The voltage ride through capability of the major auxiliary variable-frequency drive (VFD) in large thermal power plants is the key technical issue of power grid and source coordination. In order to test the high voltage ride through (HVRT) and low voltage ride through (LVRT) capability of the auxiliary VFD, it is necessary to develop a power supply to simulate different grid voltage sag and swell accurately. In this paper, a generator (VSSG) based on the common three-phase inverter circuit that can simulate multi-mode voltage sag/swell is proposed. The designed main circuit consisting of transformer, rectifier, DC split capacitors, three-phase inverter, and LC-filter can generate single-phase and three-phase voltage sag, swell, and phase angle jumping flexibly. The developed control strategies composed of the double closed-loop control and the neutral voltage balance control achieve accurate output, fast dynamic response, and step-less adjustment. Simulation and experiment results veri... [more]

Considering the pressing challenges of supply security and climate change, advanced processes to produce electricity and biofuels from biomass have to be developed. Biomass gasification is a very promising technology, but there is a lack of comprehensive reviews, specifically on the technologies for hydrogen chloride hot gas cleanup, which are necessary in order to work at the same temperature and respect the limits of advanced downstream components. In this review, the Cl content of the main biomasses in Europe is given, and data on syngas content and the tolerance of downstream equipment are highlighted. Hot gas cleaning technologies, which have the advantage of improved thermal efficiency are reviewed, analyzing the thermodynamic and primary and secondary methods. This review identifies NaAlO2 and Na2CO3 within 450−550 °C as the most effective sorbents, which are able to reduce the concentration of HCl below 1 ppm. Nevertheless, H2S cannot be simultaneously removed and has... [more]

The accurate determination of the gas in place in shale reservoirs is a basic but challenging issue for shale gas evaluation. Conventional canister gas desorption tests on retrieved core samples and subsequent data analyses (via linear or polynomial regression)—originally developed for coalbed methane, where gases are mainly stored in the adsorbed phase—is unadvisable for shale gas, which is stored as an appreciable amount of free gas in shale reservoirs. In the present study, a mathematical model that simultaneously takes into account gas expansion, adsorption/desorption, and the gas flow in shale is proposed to simulate gas release from a core sample retrieved from the Lower Silurian Longmaxi Formation of the Fuling shale gas field, Sichuan Basin. The results indicate that, compared with the value of 2.11 m3/t rock estimated with the traditional United States Bureau of Mines (USBM) method, the total gas in place within the studied Longmaxi Shale estimated with our mathematical model... [more]

As part of a project for the realization of a hybrid vehicle with an innovative power train system, the proposal presented is to disconnect the turbocharger group and study the different behavior of the compressor and turbine, so decoupled. In an actual turbocharger, when the power of the turbine exceeds that required by the compressor, the wastegate valve opens. In this way, a part of the flue gases does not evolve into a turbine and limits the power generated. In the solution proposed here (the paper considers only “compressor side”) all the flow rate of the flue gases is processed by the turbine. In this way, for each rpms of the IC engine, the turbine generates more power than that required by the compressor. This makes it possible to use this surplus of power for the auxiliaries and/or to recharge the battery pack of the considered hybrid vehicle. An additional advantage is, thanks to this surplus generated, that the battery pack can be smaller and can be recharged while driving.... [more]

In the electricity market environment, the market clearing price has strong volatility, periodicity and randomness, which makes it more difficult to select the input features of artificial neural network forecasting. Although the traditional back propagation (BP) neural network has been applied early in electricity price forecasting, it has the problem of low forecasting accuracy. For this reason, this paper uses the maximum information coefficient and Pearson correlation analysis to determine the main factors affecting electricity price fluctuation as the input factors of the forecasting model. The improved particle swarm optimization algorithm, called simulated annealing particle swarm optimization (SAPSO), is used to optimize the BP neural network to establish the SAPSO-BP short-term electricity price forecasting model and the actual sample data are used to simulate and calculate. The results show that the SAPSO-BP price forecasting model has a high degree of fit and the average rel... [more]

The re-use of wastewater is an increasingly important subject. Most recently, several attempts were reported to convert wastewater in harmless or even valuable substances by the use of electrical current. Electrochemistry is an old approach. The renewed interest stems from the fact that electrical current is often available in abundance, for example from solar energy in arid regions, while clean water is not. Experimentally, one has to deal with very many products which are the result of many reaction steps. Here, theory can help. Using Car−Parrinello molecular dynamics, we simulate the first few reaction steps of the electrolysis of wastewater. On the basis of previous studies, we investigate the reaction of carbon dioxide and nitrogen compounds. The results show a great variety of reaction steps and resulting products. Some of them are technologically interesting, such as hydrogen and formic acid.

