Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently,... [more]

Wind farm (WF) equivalence is an effective method to achieve accurate and efficient simulation of large-scale WF. Existing equivalent models are generally suitable for one certain or very few scenarios, and have difficulty reflecting the multiple aspects of dynamic processes of WF. Aiming at these problems, this paper proposes an equivalent model of WF based on multivariate multi-scale entropy (MMSE) and multi-view clustering. Firstly, the influence of the factors on the dynamic process of the wind turbine (WT) is discussed, including control mode, wind speed and its wake effect, resistance of crowbar resistor and so on. The relationship between these factors and the dynamic equivalence of WF is analyzed. Secondly, an overview of MMSE is given, and the applicability of MMSE on WF equivalence is analyzed. On this basis, this paper proposes the extraction process of a WT clustering indicator using MMSE. Then, the multi-view fuzzy C means (MV-FCM) algorithm is used for the clustering of W... [more]

The bedding planes of unconventional oil and gas reservoirs are relatively well developed. Bedding planes directly interfere with hydraulic fracture expansion. Determining how bedding planes influence hydraulic fractures is key for understanding the formation and evolution of hydraulic fracturing networks. After conducting X-ray diffraction analysis of shale, we used Python programming to establish a numerical model of mineral heterogeneity with a 0-thickness cohesive element and a bedding plane that was globally embedded. The influence of the bedding-plane angle on hydraulic fracture propagation was studied. Acoustic emission (AE) data were simulated using MATLAB programming to study fracture propagation in detail. The numerical simulation and AE data showed that the propagation paths of hydraulic fractures were determined by the maximum principal stress and bedding plane. Clearer bedding effects were observed with smaller angles between the bedding surface and the maximum principal s... [more]

One of the main topics that generate the interest of experts nowadays involves the processes of organic matter chemical transformation during heavy and shale oil reservoirs’ development via thermally enhanced oil recovery. It is common knowledge that the host rock has a catalytic effect on the ongoing processes. In addition, oil transformation is mostly associated with destructive processes of resins and asphaltenes molecules. As a result, this would provide an increase in oil mobility as a result of kerogen destruction in shale oil. This ensures the formation of synthetic oil and an increase in the filtration characteristics of the rock. Besides, iron-containing compounds in the composition of the rock are catalytically active in the above processes. Moreover, clay minerals have high catalytic activity for many reactions of organic matter transformation. This review considers publications that study the role played by the rock and its individual components in the processes of in situ... [more]

Small-scale combined heat and power (micro-CHP or mCHP) plants generate heat in the process of localised electricity production that can usefully be captured and employed for domestic space and water heating. Studies of the relative merits of three alternative network-connected mCHP plants are reviewed based respectively on an Internal Combustion engine (ICE), a Stirling engine (SE), and a Fuel Cell (FC). Each plant will, in most cases, result in lower carbon dioxide (CO2) emissions, relative to those from the most efficient condensing boilers. In addition, they lead to operational cost savings for the consumer, depending on house type. However, their capital costs are presently more expensive than a conventional boiler, with the FC being prohibitively so. The ICE and SE variants display the greatest economic and environmental benefit. Nevertheless, the performance and costs associated with these innovative technologies have rapidly improved over the last decade or so. Comparisons are... [more]

Electricity markets are characterised by high sensitivity to variations in supply and demand conditions. However, they also exhibit a number of specific characteristics, including large daily, weekly, and seasonal price fluctuations. The aim of this article is to assess the impact of fluctuations in the industry’s output on wholesale electricity prices. Results were compared for the Nord Pool markets, with a high share of renewable energy supply, and the HUPX markets, where fossil fuel and/or nuclear energy supply dominates. The results obtained generally indicate the positive impact of changes in the industry’s output on wholesale electricity prices. This impact was stronger in the HUPX markets and for periods in daily and weekly cycles with higher energy demands. The results indicate that the sensitivity of electricity prices to fluctuations in the industry’s output is lower in markets with a higher share of renewable energy, especially for periods with higher energy demands.

New thermal management technology is widely developed in new energy industries, such as electric vehicles, IoT sensors, photothermal energy conversion, ground thermal energy utilization and propulsion systems [...]

