This review emphasizes the role and performance of versatile DC-DC converters in AC/DC and Hybrid microgrid applications, especially when solar (photo voltaic) PV is the major source. Here, the various converter topologies are compared with regard to voltage gain, component count, voltage stress, and soft switching. This study suggests the suitability of the converter based on the source type. The merits of a coupled inductor and interleaved converters in micro gird applications are elucidated. The efficiency and operating frequencies of converts for different operating modes are presented to determine the suitable converters for inductive and resistive loads. The drawbacks of converters are discussed. Finally, the mode of operation of different converts with different grid power sources and its stability and reliability issues are highlighted. In addition, the significance of the converter’s size and cost-effectiveness when choosing various PV source applications are discussed.

This paper proposes a novel and robust method of sensorless speed control using a deadbeat observer for an interior permanent magnet synchronous motor (IPMSM). The proposed sensorless speed control method uses a deadbeat observer to estimate the extended electromotive force (EEMF) in a rotational coordinate system. The estimated EEMF is used in the IPMSM velocity estimation algorithm. The deadbeat EEMF observer (DEEMFO) shows greater robustness compared to the reconstructor, which estimates the EEMF by simply recalculating the voltage equation. Unlike a reconstructor, DEEMFO has a feedback component, so it can compensate for errors due to uncertainty in motor parameters and errors due to parameter fluctuations that may occur during use. By simulating and experimenting with speed, load torque, and parameter fluctuations, it is proved to be more robust and precise than the reconstructor. The simulation is performed with MATLAB/Simulink, and the experiments were carried out using a DSP TM... [more]

There is a strong trend in the development of control systems for multi-rotor unmanned aerial vehicles (UAVs), where minimization of a control signal effort is conducted to extend the flight time. The aim of this article is to shed light on the problem of shaping control signals in terms of energy-optimal flights. The synthesis of a UAV autonomous control system with a brain emotional learning based intelligent controller (BELBIC) is presented. The BELBIC, based on information from the feedback loop of the reference signal tracking system, shows a high learning ability to develop an appropriate control action with low computational complexity. This extends the capabilities of commonly used fixed-value proportional−integral−derivative controllers in a simple but efficient manner. The problem of controller tuning is treated here as a problem of optimization of the cost function expressing control signal effort and maximum precision flight. The article introduces several techniques (bio-i... [more]

This paper expresses the output power of renewable generators and load demand as interval data and develops the interval economic dispatch (IED), as well as interval reactive power optimization (IRPO) models. The two models are generalized into a specific type of linear interval programming (LIP) and nonlinear interval programming (NLIP), respectively. A security limits method (SLM) is proposed to solve LIP and NLIP problems. As for the LIP, the maximum radii of the interval variables are first calculated by the optimizing-scenarios method (OSM) for defining security limits, and the LIP is transformed into deterministic linear programming (LP), for which its constraints are the security limits, which can be solved by the simplex method. As for the NLIP, Monte Carlo simulations were used to obtain the maximum radii of the interval variables, and the average interval ratio of the interval variables is defined to compute the security limits for transforming the NLIP to deterministic nonli... [more]

One of the main problems in oil fields is the deposition of scale inside oil pipelines, which causes problems such as the reduction of the internal diameter of oil pipes, the need for more energy to transport oil products, and the waste of energy. For this purpose, the use of an accurate and reliable system for determining the amount of scale inside the pipes has always been one of the needs of the oil industry. In this research, a non-invasive, accurate, and reliable system is presented, which works based on the attenuation of gamma rays. A dual-energy gamma source (241Am and 133Ba radioisotopes), a sodium iodide detector, and a steel pipe are used in the structure of the detection system. The configuration of the detection structure is such that the dual-energy source and the detector are directly opposite each other and on both sides of the steel pipe. In the steel pipe, a stratified flow regime consisting of gas, water, and oil in different volume percentages was simulated using Mo... [more]

With the increasing scale and depth of underground engineering, the geological environment that engineering is faced with is becoming more complex. As the weak position of rock mass, the structural surface has a particularly great influence on the mechanical characteristics of the rock mass. In order to obtain the shear strength characteristic of the structural plane and analyze the influence of morphological parameters such as the undulating angle and bulge degree on shearing, taking medium-low permeability tight sandstone as the research object, four kinds of structural plane samples with different undulating angles (10, 20, 30 and 40°) were prepared with a Python and high-precision engraving machine. Direct shear tests under different normal stresses (2, 4, 6 and 8 MPa) and shear rates (0.6, 1.2 and 2.4 mm/min) were performed, and the shear mechanical properties were analyzed. The structural surfaces before and after shearing were scanned using a high-precision three-dimensional sca... [more]