Using published cross-sections and a series of geological constraints, a 3D geological model of an important area of the Adriatic sector of peninsular Italy—i.e., the Marche region—was developed. Then, an analytical procedure, taking into account the heat rising from the mantle and the radiogenic heat produced by the crust, was applied on the pre-built structural model, in order to obtain the 3D geothermal setting of the entire region. The results highlighted the key role played by the Moho geometry, particularly as a step of ~10 km occurs between the Adriatic Moho of the subducting plate to the west and the new Tyrrhenian Moho characterizing the back-arc area to the west. The comparison between our results and available borehole data suggests a good fit between the applied analytical methodology and published datasets. A visible anomaly is located at a specific site (i.e., the coastal town of Senigallia), where it may be envisaged that fluid circulation produced a local surface heat f... [more]

The aim of the research is to identify and quantify the direct sustainable effects resulting from the improved road infrastructure in the local urban-port transport system. This case study considers the city port of Szczecin (Poland). The effects are identified for the local road transport system by comparing freight road transport performance in two options: with the investment and without the investment. The sustainable effects are quantified in terms of money and physical units. Sustainable economic, social, and environmental effects concern generalized freight road transport cost, i.e., truck operating costs and costs of truck drivers’ working time, as well as freight transit time, energy consumption, greenhouse gas emissions, and environmental savings. To capture effects, the forecast of truck traffic demand, as well as unit vehicle operating costs, values of time, and air pollution and climate change, values are elaborated and revealed in freight road transport. The investigation... [more]

This study uses an artificial neural network (ANN) as an intelligent controller for the management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP). Two ANN-based scheduling control approaches are presented: the ANN-based backtracking search algorithm (ANN-BBSA) and ANN-based binary practical swarm optimization (ANN-BPSO) algorithm. Both algorithms provide the optimal schedule for every distribution generation (DG) to limit fuel consumption, reduce CO2 emission, and increase the system efficiency towards smart and economic VPP operation as well as grid decarbonization. Different test scenarios are executed to evaluate the controllers’ robustness and performance under changing system conditions. The test cases are different load curves to evaluate the ANN’s performance on untrained data. The untrained and trained load models used are real-load parameter data recorders in northern parts of Malaysia. The test results are analyzed to investigate the performance... [more]

Technological developments in the health sector for the safety of neonates are essential. Such efforts are needed to curb the increase in premature infant mortality cases caused by bacteria, asphyxia, infections, and poor management of facility equipment. Furthermore, preterm and other at-risk babies have low ability to regulate temperature and produce body heat as characterized by their dry skin conditions; hence, the need for baby incubators. For their operation, these baby incubators provide strict regulated energy change that is influenced by heat transfer caused by the surrounding atmospheric temperature and humidity. This paper presents the design, construction, and performance study of a proposed Fuzzy-PID hybrid control system for regulating temperature and humidity in a baby incubator. To accomplish its goal, the proposed controller must be able to distribute heat and maintain humidity in the incubator under fluctuating atmospheric conditions to keep the baby’s body warm. Perf... [more]

Domestic hot water preparation is one of the main sources of energy consumption in households. One of the most important elements of domestic hot water (DHW) preparation installation is the storage tank. Its design can significantly affect the efficiency of the system and energy consumption for hot water preparation. This paper presents the results of an experimental study to examine seven different designs of the cold water inlet to the storage tank and the use of two types of obstacles inside this tank placed at three different heights. The number of stratification and the energy efficiency of the system for each variant were examined. Additionally, tests were carried out for different profiles of hot water consumption in order to examine the temperature changes in the DHW tank. A system with an inlet, as an elbow facing down with a single plate, turned out to be the most advantageous variant (3−8% increase in energy efficiency compared to the basic inlet variant). An analogous analy... [more]

In the coming decades, the European energy system is expected to become increasingly reliant on non-dispatchable generation such as wind and solar power. Under such a renewable energy scenario, a better characterization of the extreme weather condition ‘Dunkelflaute’, which can lead to a sustained reduction of wind and solar power, is important. In this paper, we report findings from the very first climatological study of Dunkelflaute events occurring in eleven countries surrounding the North and Baltic Sea areas. By utilizing multi-year meteorological and power production datasets, we have quantified various statistics pertaining to these events and also identified their underlying meteorological drivers. It was found that almost all periods tagged as Dunkelflaute events (with a length of more than 24 h) are in November, December, and January for these countries. On average, there are 50−100 h of such events happening in each of these three months per year. The limited wind and solar... [more]