With the need for more environmentally friendly transportation and the wide deployment of electric and plug-in hybrid vehicles, electric vehicle (EV) charging stations have become a major issue for car manufacturers and a real challenge for researchers all over the world. Indeed, the high cost of battery energy storage, the limited EV autonomy and battery lifespan, the battery charging time, the deployment cost of a fast charging infrastructure, and the significant impact on the power grid are the origin of several research projects focused on advanced power electronics topologies and the optimization of the EV charging stations in terms of power transfer and geographical location. Three charging levels can be distinguished, which differ in terms of output power and charging time. The higher the level of charging, the faster the charging process, as more power is delivered to the vehicle at the expense of power quality issues and disturbances. Moreover, three types of charging systems... [more]

This paper constructs an open economy dynamic stochastic general equilibrium (DSGE) model with oil to investigate the transmission mechanism and impact effects of oil price fluctuations driven by different factors on China’s macroeconomy using quarterly data from 1996 to 2019. The results show that the international crude oil supply-driven oil price decline promotes positive output growth in the short run through the positive cost effect of the supply channel, and the production regulation cost will dampen the incentive to invest in the new energy sector in the long run. Domestic economic development demand-driven oil price increases act on the demand channel, driving output and oil prices to fluctuate in the same direction, generating a negative real balance effect on the economy through the interest rate channel. The oil-specific demand driven by foreign nominal interest rate shocks is transmitted through the exchange rate channel, triggering imported inflation, lower aggregate deman... [more]

As an unconventional natural gas, coalbed methane (CBM) has been recognized as a significant fuel and chemical feedstock that should be recovered. Permeability is a key factor that controls CBM transport in coal. The slippage effect is an influential phenomenon that occurs during gas penetration processes, especially in low-permeable media. Apparent permeability may differ greatly from intrinsic permeability due to gas slippage. However, the gas slippage effect has not been considered in most analytical permeability models. Based on the cubic law, a new analytical model suited for the permeability analysis of coal under different stress conditions is derived, taking into consideration gas slippage and matrix shrinkage/swelling due to gas desorption/adsorption. To enhance its application, the model is derived under constant hydrostatic stress and pore pressure. The new analytical model is then compared with the existing models, and its reliability is verified by the comparison between t... [more]

District energy is undergoing a deep transformation towards higher efficiency and greater flexibility through the promotion of renewable energy and waste energy sources [...]

The primary aim of this study was to assess and classify selected EU countries to groups differing in terms of the degree of implementation of innovative energy technologies to alleviate adverse externalities in road transport. This aim was realised using three groups of research methods: collection of empirical data, data processing and presentation of study outcomes. When collecting the research material, the authors used the method of critical literature review and the documentation method. The research material was processed using the agglomerative clustering technique, which was one of the hierarchical clustering methods. The distance between objects (here, selected EU countries) was determined based on the Euclidean distance. The outcome of this analysis was a dendrogram, which constitutes a graphical interpretation of obtained results. The study was conducted on 21 EU countries. The analyses covered the years 2013−2019. The sources of materials included literature on the subject... [more]

Accurate state characterization of batteries is conducive to ensuring the safety, reliability, and efficiency of their work. In recent years, ultrasonic non-destructive testing technology has been gradually applied to battery state estimation. In this paper, research on the state characterization of lithium-ion batteries based on ultrasonic guided wave (UGW) scanning is carried out. The laser Doppler vibrometer (LDV) and the X-Y stage are used to obtain the surface scanning UGW signal and the line scanning UGW signal of lithium-ion batteries under different states of charge and different aging degrees. The propagation law of UGWs in the battery is analyzed by surface scanning signals, then the energy spectrum of the signals is calculated, showing that the aging of the battery attenuates the transmission energy of UGWs. The “point” parameters are extracted from the scanning point signals. On this basis, the “line” parameters composed of line scanning multi-point signals are extracted. B... [more]

Petrol directly impacts the ability of and extent to which households can engage in day-to-day activities and ultimately directly influences the aggregate economic activity. Petrol price increases can lead to major economic disruption, especially among the most vulnerable, such as low-income families. In Australia, petrol prices differ substantially between metropolitan and regional areas, and regional drivers must pay more for purchasing petrol than those in capital cities. This research explored why retail petrol prices vary from one city to another within and between Australian regions. In this study, clustering methods and panel models will be used to identify factors that cause price differences. The findings revealed that a considerable part of the price differences arose from specific characteristics of cities that influence the demand and supply of petrol, thereby causing variations in price decisions. Petrol prices were substantially influenced by wholesale petrol prices, oil... [more]

