The measurement of the higher heating value (HHV) of municipal solid wastes (MSWs) plays a key role in the disposal process, especially via thermochemical approaches. An optimized multi-variate grey model (OBGM (1, N)) is introduced to forecast the MSWs’ HHV to high accuracy with sparse data. A total of 15 cities and MSW from the respective city were considered to develop and verify the multi-variant models. Results show that the most accurate model was POBGM (1, 5) of which the least error measured 5.41% MAPE (mean absolute percentage error). Ash, being a major component in MSW, is the most important factor affecting HHV, followed by volatiles, fixed carbon and water contents. Most data can be included by using the prediction interval (PI) method with 95% confidence intervals. In addition, the estimations indicated that the MAPE from estimating the HHV for various MSW samples, collected from various cities, were in the range of 3.06−34.50%, depending on the MSW sample.

This paper elaborates on a development technique for the grid-connected voltage source converter (VSC). We propose a simulation technique in the MATLAB/Simulink environment that emulates the operation of the discrete-time controlled grid-connected VSC. The switched-circuit modeling approach is used for simulation of the power stage in the continuous-time domain with the physical unit scale. The discrete-time control algorithm is implemented in an interpreted MATLAB function in the per-unit scale, which synchronizes with the switching period. Such a control algorithm is easily translated into the C language for programing of the 32-bit C2000 DSP controller with the same regulators’ parameters. The proposed platform was validated with a hardware-in-the-loop real-time simulator and with a 5-kVA 3-phase LCL-filtered grid-connected VSC. The discrete-time control scheme was implemented in the synchronous reference frame control with proportional-integral with multi-resonant controllers at ha... [more]

Engineering human-centric urban transport systems should be carried out using information technology in forecasting traffic and passenger flows. One of the most important objects of urban transport systems’ progress is modeling patterns of transport flows and their distribution on the road network. These patterns are determined by the subjective choice of city residents of traffic routes using public and private transport. This study aimed to form a sequence of stages of modeling transport and passenger flows in human-centric urban transport systems and passenger flows in the human-centric urban intelligent transport systems and to determine the patterns of change to the gravity function of employees of municipal services. It was revealed that the trip distribution function of workers of urban service enterprises can be described by the attributes of the structure of the city, socio-economic data, and attributes characterizing the zones and its residents.

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurati... [more]

Evaporative cooling is a promising concept to improve proton exchange membrane fuel cells. While the particular concept based on gas diffusion layers (GDLs) modified with hydrophilic lines (HPILs) has recently been demonstrated, there is a lack in the understanding of the mass and heat transport processes. We have developed a 3-D, non-isothermal, macro-homogeneous numerical model focusing on one interface between a HPIL and an anode gas flow channel (AGFC). In the base case model, water evaporates within a thin film adjacent to the interfaces of the HPIL with the AGFC and with the hydrophobic anode GDL. The largest part of the generated water vapor leaves the cell via the AGFC. The transport to the cathode side is shown to be partly limited by the ab-/desorption into/from the membrane. The cooling due to the latent heat has a strong effect on the local evaporation rate. An increase of the mass transfer coefficient for evaporation leads to a transport limited regime inside the MEA while... [more]

Alkaline electrolyzers are the most widespread technology due to their maturity, low cost, and large capacity in generating hydrogen. However, compared to proton exchange membrane (PEM) electrolyzers, they request the use of potassium hydroxide (KOH) or sodium hydroxide (NaOH) since the electrolyte relies on a liquid solution. For this reason, the performances of alkaline electrolyzers are governed by the electrolyte concentration and operating temperature. Due to the growing development of the water electrolysis process based on alkaline electrolyzers to generate green hydrogen from renewable energy sources, the main purpose of this paper is to carry out a comprehensive survey on alkaline electrolyzers, and more specifically about their electrical domain and specific electrolytic conductivity. Besides, this survey will allow emphasizing the remaining key issues from the modeling point of view.

