The paper presents the application of recurrent LSTM neural networks for short-time load forecasting in the Polish Power System (PPS) and a small region of a power system in Central Poland. The objective of the present work was to develop an efficient and accurate method of forecasting the 24-h pattern of power load with a 1-h and 24-h horizon. LSTM showed effectiveness in predicting the irregular trends in time series. The final forecast is estimated using an ensemble consisted of five independent predictions. Numerical experiments proved the superiority of the ensemble above single predictor resulting in a reduction of the MAPE the RMSE error by more than 6% in both forecasting tasks.

The efficiency of PV systems can be improved by accurate estimation of PV parameters. Parameter estimation of PV cells and modules is a challenging task as it requires accurate operation of PV cells and modules followed by an optimization tool that estimates their associated parameters. Mostly, population-based optimization tools are utilized for PV parameter estimation problems due to their computational intelligent behavior. However, most of them suffer from premature convergence problems, high computational burden, and often fall into local optimum solution. To mitigate these limitations, this paper presents an improved variant of particle swarm optimization (PSO) aiming to reduce shortcomings offered by conventional PSO for estimation of PV parameters. PSO is improved by introducing two strategies to control inertia weight and acceleration coefficients. At first, a sine chaotic inertia weight strategy is employed to attain an appropriate balance between local and global search. Aft... [more]

Wave power is an eco-friendly power generation method. Owing to the highly volatile nature of wave energy, the application of prediction techniques for power generation, failure diagnosis, and operational efficiency plays a key role in the successful operation of wave power plants (WPPs). To this end, we propose the following approaches: (i) deriving the correlation between highly volatile data such as wave height data and sensor data in an oscillating water column (OWC) chamber; (ii) development of an optimal training model capable of accurate prediction of the state of the wave energy converter (WEC) based on the collected sensor data. In this study, we developed a big data analysis system that can utilize the machine learning framework in KNIME (an open analysis platform), and to enable smart operation, we designed a training model using a digital twin of an OWC−WEC that is currently in operation. Using various machine learning models, the pressure of the OWC chamber was predicted,... [more]

Electric power load forecasting is an essential task in the power system restructured environment for successful trading of power in energy exchange and economic operation. In this paper, various regression models have been used to predict the active power load. Model optimization with dimensionality reduction has been done by observing correlation among original input features. Load data has been collected from a 33/11 kV substation near Kakathiya University in Warangal. The regression models with available load data have been trained and tested using Microsoft Azure services. Based on the results analysis it has been observed that the proposed regression models predict the demand on substation with better accuracy.

Decentralized electricity systems based on variable renewable energy (VRE) sources such as wind power can provide affordable, dependable, and modern energy in a manner consistent with the Paris Agreement. Such sources are, however, sensitive to extreme values of climatic factors—an issue that may jeopardize power system reliability. As a resource-rich region with a high proportion of rural population without access to electricity, Africa has been of wide interest in studies on VRE-based electricity generation. Nevertheless, there is still a major gap in our continent-scale understanding of the wind power potential and its variability at different time scales, as well as the influence of low-wind-resource periods in Africa. Using ERA5 hourly estimates of wind speed, the present study investigated the adequacy and temporal variability of local wind power potential across Africa over the 2000−2017 period. The results indicated that design requirements of wind power systems are, on average... [more]

This study determines the relationship between the increase in size of dry bulk carriers and container ships and the changes in sustainable shipping performance. It measures the elasticities of shipping costs for bulk carriers and container ships. Using regression, it derives the functions of the daily and unit costs of shipping with respect to the size of dry bulk carriers and container ships. The estimated daily and unit cost elasticities and cost models reveal significant but diversified impacts of vessel size on dry bulk and container shipping cost and its components, other operating capital, and fuel costs. Findings: Dry bulk carriers and containership size mean elasticities of daily operating costs estimates respectively: total operating costs 0.291 and 0.552, other operating cost (labor cost included) 0.238 and 0.328, capital costs 0.329 and 0.765, fuel costs 0.289 and 0.462; dry bulker and container ship unit shipping mean elasticity respectively: full operating costs (−0.751)... [more]

Small hydropower (SHP) plants are advantageous as they have a short construction period and can be easily maintained. They also have a higher energy density than other alternative energy sources as environmentally-friendly energy sources. In general, hydropower potential is estimated based on the discharge in the river basin, and the discharge can be obtained from the stage station in the gaged basin. However, if there is no station (i.e., ungaged basin) or no sufficient discharge data, the discharge should be estimated based on rainfall data. The flow duration characteristic model is the most widely used method for the estimation of mean annual discharge because of its simplicity and it consists of rainfall, basin area, and runoff coefficient. Due to the characteristics of hydroelectric power depending on the discharge, there is a limit to guaranteeing the accuracy of estimating the generated power with only one method of the flow duration characteristic model. Therefore, this st... [more]