In order to accurately predict China’s future total energy consumption, this article constructs a random forest (RF)−sparrow search algorithm (SSA)−support vector regression machine (SVR)−kernel density estimation (KDE) model to forecast China’s future energy consumption in 2022−2030. It is explored whether China can reach the relevant target in 2030. This article begins by using a random forest model to screen for influences to be used as the input set for the model. Then, the sparrow search algorithm is applied to optimize the SVR to overcome the drawback of difficult parameter setting of SVR. Finally, the model SSA-SVR is applied to forecast the future total energy consumption in China. Then, interval forecasting was performed using kernel density estimation, which enhanced the predictive significance of the model. By comparing the prediction results and error values with those of RF-PSO-SVR, RF-SVR and RF-BP, it is demonstrated that the combined model proposed in the paper is more... [more]

Renewable power is expected to increase drastically in the coming years due to the energy transition. A large part of the newly installed generators will be connected to the power system through inverters and electronic converters, whose behaviour differs from the generators connected synchronously to the network. One of the main differences is the current contribution during symmetrical and asymmetrical faults which can affect protection systems. New grid codes establish requirements for fast current injection, but the converter’s maximum current limitations during faults make it difficult to establish control strategies for such current contribution. This paper studies the performance of faulted phase selector algorithm of a commercial relay under the current contribution from renewables before unbalanced faults. Two positive and negative sequence current injection strategies in compliance with new Spanish grid code requirements are proposed and tested under fault conditions in HiL (... [more]

A significant contribution to the reduction of carbon emissions will be enabled through the transition from a centralised fossil fuel system to a decentralised, renewable electricity system. However, due to the intermittent nature of renewable energy, storage is required to provide a suitable response to dynamic loads and manage the excess generated electricity with utilisation during periods of low generation. This paper investigates the use of stationary hydrogen-based energy storage systems for microgrids and distributed energy resource systems. An exploratory study was conducted in Australia based on a mixed methodology. Ten Australian industry experts were interviewed to determine use cases for hydrogen-based energy storage systems’ requirements, barriers, methods, and recommendations. This study suggests that the current cost of the electrolyser, fuel cell, and storage medium, and the current low round-trip efficiency, are the main elements inhibiting hydrogen-based energy storag... [more]

The reverse electrodialysis heat engine (REDHE) is a promising salinity gradient energy technology, capable of producing hydrogen with an input of waste heat at temperatures below 100 °C. A salinity gradient drives water electrolysis in the reverse electrodialysis (RED) cell, and spent solutions are regenerated using waste heat in a precipitation or evaporation unit. This work presents a non-equilibrium thermodynamics model for the RED cell, and the hydrogen production is investigated for KCl/water solutions. The results show that the evaporation concept requires 40 times less waste heat and produces three times more hydrogen than the precipitation concept. With commercial evaporation technology, a system efficiency of 2% is obtained, with a hydrogen production rate of 0.38 gH2 m−2h−1 and a waste heat requirement of 1.7 kWh gH2−1. The water transference coefficient and the salt diffusion coefficient are identified as membrane properties with a large negative impact on hydrogen producti... [more]

This article is devoted to the following issues: calculating the values of temperatures obtained by simulating welding heating and the subsequent implementation of the welding process at the given mode parameters made it possible to obtain a welded joint of the rotor with an improved initial structure and increased mechanical properties, hydrogen resistance and durability by up to 10−15%; simulating welding heating in the areas of fusion, the overheating and normalization of the HAZ and the formation of austenite grains; specified welding heating creates the conditions for the formation of new products of austenite decomposition in the form of sorbitol in the area of the incomplete recrystallization of the HAZ. In air and gaseous hydrogen, the destruction of the combined joints took place on the weld metal, as well as on the fusion areas, the overheating and the incomplete recrystallization of the HAZ of 20H3NMFA steel as the base metal. Structural materials have a relatively low stren... [more]

