The energy crisis caused by global structural changes in the economic sphere is the cause accelerating the energy transition based on the concept of sustainable development. This study is to test the hypothesis about the incentive effect of tax expenditures on alternative energy and energy conservation. The objects of empirical research are the EU, OECD countries, OECD partner countries and Russia from 2018−2020. The tools of scientific research are based on methods of economic−statistical and comparative analysis and expert judgments. The concept of tax expenditures in terms of decarbonization is analyzed using a systematic approach. The integrated methodological approach shows the relationship between the tax policy and government strategies in achieving sustainable development goals to ensure the transition to rational energy consumption patterns and sustainable energy sources. The authors analyze incentives for the energy sector and alternative energy sources in the considered grou... [more]

This paper presents a comprehensive model predictive control (CMPC) method to control a three-phase four-legged inverter (TP4LI) for PV systems. The proposed TP4LI model aims to predictively model and control switching frequency and higher voltage/current switching to reduce losses. The CMPC model can be operated in four modes, namely standard MPC mode (Mode I), switching frequency reduction (SFR) mode (Mode II), high voltage/current switching loss reduction (SLR) mode (Mode III), and SFR plus SLR mode (Mode IV, a combination of Modes II and III). The proposed CMPC approach controls the TP4LI to (1) successfully track balanced and unbalanced reference currents with balanced or unbalanced loads; (2) reduce switching losses; and (3) keep the generated current total harmonic distortion (THD) within the industry’s recommended limits. The TP4LI model with the CMPC approach was verified and validated in the MATLAB/Simulink for a PV system. The simulation results show good tracking and perfor... [more]

The maintenance paradigm has evolved over the last few years and companies that want to remain competitive in the market need to provide condition-based maintenance (CBM). The diagnosis and prognosis of the health status of equipment, predictive maintenance (PdM), are fundamental strategies to perform informed maintenance, increasing the company’s profit. This article aims to present a diagnosis and prognosis methodology using a hidden Markov model (HMM) classifier to recognise the equipment status in real time and a deep neural network (DNN), specifically a gated recurrent unit (GRU), to determine this same status in a future of one week. The data collected by the sensors go through several phases, starting by cleaning them. After that, temporal windows are created in order to generate statistical features of the time domain to better understand the equipment’s behaviour. These features go through a normalisation to produce inputs for a feature extraction process, via a principal comp... [more]

An adaptive matrix inverse (AMI) method is presented to identify the temperature and unknown boundary heat flux in a domain of a regular or irregular shape with temperature-dependent properties. The nonlinear problem is broken down into a number of linear submodels, and for each submodel, the temperature is obtained in measuring points. Next, based on the matching degree between the temperatures measured and calculated by each prediction submodel, the submodels are weighted and combined to create the full model for the solution of an inverse nonlinear heat transfer problem. Comparisons are also made with the existing multiple model adaptive inverse (MMAI) algorithm and method based on the Levenberg−Marquardt algorithm (LMA). The results of the presented numerical tests for undisturbed and disturbed “measuring” data indicate that the heat fluxes identified by the AMI method are close to the exact values. The application of the presented method for bodies with an irregular shape is also... [more]

Power grids are a combined system where the electrical energy produced by the power plants is transmitted to consumers. This forms a specific interdependence where the recipients have a significant impact on the power quality. Therefore, the nonlinear loads connected by households and industrial customers cause current and voltage distortion in the power networks. This creates the need for accurate measurement of nonsinusoidal voltage and current composed not only from the fundamental component but also containing higher harmonics, interharmonics, and subharmonics. In order to ensure high transformation accuracy of distorted current and voltage, the inductive instrument transformers have to be tested in these conditions. Many papers describe their behavior during the transformation of sinusoidal current or voltage. Nowadays, the scientific field in this scope is focused on the evaluation of their exploitation properties for distorted signals. The common problem of inductive instrument... [more]

The Future of Energy is focused on the consolidation of new energy technologies. Among them, Fuel Cells (FCs) are on the Energy Agenda due to their potential to reduce the demand for fossil fuel and greenhouse gas emissions, their higher efficiency (as fuel cells do not use combustion, their efficiency is not linked to their maximum operating temperature) and simplicity and absence of moving parts. Additionally, low-power FCs have been identified as the target technology to replace conventional batteries in portable applications, which can have recreational, professional, and military purposes. More recently, low-power FCs have also been identified as an alternative to conventional batteries for medical devices and have been used in the medical field both in implantable devices and as micro-power sources. The most used power supply for implantable medical devices (IMD) is lithium batteries. However, despite its higher lifetime, this is far from enough to meet the patient’s needs since... [more]