This article proposes a plan to replace real-time power with constant power from the grid to reduce costs and reduce the impact of the micro-grid on the main grid at the same time. Most of the peak electricity consumption periods of universities or some enterprise institutions are during the daytime. If solar energy can be used reasonably at this time, it can provide a good guarantee of peak power. In this study, a grid-linked solar-plus-storage micro-grid was used to supply power to a university located in Okinawa, Japan. The non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize the model size, and the loss of power supply probability (LPSP), life cycle cost (LCC), and waste of energy (WE) were taken as the optimization indicators. For this study, three scenarios were considered where the first scheme (Case 1) was a comparison scheme, which used a PV battery and real-time power from the infinity bus. Both the second and third cases used constant power. While Case 2... [more]

The mechanical integrity of a lithium ion battery cell can be evaluated using finite element (FE) simulation techniques. In this study, different FE modelling approaches including heterogeneous, homogeneous, hybrid and sandwich methods are presented and analysed. The basic capabilities of the FE-methods and their suitability to simulate a real mechanical safety test procedures on battery cells are investigated by performing a simulation of a spherical indentation test on a sample pouch cell. For each modelling approach, one battery cell model was created. In order to observe the system behaviour, relevant parametric studies involving coefficient of friction and failure strain of separator were performed. This studied showed that these parameters can influence the maximum force and the point of failure of the cell. Furthermore, the influence of an anisotropic separator on the results was also investigated. The advantages and disadvantages of each modelling approach are discussed and a s... [more]

For two decades, the Thai government has been promoting ethanol and biodiesel consumption through tax measures and price subsidies. Although this policy has substantially increased the consumption and production of biofuels, there is concern regarding its future fiscal burden. Due to fiscal constraints, the Thai government has planned to completely terminate the biofuel subsidy by 2022. This study aims at examining the economy-wide impacts of removing the biofuel subsidy and also conducting simulations of alternative scenarios, i.e., improving the yield of energy crops and reallocating the burden to expand capital investment in energy crop plantations. A recursive dynamic computable general equilibrium (CGE) model was used as the main quantitative method to conduct four simulation scenarios. This model was validated by comparing the simulation results with the actual 2015−2019 data and showed low values of root mean square error (RMSE). The simulation results indicate that solely termi... [more]

From January 2020, the International Maritime Organization has regulated ship emissions to reduce sulfur content. As an alternative to this, LNG bunkering was proposed, and infrastructure and ships were deployed. Therefore, we used analytic hierarchy process AHP techniques to determine optimal methods of LNG bunkering for shipyard safety. First, we conducted a literature survey on the concept and type of LNG bunkering, global LNG bunkering trends, and features of Japan and South Korea cases and compared them. Thereafter, an expert survey was conducted, and survey data was analyzed using AHP techniques. Finally, we derived optimal methods applicable to shipyard industry. The analytical results revealed that the derived priority of the optimal LNG bunkering method of shipyard was in the order of the STS method, TTS method, and the PTS method. The result of this study can serve as a theoretical basis to make LNG bunkering safer and more economical in shipyards to prepare for the expansion... [more]

A theoretical justification and computation of the optimum values of the two longitudinal tilt angles of a small-scale linear Fresnel reflector is provided. The optimum angle of the mobile structure is proved to be half the latitude of the geographic location, while the optimum angle of the secondary reflector system is proved to be equal to that latitude. Brute-force verification is carried out for five EU cities, each in one of the five European climate zones.

The objective of this work is to propose and apply a methodology to obtain the cost of industrial process shutdowns due to voltage sag and short interruption. A field survey, aided by a specific questionnaire, was carried out in several industries connected to medium voltage networks, in the states of Espírito Santo and São Paulo in Brazil. The results obtained were the costs per event and the costs per demand in a total of 33 companies in 12 different types of activities. It is noteworthy that this survey brings a relevant technical contribution to the electricity sector, helping to fill, even partially, an existing gap in both national and international literature.