This paper provides a comprehensive review and critical analysis of the latest research results in addition to an overview of the future challenges and opportunities regarding the use of hydrogen to power internal combustion engines (ICEs). The experiences and opinions of various international research centers on the technical possibilities of using hydrogen as a fuel in ICE are summarized. The advantages and disadvantages of the use of hydrogen as a solution are described. Attention is drawn to the specific physical, chemical, and operational properties of hydrogen for ICEs. A critical review of hydrogen combustion concepts is provided, drawing on previous research results and experiences described in a number of research papers. Much space is devoted to discussing the challenges and opportunities associated with port and direct hydrogen injection technology. A comparison of different fuel injection and ignition strategies and the benefits of using the synergies of selected solutions... [more]

The paper presents the Generalized Benders Decomposition (GBD) method, which is now one of the basic approaches to solve big mixed-integer nonlinear optimization problems. It concentrates on the basic formulation with convex objectives and constraints functions. Apart from the classical projection and representation theorems, a unified formulation of the master problem with nonlinear and linear cuts will be given. For the latter case the most effective and, at the same time, easy to implement computational algorithms will be pointed out.

This paper focuses on the issue of energy efficiency management in the region of Prešov self-governing region (PSR), Slovakia, as the energy market is liberalized and the behavior of electricity consumers is influenced not only by conventional but also by alternative suppliers of this type of energy. Based on the statistical evaluation of a questionnaire survey focused on the emotional, behavioral, and cognitive behavior of consumers, a model of optimization of system processes of energy efficiency management at the regional level is presented. A one-way ANOVA and t-test were used to determine statistically significant differences, and Pearson’s correlation coefficient was used to determine a statistically significant relationship. Based on the obtained results, a suitable candidate for efficient electricity management is an employee aged 36 to 50 with a technical focus. The proposed model of optimizing the processes of energy management efficiency at the regional level can also be app... [more]

The rapid growth of wind and solar energy penetration has created critical issues, such as fluctuation, uncertainty, and intermittence, that influence the power system stability, grid operation, and the balance of the power supply. Improving the reliability and accuracy of wind and solar energy predictions can enhance the power system stability. This study aims to contribute to the issues of wind and solar energy fluctuation and intermittence by proposing a high-quality prediction model based on neural networks (NNs). The most efficient technology for analyzing the future performance of wind speed and solar irradiance is recurrent neural networks (RNNs). Bidirectional RNNs (BRNNs) have the advantages of manipulating the information in two opposing directions and providing feedback to the same outputs via two different hidden layers. A BRNN’s output layer concurrently receives information from both the backward layers and the forward layers. The bidirectional long short-term memory (BI-... [more]

Accurate and timely wind power forecasting is essential for achieving large-scale wind power grid integration and ensuring the safe and stable operation of the power system. For overcoming the inaccuracy of wind power forecasting caused by randomness and volatility, this study proposes a hybrid convolutional neural network (CNN) model (GA−PSO−CNN) integrating genetic algorithm (GA) and a particle swarm optimization (PSO). The model can establish feature maps between factors affecting wind power such as wind speed, wind direction, and temperature. Moreover, a mix-encoding GA−PSO algorithm is introduced to optimize the network hyperparameters and weights collaboratively, which solves the problem of subjective determination of the optimal network in the CNN and effectively prevents local optimization in the training process. The prediction effectiveness of the proposed model is verified using data from a wind farm in Ningxia, China. The results show that the MAE, MSE, and MAPE of the prop... [more]

The challenges of the world economy and their societies, after the outbreak of the COVID-19 pandemic have led policy-makers to seek for effective solutions. This paper examines the oil price volatility response to the COVID-19 pandemic and stock market volatility using daily data. A general econometric panel model is applied to investigate the relationship between COVID-19 infection and death announcements with oil price volatility. The paper uses data from six geographical zones, Europe, Africa, Asia, North America, South America, and Oceania for the period 21 January 2020 until 13 May 2021 and the empirical findings show that COVID-19 deaths affected oil volatility significantly. This conclusion is confirmed by a second stage analysis applied separately for each geographical area. The only geographical area where the existence of correlation is not confirmed between the rate of increase in deaths and the volatility of the price of crude oil is Asia. The conclusions of this study clea... [more]

In this paper, the problem of estimating the core losses for inductive components is addressed. A novel methodology is applied to estimate the core losses of an inductor in a DC-DC converter in the time-domain. The methodology addresses both the non-linearity and dynamic behavior of the core magnetic material and the non-uniformity of the field distribution for the device geometry. The methodology is natively implemented using the LTSpice simulation environment and can be used to include an accurate behavioral model of the magnetic devices in a more complex lumped circuit. The methodology is compared against classic estimation techniques such as Steinmetz Equation and the improved Generalized Steinmetz Equation. The validation is performed on a practical DC-DC Buck converter, which was utilized to experimentally verify the results derived by a model suitable to estimate the inductor losses. Both simulation and experimental test confirm the accuracy of the proposed methodology. Thus, th... [more]