The work aimed to solve the problem of determining, validating, and transferring model parameters of flooding using chemical enhanced oil recovery (EOR) from a core experiment to a full-scale hydrodynamic model. For this purpose, a digital hydrodynamic model describing the process of oil displacement by the surfactant and polymer solution on the core is created and the digital model is matched to achieve convergence with the historical data. This approach allows the uncertainties associated with the limited number of experiments to be removed to fully describe the parameters of the chemical surfactant polymer flooding model and form a database that could subsequently be replicated at various field sites, having the composition of reservoir fluids and distribution of rock composition in the core material as the basis. Besides, the digital model allows for verification of physical and chemical properties of surfactants and polymers, values of the adsorption of chemical agents on rocks, a... [more]

In this work, performance analysis and comparison of three photovoltaic technologies are carried out in the Louisiana climate. During the calendar year of 2018, the University of Louisiana at Lafayette constructed and commissioned a 1.1 MW solar photovoltaic power plant for researching solar power in southern Louisiana and for partial energy demand of the university. It was one of the largest solar photovoltaic power plants in Louisiana when constructed and receives an annual solar insolation of 4.88 kWh/m2/d at latitude minus five degrees (25°) tilt. The solar power plant has a total of 4142 modules and incorporates three module technologies. Preliminary performance data from the system level are presented. The evaluation of different technologies is based on final yield, performance ratio, and capacity factor for one year from September 2019 to August 2020. An economic analysis is carried out using levelized cost of energy for the three photovoltaic (PV) technologies. Finally, the re... [more]

The modelling of Linear Fresnel Collectors (LFCs) is crucial in order to predict accurate performance for annual yields and to define proper commands to design the suitable controller. The ISO 9806 modelling, applied to thermal collectors, presents some gaps especially with concentration collectors including LFCs notably due to the factorisation of the incidence angle modifiers and the fact that they are considered symmetric around the south meridian. The present work details the use of two alternative modellings methodologies based on recorded experimental data on the solar system installed at the Cyprus Institute, in the outskirts of Nicosia, Cyprus. The first modelling is the RealTrackEff, which is an improved ISO9806 modelling, and the second is constructed using the CARNOT blockset in MATLAB/Simulink. Both models include all the elements of the heat transfer fluid loop, i.e., mineral oil, with a tank and a heat-exchanger. First, the open loop’s studies demonstrated that the root m... [more]

This article approaches the optimal solution of energy sustainability based on the use of artificial intelligence (AI). The application of renewable energy sources (RES) and unit commitment (UC) is the basic idea of this concept. Therefore, a new approach to solving the UC problem is introduced. The proposed method has a simple procedure to obtain the popular solutions in an acceptable time interval, by creating a basic model of the schedule of the state of energy units RES. It is obvious that individual consumer units, of an operational nature, take hourly performance values by performing economic evaluations on them in the sense of cost optimization. This is conducted through an artificial intelligence (AI) algorithm by optimizing the dedicated cost function, simulated by annealing. Despite the acceptable solution obtained from these two steps, another shift is proposed, called the TDD process in a given consumer area. This process in the application of AI in the system of selection... [more]

A heat pump for simultaneous heating and cooling (HPS) is a refrigeration machine by which the productions of heating and cooling energies are simultaneously valorized. This introductory article presents the uses of heat pump productions under the form of an analysis of thermal demands of different types of buildings and a literature review of real installations and experimental systems, which are the basis of the construction of numerical models. The applications of HPSs are diverse: space heating and cooling, domestic hot water (DHW), hot water for desalination process, etc. Means and methods for improving the performance of refrigeration cycles and the management of heat and cold productions are developed, including modeling and simulation. New refrigeration circuit architectures were designed. A focus is paid on refrigerants. Prototypes combining heating-cooling, heating-cooling-DHW and cooling-desalination have been developed, built and tested to validate the models. Even though a... [more]

The aim of this work is to propose a methodology to obtain an effectiveness factor for biofilm in a microbial electrolysis cell (MEC) system and use it to reduce a partial differential equation (PDE) biofilm MEC model to an ordinary differential equation (ODE) MEC model. The biofilm mass balances of the different species are considered. In addition, it is considered that all the involved microorganisms are attached to the anodic biological film. Three effectiveness factors are obtained from partial differential equations describing the spatial distributions of potential and substrate in the biofilm. Then, a model reduction is carried out using the global mass balances of the different species in the system. The reduced model with three uncertain but bounded effectiveness factors is evaluated numerically and analyzed in the sense of stability and parametric sensibility to demonstrate its applicability. The reduced ODE model is compared with a validated model taken from the literature, a... [more]