In order to decarbonize the rail industry, the development of innovative locomotives with the ability to use multiple energy sources, constituting hybrid powertrains, plays a central role in transitioning from conventional diesel trains. In this paper, four configurations based on suitable combinations of fuel cells and/or batteries are designed to replace or supplement a diesel/overhead line powertrain on a real passenger train (the Hitachi Blues) tested on an existing regional track, the Catanzaro Lido−Reggio Calabria line (Italy), managed by Trenitalia SpA. (Italy). The configurations (namely battery−electrified line, full-battery, fuel cell−battery−electrified line, and fuel cell−battery) are first sized with the intention of completing a round trip, then integrated on board with diesel engine replacement in mind, and finally occupy a portion of the passenger area within two locomotives. The achieved performance is thoroughly examined in terms of fuel cell efficiency (greater than... [more]

In a developing country such as Malaysia, studies of determinants which influence residential consumers of the Battery Energy Storage System (BESS) are limited. This paucity of studies was the catalyst for this study and its aim to investigate the factors affecting acceptance by Malaysian residential consumers of BESS as it relates to the Technology Acceptance Model Theory. A sample of 331 residential consumers indicated that consumer attitudes, social norms and self-efficacy, or the perception of behavioral control, had a positive and significant relationship with the intention to use BESS. Additionally, trust was a factor that had a significant effect on the consumers’ perceptions of cost, benefits and anticipated effects. All these variables significantly affect consumer attitudes. These findings provide important insights into BESS and facilitate the development of policies and practices relating to BESS in developing countries such as Malaysia.

Renewable and clean energy sources are being integrated into the United States’ modern energy industry to mitigate climate change effects, creating a more complex network of energy production, distribution, and consumption. This study defines the state of Maryland’s energy industry as a network of producers and consumers and analyzes the network’s characteristics by using ecological network analysis (ENA), an analytical tool useful for identifying a system’s indirect effects. The energy industry within Maryland is analyzed over a nine-year time span to understand how its evolution is influencing the network’s characteristics. Maryland’s renewable portfolio standard (RPS) for the year 2030 is then simulated by adjusting renewable and non-renewable energy sources according to energy trends and related state policy. Results from the ENA over the nine-year period of 2010−2019 indicate that the energy industry is highly linear. While typical cycling indices range from 5−15% in ecological en... [more]

Membrane distillation (MD) is a thermal-based membrane operation with high potential for the treatment of aqueous streams. However, its implementation is limited and only few examples of MD pilots can be found in desalination. One of the reasons behind this is that MD requires thermal energy for promoting the evaporation of water, which implies higher energy consumption with respect to pressure-driven membrane operations, like reverse osmosis (RO). Recently, among the different methods investigated to improve the thermal efficiency of MD, attempts for obtaining a localized heating of the feed, close to the membrane surface, were carried out. This work reviews experimental activities on the topic, dealing with both modified membranes, used under solar irradiation or coupled to an electric source, and specifically designed heated modules. The main results are reported and points of action for further optimization are identified. In particular, although at an early stage, this type of app... [more]

Direct-drive generators are an attractive candidate for wind power application since they do not need a gearbox, thus increasing operational reliability and reducing power losses. However, this is achieved at the cost of an increased generator size, larger inverter and decreased thermal performance. The associated cooling system is therefore crucial to keep the generator and inverter sizes down and to operate within the safe thermal limits. Various cooling techniques suitable for generators are therefore reviewed and analyzed in this paper. The performance and maintenance requirements are unavoidable compromises that need to be investigated together, especially for large generators. The location of the wind turbine is also important and dictates critical issues such as accessibility and maximum size. The key novelty in this paper is the assessment of the cooling methods based on generator size, reliability and maintenance requirements.

To mine the battery’s health factors more comprehensively and accurately identify the lithium battery’s State of Health (SOH), an Improved Douglas−Peucker feature extraction algorithm is proposed, and the LAOS-XGboost model is proposed to be used to predict the SOH of the battery. Firstly, to solve the problem that the traditional Douglas−Peucker algorithm has difficulties extracting curve features in a fixed dimension, the Douglas−Peucker algorithm is improved by de-thresholding. Then, the Wrapper method combined with the Improved Douglas−Peucker algorithm is used to construct the feature engineering of battery life prediction, and the optimal feature subset is obtained. Then, LAOS-XGboost is used to establish a battery SOH prediction model; finally, this model is used to predict the SOH of different batteries and the same battery, and the robustness of the model is analyzed. The experimental results show that the R2 of all XGboost models is higher than 0.97 in the prediction experime... [more]