To decrease the cost of fuel cell manufacturing, the amount of platinum (Pt) in the catalyst layer needs to be reduced. In this study, ionomer gradient membrane electrode assemblies (MEAs) were designed to reduce Pt loading without sacrificing performance and lifetime. A two-layer stratification of the cathode was achieved with varying ratios of 28 wt. % ionomer in the inner layer, on the membrane, and 24 wt. % on the outer layer, coated onto the inner layer. To study the MEA performance, the electrochemical surface area (ECSA), polarization curves, and electrochemical impedance spectroscopy (EIS) responses were evaluated under 20, 60, and 100% relative humidity (RH). The stratified MEA Pt loading was reduced by 12% while maintaining commercial equivalent performance. The optimal two-layer design was achieved when the Pt loading ratio between the layers was 1:6 (inner:outer layer). This MEA showed the highest ECSA and performance at 0.65 V with reduced mass transport losses. The integr... [more]

This study attempt to fill the research gap by figuring out the dynamic effects of foreign capital inflows effect on renewable energy and non-renewable consumption by using the time series non-linear ARDL approach for BRICS from 1991 to 2019. Non-linear ARDL estimates show that positive change in foreign capital inflows has a positive effect on renewable consumption in Brazil, India, and South Africa in long run. Also, the negative change in foreign capital inflows exhibits negatively liked with renewable energy consumption in BRICS economies, except Russia in long run. We find that positive shock in foreign capital inflows tends to increase non-renewable energy consumption in BRICS except India in the long run. Finding suggests that negative change in foreign capital inflows has negative impacts on non-renewable energy consumption in India and Brazil, while the positive effect in only China in the long run.

The Ni-containing catalysts based on ceria−zirconia doped with Ti and Ti+Nb were prepared by the solvothermal method in supercritical fluids. Ni deposition was carried out by incipient wetness impregnation and the one-pot technique. All materials were investigated by a complex of physicochemical methods (XRD, BET, TEM, H2-TPR). Samples catalytic properties were studied in methane dry reforming in the plug-flow reactor. Conversions of CH4 and CO2, H2/CO ratio, and CO and H2 yields were measured, and detailed kinetics analysis was carried out. The influence of Ni loading method and support modification on the catalytic behavior in the methane dry reforming process was studied. The preparation method of catalysts affects the textural characteristics. For one-pot samples, pore volume and surface area are lower than for impregnated samples. For catalysts on modified supports, strong metal−support interaction was shown to increase catalytic activity. A reduction pretreatment of samples was s... [more]

Based on resource carrying capacity, this study used the revised theory of relative resource carrying capacity (RRCC) and introduced an innovative concept of relative fossil energy carrying capacity (RFECC), which evaluates the degree of fossil energy sustainability based on the relationship between economy, population, and environment. This study took China and the United States as the study objects, took the whole country as the reference area, and calculated the RFECC of population, economic, and environmental resources from 2000 to 2018. Therefore, based on the comparative analysis, the following conclusions were drawn: (i) there is a big difference in the RFECC between China and the United States, which is manifested in the inverted U-shaped trend in China and the U-shaped trend in the United States; (ii) the relative fossil energy carrying states in China and the United States are different, mainly reflected in the economy and environment; (iii) the gap in RFECC between China and... [more]

Trolleybus transport refers to contemporary challenges related to a reduction in emissions of greenhouse gases and CO2 into the atmosphere formulated by international institutions, such as the United Nations, the Organisation for Security and Co-operation in Europe, or the European Union. Departure from fossil fuels in urban transport is one of the key challenges for the coming years. Trolleybuses are an important tool in this task, even though their importance was declining in the past. Nowadays, due to, among others, technological development, in particular the availability of high-capacity batteries, their long life and low weight, trolleybus transport is becoming popular again. The use of the existing overhead contact infrastructure of the trolleybus network and small on-board batteries allow expanding the spatial accessibility of zero-emission public transport. Thus, this reduces the social differentiation in access to environmentally friendly transport that does not emit pollutan... [more]

Due to the rapid increase in electric vehicles (EVs) globally, new technologies have emerged in recent years to meet the excess demand imposed on the power systems by EV charging. Among these technologies, a mobile energy storage system (MESS), which is a transportable storage system that provides various utility services, was used in this study to support several charging stations, in addition to supplying power to the grid during overload and on-peak hours. Thus, this paper proposes a new day-ahead optimal operation of a single MESS unit that serves several charging stations that share the same geographical area. The operational problem is formulated as a mixed-integer non-linear programming (MINLP), where the objective is to minimize the total operating cost of the parking lots (PLs). Two different case studies are simulated to highlight the effectiveness of the proposed system compared to the current approach.