Irradiance variability is one of the main challenges for using photovoltaic energy. This variability affects the operation of maximum power point trackers (MPPT) causing energy losses. The logic of the Perturb-and-Observe MPPT algorithm is particularly sensitive to quick irradiance changes. We quantified the existing relation between irradiance variations and efficiency loss of the logic of the Perturb-and-Observe MPPT algorithm, along with the sensitivity of the MPPT to its control parameters. If the algorithm parameters are not tuned properly, its efficiency will drop to nearly 2%. Irradiance variability causes a systematic energy loss of the algorithm that can only be quantified by ignoring the hardware components. With this, we aim to improve the energy yield estimation by providing an additional efficiency loss to be considered in the calculations.

Global warming is becoming an increasing issue, and greenhouse gas (GHG) emissions represent the engine of such a phenomenon. This review aims to identify the origin of GHG emissions and focus in detail on the ones related to (petro) chemical industries. The industrial sector is the primary GHG emitter among all the other anthropogenic sources. The chemical industry is the first in charge of that (having accounted for about 6.5% of the global GHG emissions in 2018). Thought-provoking data such as yearly productivities and emission factors related to the predominant chemicals prompt the reader to acquire a sense of the critical activities responsible for carbon-intensive emissions, which should be the first to be decarbonized. Specifically, ammonia synthesis and steam cracking resulted in the most polluting processes of the chemical industry, being responsible for the release of about 440 and 228 Mt-CO2,eq/y, respectively, in 2020. The same approach also applies to oil refining. Due to... [more]

The organic Rankine cycle (ORC) technology is an efficient way to convert low-grade heat from renewable sources or waste heat for power generation. The partial evaporating organic Rankine cycle (PEORC) can be considered as a promising alternative as it can offer a higher utilization of the heat source. An experimental investigation of a small ORC system used in full or partial evaporation mode is performed. First characterized in superheated mode, which corresponds to standard ORC behavior, a semi-empirical correlative approach involving traditional non-dimensional turbomachinery parameters (specific speed, pressure ratio) can accurately describe one-phase turbine performance. In a second step, two-phase behavior is experimentally investigated. The efficiency loss caused by the two-phase inlet condition is quantified and considered acceptable. The turbine two-phase operation allows for an increase in the amount of recovered heat source. The ability to operate in two phases provides a n... [more]

The integrated scheduling problem in automated storage and retrieval systems (AS/RS) and the hybrid flowshop is critical for the realization of lean logistics and just-in-time distribution in manufacturing systems. The bi-objective model that minimizes the operation time in AS/RS and the makespan in the hybrid flowshop is established to optimize the problem. A mixed algorithm, named GA-MBO algorithm, is proposed to solve the model, which combines the advantages of the strong global optimization ability of genetic algorithm (GA) and the strong local search ability of migratory birds optimization (MBO). To avoid useless solutions, different cross operations of storage and retrieval tasks are designed. Compared with three algorithms, including improved genetic algorithm, improved particle swam optimization, and a hybrid algorithm of GA and particle swam optimization, the experimental results showed that the GA-MBO algorithm improves the operation efficiency by 9.48%, 19.54%, and 5.12% and... [more]

The construction of daily electricity consumption profiles is a common practice for user characterization and segmentation tasks. As in any data analysis project, to obtain these load profiles, a stage of data preparation is necessary. This article explores to what extent does the selection of the data preparation technique impacts load profiling. The techniques discussed are used in the following tasks: standardization, construction of data, dimensionality reduction and data enrichment. The analysis reveals a great incidence of the data preparation on the result. The need to make the data preparation process explicit in each report is identified. In particular, it is highlighted that the most usual default standardization process, column standardization, is not adequate in the preparation of energy consumption profiles.

Safety issues arising from a hydrogen explosion accident in Korea are discussed herein. In order to increase the safety of hydrogen refueling stations (HRSs), the Korea Gas Safety Corporation (KGS) decided to install a damage-mitigation wall, also referred to as a barrier, around the storage tanks at the HRSs after evaluating the consequences of hypothetical hydrogen explosion accidents based on the characteristics of each HRS. To propose a new regulation related to the barrier installation at the HRSs, which can ensure a proper separation distance between the HRS and its surrounding protected facilities in a complex city, KGS planned to test various barrier models under hypothetical hydrogen explosion accidents to develop a standard model of the barrier. A numerical simulation to investigate the effect of the recommended barrier during hypothetical hydrogen explosion accidents in the HRS will be performed before installing the barrier at the HRSs. A computational fluid dynamic (CFD) c... [more]