This study presents the modeling of wood chips pyrolysis, considering the initial moisture content and taking into account the near-parallelepiped geometry of common wood chips, which is not available among the simulated shapes of wood in the literature. The goal is to extend the research and generate useful data on how different varieties of shapes and initial moisture contents influence wood chips pyrolysis. The effects of temperature and thickness variation on the pressure of volatile products, core temperature, and densities of pyrolysis products were studied. The model was validated with the mass fraction of experimental data obtained from beechwood chips with a density of 700 kg/m3 and thickness of 10 mm−30 mm at 973.15 K−1273.15 K. The mean absolute error (MAE) and mean relative error (MRE) values were, respectively, 0.066 and 10.376% at 973.15 K, and 0.065 and 22.632% at 1273.15 K. High temperature favored the rate of biocharcoal production from the surface to the core, though... [more]

Grid-powered pumping plants are widespread electromechanical systems commonly set in motion by electrical machines. The productivity of these electromechanical systems varies substantially according to the shift of the location of the working point on the H-Q plane, which is determined with the help of mutual positions of the characteristics of the pump unit itself and the hydraulic parameters of the pipeline. The topic of the proposed article is mainly focused on the investigation of pumping plant productivity equipped with two various types of electrical machines known as induction and synchronous reluctance motors. A simulation method of efficiency prediction of a centrifugal pumping plant for flow regulation is proposed. The described Simulink/Matlab simulation approach is quite valuable for validating efficiency in the case of pumping plants supplied with various types of electrical machines. The data relating to the electrical machines’ efficiency estimation were obtained during... [more]

The “Clean Energy for all Europeans” package highlights the need to create a resilient critical energy infrastructure in the European Union. Resilience is an emerging term to describe the energy system’s ability to withstand shocks caused by natural hazards, technical accidents, or intentional threats. In this paper, a framework to assess the resilience of energy systems using quantitative indicators is presented. Two main groups of resilience indicators are proposed that depend on what is being measured within the energy system: capacity (attribute-based) indicators or performance in the presence of disruption (performance-based) indicators. This study concentrates on the first resilience phase, when the energy system has to absorb the impact of the shock. The approach considers various disruptions (both internal and external) as triggering events. There is a particular focus on future shocks affecting the prospective energy system, which will have changed with respect to the current... [more]

Biomass pyrolysis is considered as a thermochemical conversion system that is performed under oxygen-depleted conditions. A large body of literature exists in which thermodynamic equilibrium (TE) and kinetic approaches have been applied to predict pyrolysis products. However, the reliability, accuracy and predictive power of both modeling approaches is an area of concern. To address these concerns, in this paper, two new simulation models based on the TE and kinetic approaches are developed using Aspen Plus, to analyze the performance of each approach. Subsequently, the results of two models are compared with modeling and experimental results available in the literature. The comparison shows that, on the one hand, the performance of the TE approach is not satisfactory and cannot be used as an effective way for pyrolysis modeling. On the other hand, the results generated by the new model based on the kinetic approach suggests that this approach is suitable for modeling biomass pyrolysis... [more]

This article surveys the mathematical principles essential for understanding the thermal management of Li-ion batteries, the current technological state of the art, and the solution. Since the thermal management of electric drive vehicles has environmental, economic, and safety impacts, this review focuses on the efficient methods of battery thermal management (BTM) that were proposed to overcome the major challenges in the electric vehicle industry. The first section examines the perspective of battery-driven vehicles, the principles of Li-ion batteries with a thermal runaway, and their implication for battery safety. The second section discusses mathematical approaches for effective BTM modeling, including the thermal-fluidic network model, lumped capacitance model, spatial resolution lumped capacitance model, equivalent circuit model, impedance-based model, and data-driven model. The third section presents the current state-of-the-art technologies, including air-based, liquid-based,... [more]

The present work mainly developed a mathematical model based on the plug flow model and coarse fly ash particles’ fragmentation model to describe the behavior and evolution of ash formation and the influence of the biomass feeding rate and flue gas cooling rate on ash properties, which is validated by literature data. The model considers homogeneous nucleation of alkali vapors, heterogeneous condensation of vapors on newly formed particles and fly ash particles, and collision-coagulation between aerosol particles, which is also applied to numerically study and analyze the ash formation characteristics in the cases of practical boiler pulverized fuel combustion and SO2 sulfation. The results show that the mathematical model can reasonably describe the ash formation and the influence of the biomass feeding rate and the flue gas cooling rate on the mass PSDs of PM10 and its elements. The initial nucleation temperature and initial nucleation particle size increase with the biomass feeding... [more]

