical systems is discussed. Then, details related to the PEGS-DC... [more]

Machine learning (ML) models are commonly used in solar modeling due to their high predictive accuracy. However, the predictions of these models are difficult to explain and trust. This paper aims to demonstrate the utility of two interpretation techniques to explain and improve the predictions of ML models. We compared first the predictive performance of Light Gradient Boosting (LightGBM) with three benchmark models, including multilayer perceptron (MLP), multiple linear regression (MLR), and support-vector regression (SVR), for estimating the global solar radiation (H) in the city of Fez, Morocco. Then, the predictions of the most accurate model were explained by two model-agnostic explanation techniques: permutation feature importance (PFI) and Shapley additive explanations (SHAP). The results indicated that LightGBM (R2 = 0.9377, RMSE = 0.4827 kWh/m2, MAE = 0.3614 kWh/m2) provides similar predictive accuracy as SVR, and outperformed MLP and MLR in the testing stage. Both PFI and SH... [more]