This research work aims at providing power quality improvement for the nonlinear load to improve the system performance indices by eliminating maximum total harmonic distortion (THD) and reducing neutral wire current. The idea is to integrate a shunt hybrid active power filter (SHAPF) with the system using machine learning control techniques. The system proposed has been evaluated under an artificial neural network (ANN), gated recurrent unit, and long short-term memory for the optimization of the SHAPF. The method is based on the detection of harmonic presence in the power system by testing and comparison of traditional pq0 theory and deep learning neural networks. The results obtained through the proposed methodology meet all the suggested international standards of THD. The results also satisfy the current removal from the neutral wire and deal efficiently with minor DC voltage variations occurring in the voltage-regulating current. The proposed algorithms have been evaluated on the... [more]

Among the activities that cities are taking to reduce the emissions of harmful substances emitted by conventional engine-powered vehicles is replacing the fleet with electric vehicles in public transport that can operate in urban areas. Fleet conversion is a process in which one of the decisions that must be made is the choice of lines that should be served in the first place by electric buses. Due to the specificity of the battery charging process, the routes of lines serviced by electric vehicles should run through sections that are as little exposed to disruptions as possible, which can adversely affect the travel time of these sections. The main goal of the article was to develop a method that supports the search for bus lines that are characterized by the highest level of reliability and punctuality and therefore also by the stability of the travel time between stops. The proposed method makes it possible to indicate critical interstop sections that have the greatest impact on the... [more]

Increasing and inexorable urbanization calls for the involvement of all the stakeholders [...]

As a developing country, South Africa relies on electricity as the most critical amenity needed for development. KwaZulu-Natal (KZN) is one of the nine provinces in South Africa that faces an energy supply challenge. KZN is also the warmest province among them all due to its location. As one of the warmest provinces, solar power could be utilised to assist in dealing with the energy crisis. This paper focuses on the cost uncertainties attributed to the implementation of solar power which will assist in meeting the demand of energy in the region. The unsustainability of energy has led to a near collapse of the region’s economy. This study also contributes to improving the scientific implementation of solar power in the region to deal with the unsustainability criteria observed. The employment of Cost Benefit Analysis (CBA) revealed solar power as one of the most reliable renewable energies for planned implementation bases. With the development of the Economical, Methodological and Envir... [more]

Energy renovations of the building stock are a paramount objective of the European Union (EU) to combat climate change. A tool for renovation progress monitoring is energy performance certificate (EPC) labelling. The present study tested the effect of different EPC label classifications on a national database, which comprises ~25,000 EPC values from apartment buildings, detached houses, office buildings, and educational, commercial, and service buildings. Analysing the EPC classes labelling resulting from four different EU methods, we estimated the annual renovation rates, costs, energy savings, and CO2 emissions reduction that would affect the national building stock if each of them was adopted, to fulfil the European Climate Target Plan by the year 2033. The ISO 52003-1:2017 two-point and one-point methods determined a very uneven distribution of renovation rates, from 0.45% to ~9%. Conversely, the Directive 15% recently proposed in COM/2021/802 with uniform rates determined smaller... [more]

In recent years, growing energy demands and environmental pollution caused by the extensive use of fossil fuels have inspired considerable research interest in adsorptive heat transformation (AHT). This technology offers effective utilization of low-grade solar or waste thermal energy for cooling and heating with low environmental impact. Increasing the AHT power is a keystone for further development and dissemination of this emerging technology. The AHT power is mainly determined by ad/desorption dynamics, which is significantly hindered by slow heat transfer between the adsorbent and heat exchanger. Shaping the adsorbent bed as a coating on the heat exchanger surface is considered an effective route to enhance heat transfer and increase the AHT power. In this review, the technology of adsorbent coating for AHT is comprehensively surveyed, including coating synthesis, adsorption dynamics, and use in real AHT devices. The advantages of the coated bed configuration are considered, and i... [more]

The Ri-Qing-Wei Basin is a newly discovered Late Mesozoic rift basin on the eastern Shandong coast in recent years. Thick, continuous deposited source rocks are found in the Lingshan Island scientific drilling project. Therefore, it is necessary to evaluate the distribution and hydrocarbon generation potential of source rocks in this area. Organic geochemical experiments were carried out on samples from the core of LK-1 and outcrops in the Lingshan Island, the Laoshan area, and the Jimo Zhougezhuang area to evaluate the maturity, abundance, and type of organic matter in source rocks. The results show that the cumulative thickness of the source rocks in the study area is more than 500 m, and the TOC content is generally greater than 1.0%. The organic matter type is good (mainly type II1 and type II2 kerogen) and the Ro value is more than 2.0. The thermal evolution degree of the organic matter is high with natural gas predominantly generated. We carried out Rock-Eval, PY-GC and gold tube... [more]