Adiabatic Compressed Air Energy Storage (ACAES) is regarded as a promising, grid scale, medium-to-long duration energy storage technology. In ACAES, the air storage may be isochoric (constant volume) or isobaric (constant pressure). Isochoric storage, wherein the internal pressure cycles between an upper and lower limit as the system charges and discharges is mechanically simpler, however, it leads to undesirable thermodynamic consequences which are detrimental to the ACAES overall performance. Isobaric storage can be a valuable alternative: the storage volume varies to offset the pressure and temperature changes that would otherwise occur as air mass enters or leaves the high-pressure storage. In this paper we develop a thermodynamic model based on expected ACAES and existing CAES system features to compare the effects of isochoric and isobaric storage. Importantly, off-design compressor performance due to the sliding storage pressure is included by using a second degree polynomial fi... [more]

Integrating hydrogen fuel cell systems (FCS) remains challenging in the expanding electric vehicle market. One of the levers to meet this challenge is the relevance of energy supervisors. This paper proposes an innovative energy management strategy (EMS) based on the integrated EMS (iEMS) concept. It uses a nested approach combining the best of the three EMS categories (optimization-based (OBS), rules-based (RBS), and learning-based (LBS) strategies) to overcome the real-time operating condition limitations of the fuel cell hybrid electric vehicle (FCHEV). Through a fuel cell/battery hybrid architecture, the purpose is to improve hydrogen consumption and manage the battery state of charge (SOC) under real-time driving conditions. The proposed iEMS approach is based on an OBS with optimal control to make the energy-optimal decision. However, it requires the adaptations of real-time operating conditions and a dynamic SOC horizon management. These requirements are supported by combining a... [more]

The classification of engine fuels was systematised in the present study. The basic evaluation criterion included the type of raw material used for the production of motor fuel and the prevalence of its usage. There was a reason for the purposefulness of searching for new kinds of engine fuels not only for the sake of environmental protection but also for the rational use of natural resources. The concept of substitute fuels was methodically presented. The criteria for the qualification of substitute fuels for internal combustion engines were systematised. Using the example of fuels produced from bio-oils, tests were carried out to assess the prospects of considering bio-oil fuels as substitute ones for self-ignition engines. Accordingly, an analysis was, inter alia, conducted on the fuel combustion process in the cylinder of a test self-ignition engine. Based on the results obtained, the thesis was formulated that rapeseed methyl ester (RME) fuel can be considered a substitute fuel fo... [more]

The course of pyrolysis of pea husks was studied. It was stated that the compaction of a sample during its pyrolysis causes an almost two-fold increase in the content of hydrocarbons in the composition of volatile products in the temperature range of 350−470 °C. Low density polyethylene (LDPE), novolac, and coal tar pitch (CTP) wastes were added to feedstocks in the amount of 2 wt% in order to decrease the contribution of saturated and unsaturated hydrocarbons along with oxygen-containing compounds in volatile products. The analysis of the obtained products of pyrolysis was conducted using the techniques of thermogravimetry/Fourier transform infrared spectroscopy (TG/FT-IR), attenuated total reflectance (ATR) and ultraviolet (UV)-spectroscopies, gas chromatography-mass spectrometry (GCMS), X-ray diffractions (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray analysis (EDX). It was determined that pitch took the first place in a series of effectiveness in decreasing... [more]

Lithium-ion batteries (LIBs) have circumvented the energy storage landscape for decades. However, safety concerns about liquid−electrolyte-based LIBs have challenged their mobilization. Lithium polymer (LiPo) batteries have gained rising interest due to their high thermal stability. Despite an array of commercially available LiPo batteries, limited studies have ventured into modeling. Numerical simulations allow low-cost optimization of existing battery designs through parameter analysis and material configuration, leading to safer and more energy-efficient batteries. This work examined the electrochemical, thermal, and thermal runaway behavior of a lithium cobalt oxide cathode, graphite anode, and poly(vinylidene fluoride-hexafluoropropylene) electrolyte pouch-type LiPo battery using COMSOL Multiphysics®, and validated results with experimental data. The simulated potential curve exhibited strong agreement with experiment data, while the temperature profile during discharge displayed... [more]

Digital reflections of physical energy plants can help support and optimize energy technologies within their lifecycle. So far, no framework for the evolution of virtual representations throughout the process development lifecycle exists. Based on various concepts of virtual representations in different industries, this review paper focuses on developing a novel virtual representation framework for the process development environment within the energy sector. The proposed methodology enables the continuous evolution of virtual representations along the process development lifecycle. A novel definition for virtual representations in the process development environment is developed. Additionally, the most important virtual representation challenges, properties, and applications for developing a widely applicable framework are summarized. The essential sustainability indicators for the energy sector are listed to standardize the process evaluation throughout the process development lifecy... [more]

Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops because of their environmentally friendly nature, high energy density, and long lifespan. Despite these advantages, lithium-ion batteries may experience overcharging or discharging if they are not continuously monitored, leading to fire and explosion risks, in cases of overcharging, and decreased capacity and lifespan, in cases of overdischarging. Another factor that can decrease the capacity of these batteries is their internal resistance, which varies with temperature. This study proposes an estimation method for the state of charge (SOC) using a neural network (NN) model that is highly applicable to the external temperatures of batteries. Data from a vehicle-driving simulator were used to collect battery data at temperatures of 25 °C, 30 °C, 35 °C, and 40 °C, including voltage, current, temperature, and time data. These data were used as inputs to generate the NN models. The NNs used to generate... [more]

The regulation of the seasonal energy supply for natural gas and the storage of fossil energy are important to society. To achieve it, storing a large amount of natural gas in porous underground media is one of the government’s choices. Due to the successful lesson learned from the oil and gas industry, natural gas storage in underground porous media has been regarded as the most potential long−term energy storage method. In this paper, we developed a new workflow to evaluate the performance of gas reservoir−type underground natural gas storage (UGS). The theoretical background of this workflow includes the correction of the average formation pressure (AFP) and gas deviation factor by error theory and the analytical mathematical model of UGS wells. The Laplace transform, line source function, and Stehfest numerical inversion methods were used to obtain pressure solutions for typical vertical and horizontal wells in UGS. The pressure superposition principle and weighting method of the g... [more]

The paper considers the issues of maintaining an equality of flow in generated and consumed electric energy in an electric network incorporating an electric power storage system. An analysis of ways to equalize the energy and power balance was carried out, and the advantages of using electricity storage systems in electrical networks was assessed. Upon simulation using the Power Factory program, we noted that, after switching on the load, a transient process occurs, characterized by a jump in active power, which was caused by the need for time to initiate the electric energy storage system. However, immediately after this, the process of issuing the accumulated energy to the electrical network and compensating for energy consumption began. Moreover, when the load was disconnected, there is a certain dip in the active power curve and a further increase in consumption. This was found to be due to the transition of the electricity storage system to the modes of energy storage and battery... [more]

The normal development of “smart buildings,” which calls for integrating sensors, rich data, and artificial intelligence (AI) simulation models, promises to usher in a new era of architectural concepts. AI simulation models can improve home functions and users’ comfort and significantly cut energy consumption through better control, increased reliability, and automation. This article highlights the potential of using artificial intelligence (AI) models to improve the design and functionality of smart houses, especially in implementing living spaces. This case study provides examples of how artificial intelligence can be embedded in smart homes to improve user experience and optimize energy efficiency. Next, the article will explore and thoroughly analyze the thorough analysis of current research on the use of artificial intelligence (AI) technology in smart homes using a variety of innovative ideas, including smart interior design and a Smart Building System Framework based on digital... [more]

The large-scale integration into electrical systems of intermittent power-generation sources, such as wind power plants, requires greater efforts and knowledge from operators to keep these systems operating efficiently. These sources require reliable output power forecasts to set up the optimal operating point of the electrical system. In previous research, the authors developed an evolutionary approach algorithm called RCDESIGN to optimize the hyperparameters and topology of Echo State Networks (ESN), and applied the model in different time series forecasting, including wind speed. In this paper, RCDESIGN was modified in some aspects of the genetic algorithm, and now it optimizes an ESN with augmented states (ESN-AS) and has been called RCDESIGN-AS. The evolutionary algorithm allows the search for the best parameters and topology of the recurrent neural network to be performed simultaneously. In addition, RCDESIGN-AS has the important characteristic of requiring little computational e... [more]

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak... [more]

The engine fuel control system plays a crucial role in engine performance and fuel economy. Fuel control, in traditional engine control systems, is carried out by means of sensor-based control methods, which correct the fuel flow rate through correlations or scheduled parameters in order to reduce the error between a measured parameter and its desired value. In the presence of component degradation, however, the relationship between the engine measurable parameters and performance may lead to an increase in the control error. In this research, linear models for advanced control systems and for direct fuel control in the presence of components degradation are proposed, with the main objective being to directly predict and correct fuel consumption in the presence of degradation instead of adopting measurable parameters. Two techniques were adopted for model linearization: Small Perturbation and System Identification. Results showed that both models are characterized by high accuracy in p... [more]