The main objective of the current work was to enhance the transformer fault diagnostic accuracy based on dissolved gas analysis (DGA) data with a proposed coupled system of support vector machine (SVM)-bat algorithm (BA) and Gaussian classifiers. Six electrical and thermal fault classes were categorized based on the IEC and IEEE standard rules. The concentration of five main combustible gases (hydrogen, methane, ethane, ethylene, and acetylene) was utilized as an input vector of the two classifiers. Two types of input vectors have been tested; the first input type considered the five gases in ppm, and the second input type considered the gases introduced in the percentage of the sum of the five gases. An extensive database of 481 had been used for training and testing phases (321 data samples for training and 160 data samples for testing). The SVM model conditioning parameter “λ” and penalty margin parameter “C” were adjusted through the bat algorithm to develop a maximum accuracy rate... [more]

The aim of this study was the investigation of the effect of growth conditions of energy willow (Salix viminalis L.) on its physical and chemical parameters towards lignocellulosic biofuels. This work is linked to the global trend of replacing fossil fuels (coal, oil, natural gas) with energy and renewable fuels. This energy transition is dictated by the reduction of the human-induced greenhouse effect (to the greatest extent by industrial development). Changing from traditional to renewable energy sources results in industry becoming less dependent on fuels whose sources are beginning to run out, and in energy processing being broken down into smaller sectors with greater flexibility to change and less susceptibility to failure. The use of lignocellulosic raw materials such as wood, straw, food industry waste, wood, and post-consumer products such as old furniture for energy purposes allows the use of substances which bind the greenhouse gas carbon dioxide in their cellular structure... [more]

In the course of our investigations, we burned high-quality logs as well as wood briquettes in a conventional, manually fed mixed-fired boiler, under different operating parameters. Based on the evaluation of the measurement results, there is a significant difference in terms of recoverable energy and carbon monoxide emissions for the two fuels burned in the same device at different air supply parameters. Studies have shown that a constantly changing position of the draft control door has an adverse effect on carbon monoxide emissions as well as the energy produced. In the case of a constant draft door setting, the preset values that can be considered ideal for energy yield and CO emissions were determined for the two fuel types. The obtained results were compared with the requirements according to the MSZ EN 303-5 standard.

Facilitating the proper handling of water is one of the main challenges to overcome when trying to improve fuel cell performance. Specifically, enhanced removal of liquid water from the porous gas diffusion layers (GDLs) holds a lot of potential, but has proven to be non-trivial. A main contributor to this removal process is the gaseous transport of water following evaporation inside the GDL or catalyst layer domain. Vapor transport is desired over liquid removal, as the liquid water takes up pore space otherwise available for reactant gas supply to the catalytically active sites and opens up the possibility to remove the waste heat of the cell by evaporative cooling concepts. To better understand evaporative water removal from fuel cells and facilitate the evaporative cooling concept developed at the Paul Scherrer Institute, the effect of gas speed (0.5−10 m/s), temperature (30−60 °C), and evaporation domain (0.8−10 mm) on the evaporation rate of water from a GDL (TGP-H-120, 10 wt% PT... [more]

In the construction of ecological civilization, green innovation has become an important driving force for the sustainable development of state-owned enterprises (SOEs). This paper uses panel data of state-owned listed enterprises from 2008 to 2019 to explore mixed-ownership reform’s influence on the green transformation of SOEs and its specific mechanisms. The results show that the diversity of mixed shareholders, the depth of mixed equity, and the restriction of mixed equity significantly promote the SOEs’ green innovation. Moreover, there are distinctions in the impact of the shareholding ratio of heterogeneous shareholders on green innovation. Only the increase in the shareholding ratio of foreign shareholders has a positive correlation with green innovation. The mechanism tests indicate that the mixed-ownership reform plays a governance role in the green transformation of SOEs by optimizing the reasonable allocation of environmental protection subsidies and propelling environmenta... [more]

Hydrothermal carbonization (HTC) is considered as an efficient and constantly expanding eco-friendly methodology for thermochemical processing of high moisture waste biomass into solid biofuels and valuable carbonaceous materials. However, during HTC, a considerable amount of organics, initially present in the feedstock, are found in the process water (PW). PW recirculation is attracting an increasing interest in the hydrothermal process field as it offers the potential to increase the carbon recovery yield while increasing hydrochar energy density. PW recirculation can be considered as a viable method for the valorization and reuse of the HTC aqueous phase, both by reducing the amount of additional water used for the process and maximizing energy recovery from the HTC liquid residual fraction. In this work, the effects of PW recirculation, for different starting waste biomasses, on the properties of hydrochars and liquid phase products are reviewed. The mechanism of production and evo... [more]