While the contribution of renewable energy technologies to the energy system is increasing, so is its level of complexity. In addition to new types of consumer systems, the future system will be characterized by volatile generation plants that will require storage technologies. Furthermore, a solid interconnected system that enables the transit of electrical energy can reduce the need for generation and storage systems. Therefore, appropriate methods are needed to analyze energy production and consumption interactions within different system constellations. Energy system models can help to understand and build these future energy systems. However, although various energy models already exist, none of them can cover all issues related to integrating renewable energy systems. The existing research gap is also reflected in the fact that current models cannot model the entire energy system for very high shares of renewable energies with high temporal resolution (15 min or 1-h steps) and hi... [more]

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine tot... [more]

Data-driven normal behaviour models have gained traction over the last few years as a convenient way of modelling turbine operational health to detect anomalies. By leveraging high-dimensional operational relationships, temperature thresholds can be automatically calculated based on each individual turbine unique operating envelope, in theory minimising false alarms and providing more reliable diagnostics. The aim of this work is to provide further insight into practical uses and limitations of implementing normal behaviour temperature models in practice, to inform practitioners, as well as assist in improving wind turbine generator fault detection systems. Results suggest that, on average, as little as two months of data are adequate to produce stable temperature alarm thresholds, with the worst case example requiring approximately 200−290 days of data depending on the component and desired convergence criteria.

The evolution of changes in shopping in the modern society necessitates suppliers to seek new solutions consisting of increasing the efficiency of transport processes. When it comes to controlling the flow of goods in modern distribution networks, planning and timely deliveries are of particular importance. The first factor creating a competitive advantage involves the tendency to shorten order delivery times, especially for products with a short shelf life. Shorter delivery times, in turn, extend the period of effective residence of the product “available on the shelf”, increasing the likelihood of its sale. The second component in line with the Sustainable Development Strategy consists of aspects related to the protection of the natural environment, in particular those related to car transport. In this case, the fuel consumption and the level of emitted toxic substances (including carbon dioxide) are analyzed and assessed. Bearing in mind the above, this article presents the problem... [more]

This paper proposes a methodology for numerical modeling of terraforming Mars’ atmosphere using high-energy asteroid impact and greenhouse gas production processes. The developed simulation model uses a spatial data science approach to analyze the Global Climate Model of Mars and cellular automata to model the changes in Mars’ atmospheric parameters. The developed model allows estimating the energy required to raise the planet’s temperature by sixty degrees using different variations of the terraforming process. Using a data science approach for spatial big data analysis has enabled successful numerical simulations of global and local atmospheric changes on Mars and an analysis of the energy potential required for this process.

Fluid bed granulation is faced with a high level of complexity due to the simultaneous occurrence of agglomeration, breakage, and drying. These complexities should be thoroughly investigated through particle−particle, particle−droplet, and particle−fluid interactions to understand the process better. The present contribution focuses on the importance of drying and the associated challenges when modeling a granulation process. To do so, initially, we will present a summary of the numerical approaches, from micro-scale to macro-scale, used for the simulation of drying and agglomeration in fluid bed granulators. Depending on the modeled scale, each approach features several advantages and challenges. We classified the imposed challenges based on their contributions to the drying rate. Then, we critically scrutinized how these challenges have been addressed in the literature. Our review identifies some of the main challenges related to (i) the interaction of droplets with particles; (ii) t... [more]

Using the mixture of carbonized rice husk and shungite from the Kazakhstan Koksu deposit and the experimentally determined oil sorption capacity from contaminated soil with oil originating in the Karazhanbas oil field, a set of Artificial Neural Network (ANN) models were built for sorption predictions. The ANN architecture design, training, validation and testing methodology were performed, and the sorption capacity prediction was evaluated. The ANN models were successfully trained for capturing the sorption capacity dependence on time and on a carbonized rice husk and shungite mixture ratio for the 10% and 15% oil-contaminated soil. The best trained ANNs revealed a very good prediction capability for the testing data subset, demonstrated by the high coefficient of the determination values of R2 = 0.998 and R2 = 0.981 and the mean absolute percentage errors ranging from 1.60% to 3.16%. Furthermore, the ANN sorption models proved their interpolation ability and utility for predicting th... [more]