The construction industry has experienced phenomenal growth because of technological advancements in the past couple of decades. Prefabrication constitutes a sizeable share of this industry and is being adopted all over the world. The method of casting construction elements in a controlled environment and assembling them on-site has revolutionised the industry. Research on various aspects of the technology is ongoing around the world, and an impressive number of articles have been published. However, the prefab technology, materials used, and terminology have varied across locations, which may have hindered the method’s wider acceptability. By evaluating technical articles published between 1991 and 2022, this report analyses the present body of knowledge regarding prefab technology, its evolution, sustainability, and stakeholder views. This technology effectively contributes around 40% in time saving, 27% in cost reduction, 30% in reduced carbon emissions, and 84% in on-site wastage r... [more]

Random forest (RF) is one of the most popular machine learning (ML) models used for both classification and regression problems. As an ensemble model, it demonstrates high predictive accuracy and low variance, while being easy to learn and optimize. In this study, we use RF for short-term load forecasting (STLF), focusing on data representation and training modes. We consider seven methods of defining input patterns and three training modes: local, global and extended global. We also investigate key RF hyperparameters to learn about their optimal settings. The experimental part of the work demonstrates on four STLF problems that our model, in its optimal variant, can outperform both statistical and ML models, providing the most accurate forecasts.

The increasing importance of renewable energy capacity in the power generation scenario, together with the fluctuating consumer energy demand, forces conventional fossil fuel power generation systems to promptly respond to relevant and rapid load variations and to operate under off-design conditions during a major fraction of their lives. In order to improve existing power plants’ flexibility in facing energy surplus or deficit, retrofittable solutions for gas turbine compressors are proposed. In this paper, two different operation strategies, variable inlet guide vanes (IGVs) and blow-off extraction (BO), are considered for enabling partial load and minimum environmental load operation, and thus to identify implementation opportunities in existing thermal power plants. A typical 15-stage F-class gas turbine compressor is chosen as a test case and some energy demand scenarios are selected to validate the adopted solutions. The results of an extensive 3D, steady, CFD analysis are compar... [more]

The aim of this paper is to present a novel approach to energy use forecasting. We propose a nested fuzzy cognitive map in which each concept at a higher level can be decomposed into another fuzzy cognitive map, multilayer perceptron artificial neural network or long short-term memory network. Historical data related to energy consumption are used to construct a nested fuzzy cognitive map in order to better understand energy use behavior. Through the experiments, the usefulness of the nested structure in energy demand prediction is demonstrated, by calculating three popular metrics: Mean Square Error, Mean Absolute Error and the correlation coefficient. A comparative analysis is performed, applying classic multilayer perceptron artificial neural networks, long short-term memory networks and fuzzy cognitive maps. The results confirmed that the proposed approach outperforms the classic methods in terms of prediction accuracy. Moreover, the advantage of the proposed approach is the abilit... [more]

Addressing the shortcomings of existing low-frequency oscillation research on electrified railways, which has mainly focused on single-type trains and lacks the accurate modeling of traction inverter systems, in this paper we modeled and analyzed low-frequency oscillations in an electrified railway passenger and freight mixed-operation vehicle−grid system. First, an equivalent model of the DC side of the traction inverter was established, with the inverter system being equivalent to the parallel connection of the load resistance and the current source, and the specific mathematical expression was determined and verified by impedance measurement. Secondly, based on the equivalent model of the DC side of the traction inverter, a small signal model of the vehicle−grid system under the mixed operating conditions of CRH5 and HXD2B considering the inverter system was established. The generalized Nyqusit criterion was used to study the low-frequency oscillation characteristics under mixed tra... [more]

This paper proposes a dispatchable photovoltaic (PV) hybrid inverter for output power tracking without any dependency on the converter’s efficiency and with no power closed loop. The system uses an extra-low-voltage battery energy storage system (BEES) based on a Li-ion battery pack to be applicable for use inside homes and other installations close to the end-user. A bidirectional isolated current-fed dual-active bridge (CF-DAB) converter associated with the batteries provides a wide conversion voltage ratio and ensures safety for the users. The proposed control system shares the DC bus voltage controller between the ac grid interfacing converter (AC-DC) and CF-DAB (DC-DC), eliminating the converter’s efficiency in the reference equations. When dispatchable power is not required, or according to the user’s request, the battery’s charge/discharge current can be specified. A disturbance rejection technique avoids low-frequency current ripple on the battery side. It contributes to the ba... [more]