Ocean energy is a kind of renewable energy contained in seawater, which has the characteristics of large total reserves, sustainable use, and its being green and clean. Influenced by rising oil prices and global climate change, an increasing number of countries are attaching great importance to the strategic position of ocean energy in the future energy sector, and are formulating national ocean energy development roadmaps and conducting research and development on ocean energy technologies. Ocean current energy is a widely existing kind of ocean energy with abundant reserves. However, due to the low current velocity in most of the deep sea, low current energy has not been effectively exploited. In this paper, the Blade element momentum (BEM) theory based on Vortex column theory is used to design a special airfoil for low current energy applications, and a prototype turbine with rotor diameter of 4.46 m and tip speed ratio (TSR) of 6 is fabricated. In order to achieve stable electric p... [more]

Climate mitigation and adaptation planning (CMAP) has recently been implemented across the EU-28 to reduce GHG emissions (CO2, CH4, N2O). Thus, the aim of this study was to provide an overview of GHG emissions from the agricultural sector in the EU-28 from 1990 to 2019, and cluster the EU-28 countries regarding their total GHG emissions. The results emphasize the positive impact of CMAP through a negative trend of the total GHG emissions (−2653.01 thousand tons/year, p < 0.05). Despite the positive and not significant trend of the total CO2 emissions, both CH4 and N2O exhibited a negative and significant trend. At the country scale, Italy, the United Kingdom, and the Netherlands showed the highest reduction in total GHG emissions, by −282.61thousand tons/year (p < 0.05), −266.40 thousand tons/year (p < 0.05), and −262.91 thousand tons/year (p < 0.05), respectively. The output of the multivariate analysis approach indicates changes in the pattern of GHG emissions between 199... [more]

In this paper, the object of study is secure transmission and green energy transfer in full-duplex (FD) wireless-powered relay (WPR) secure systems, where an FD relay collects the power from radio-frequency signs and transmits the information in the face of multiple eavesdroppers. In order to improve the efficiency and safety of the contemporaneous wireless energy and information delivery, we propose a joint energy-signal- (ES-) aided secure beamforming and time-switch scheme under the self-power circulation protocol at the relay. The question formulated in this paper is to maximize the confidentiality rate according to energy restrictions at both the relay and energy receiver. As the question is non-salient and hard to resolve directly, we transform it into two sub-problems. For the first sub-problem, a two-level optimization technique is suggested to separately gain the optimal beamforming as well as the ES covariance. The extrinsic rank is a single-variable majorization question, wh... [more]

The chiller is the major energy consuming HVAC component in a building. Currently, huge chiller data is easy to obtain due to Internet of Things (IoT) technology development. In order to optimize the chiller system, this study presents a data mining technique that utilizes the available chiller data. The data mining techniques used are prediction model, clustering analysis, and association rules mining (ARM) analysis. The dataset was collected every minute for a year from a water-cooled chiller at an institutional building in Taiwan and from meteorological data. The power consumption prediction model was built using deep neural networks with 0.955 of R2, 4.470 of MAE, and 6.716 of RMSE. Clustering analysis was performed using the k-means algorithm and ARM analysis was performed using Apriori algorithm. Each cluster identifies those operational parameters that have strong association rules with high performance. The operational parameters from ARM were simulated using the prediction mod... [more]

Uninterrupted availability of energy and power resources is essential for the productivity and smooth functioning of an enterprise. However, constrained by financial resources, smaller firms in developing economies face a plethora of challenges concerning the access to electricity. However, less attention has been paid in the extant literature to explore this phenomenon. The present study investigates the impact of access to electricity on labor productivity in Bangladesh in the presence of electricity constraints, electricity obstacles, and SME firm size. It employs the OLS regression and propensity score matching (PSM) technique for treatment effect to deal with the selection bias and endogeneity issue using the World Bank Enterprise Survey’s cross-sectional firm-level data for 3196 sample firms over the period of 2007−2013. The results provide evidence in support of SMEs’ labor productivity in response to electricity access. Lack of electricity access was partially found to affect S... [more]

Organic Rankine cycle (ORC) is considered a promising heat-to-power technology to utilize waste heat and renewable energy, including solar, biomass and geothermal. However, since the thermodynamic, economic and environmental performance is usually conflict, the single objective design could no longer meet the requirements of the ORC system, putting forward urgent requirements for multi-objective optimization, which has attracted increasing attention with lots of papers published. However, due to these different decision variables, optimization objectives and approaches, existing research is significantly different from each other and is difficult to compare without a systematic summary. Therefore, this paper provides an overview of ORC multi-objective research from three perspectives: optimization objective, method and optimization parameters. Based on the classification of different objectives, this work summarizes the involved variables and provides a recommendation for selecting app... [more]