A sliding mode control-based model reference adaptive system (SMC-MRAS) estimator for sensor-less control of doubly fed induction generator (DFIG) systems in wind turbine applications is proposed in this paper. The proposed SMC-MRAS estimator uses the rotor current as a variable of interest. The proposed SMC-MRAS estimator has the advantage of being immune to machine parameter variations. The SMC parameters are designed using the Lyapunov stability criteria. The performance of the proposed SMC-MRAS estimator is validated using simulations in MATLAB/SIMULINK. A comparative study between the proposed SMC-MRAS estimator and the PI-MRAS estimator is also conducted to demonstrate the superiority of the proposed SMC-MRAS estimator.

By 2050, the European Union plans to make Europe the first carbon-neutral continent and a global leader in climate-green industries. Recently, many decisions have been taken in the world to ensure the energy transition from fossil fuel to renewable energy. The creation of renewable energy communities (REC) is among the solutions used to increase this transition. This study presents 16 different configurations for energy self-consumption in RECs containing different industrial factories. One mathematical model is proposed for each configuration, and they have been solved according to different criteria. The comparisons are made between these configurations according to economic, environmental, technical, and social criteria. Then, four multi-criteria decision-making (MCDM) methods are used to choose the best configurations considering all the criteria. For this purpose, the achieved results from the mathematical models are used as input for the MCDM methods. The findings demonstrate tha... [more]

In this paper, we propose an optimization model that considers two pathways for injecting renewable content into natural gas pipeline networks. The pathways include (1) power-to-hydrogen or PtH, where off-peak electricity is converted to hydrogen via electrolysis, and (2) power-to-methane, or PtM, where carbon dioxide from different source locations is converted into renewable methane (also known as synthetic natural gas, SNG). The above pathways result in green hydrogen and methane, which can be injected into an existing natural gas pipeline network. Based on these pathways, a multi-period network optimization model that integrates the design and operation of hydrogen from PtH and renewable methane is proposed. The multi-period model is a mixed-integer non-linear programming (MINLP) model that determines (1) the optimal concentration of hydrogen and carbon dioxide in the natural gas pipelines, (2) the optimal location of PtH and carbon dioxide units, while minimizing the overall syste... [more]

This article comprehensively investigates the thermal performance of a ternary hybrid nanofluid flowing in a permeable inclined cylinder/plate system. The study focuses on the effects of key constraints such as the inclined geometry, permeable medium, and heat source/sink on the thermal distribution features of the ternary nanofluid. The present work is motivated by the growing demand for energy-efficient cooling systems in various industrial and energy-related applications. A mathematical model is developed to describe the system’s fluid flow and heat-transfer processes. The PDEs (partial differential equations) are transformed into ODEs (ordinary differential equations) with the aid of suitable similarity constraints and solved numerically using a combination of the RKF45 method and shooting technique. The study’s findings give useful insights into the behavior of ternary nanofluids in permeable inclined cylinder/plate systems. Further, important engineering coefficients such as skin... [more]

An energy production system that combines biomass and fuel cells produces much energy with minimal environmental impact. However, the hydrogen sulfide (H2S) contained in gasified biomass degrades fuel cell performance, thus negating the advantages of this combination. In this study, the removal of H2S by adsorption after biomass gasification was investigated. Metal oxides with high adsorption performance are common H2S adsorbents. However, they have a significant environmental impact in terms of metal depletion, which is an environmental impact indicator. Therefore, neutralized sediment materials from mine drainage treatments can be used as H2S adsorbents. A previous study found that the adsorption performance of H2S adsorbents is equivalent to that of metal oxides, especially in the high-temperature zone (300 °C), and the environmental impact is considerably lower than that of metal oxides. However, because the neutralized sediment is a powder (Φ 4.5 μm on average), there is a possibi... [more]

In the context of energy transformation, the importance of energy storage devices in regional integrated energy systems (RIESs) is becoming increasingly prominent. To explore the impact of energy storage devices on the design and operation of RIESs, this paper first establishes a bi-level dynamic optimization model with the total system cost as the optimization objective. The optimization model is used to optimize the design of three RIESs with different energy storage devices, including System 1 without an energy storage device, System 2 with a thermal energy storage (TES) device, and System 3 with TES and electrical energy storage (EES) devices. According to the design and operation results, the impact of energy storage devices on the operational performance of RIESs is analyzed. The results show that under the design conditions, energy storage devices can significantly increase the capacity of the combined heating and power units and absorption chillers in System 2 and System 3 and... [more]