Microalgae, a renewable bio-resource, are considered a potential value-added commodity and a tool to combat climate change. Microalgal research has received worldwide attention recently. Different perspectives have been explored, but cultivation in outdoor photobioreactors (PBRs) is still a less explored field. This review summarizes the studies conducted on the microalgae cultivated in outdoor PBRs only. The locations, algal strains, PBRs, and cultivation media used in these studies were identified and tabulated. Different aspects of outdoor algal cultivation in PBRs, such as temperature control, light intensity control, photosynthetic efficiency (PE), the outdoor adaptation of strains, PBR designs, and algal growth and biochemical composition variation from the weather, were studied and reviewed. A brief review of downstream processes and environmental and economic impacts was also conducted. This review summarizes what has been carried out in this field so far and will help research... [more]

The China Fusion Engineering Test Reactor (CFETR), a superconducting magnetic confinement tokamak fusion reactor, will develop a high-performance torus cryopump to pump torus plasma exhaust gas. The inlet valve is one of the key components of the cryopump, and it is used to isolate the cryopump from the plasma for regeneration, to control the pumping speed of the cryopump, and to operate as a pressure relief valve in case of a failure, such as the cryopipe breaking inside the cryopump chamber. This paper presents a novel inlet valve. Ensuring that the design of the inlet valve meets the above requirements will be a challenge. In order to verify the reliability of the inlet valve, its critical components are analyzed and optimized by the Finite Element Method. The effect of the stroke of the inlet valve on pumping performance is then estimated by the Monte Carlo Method, and the pressure profile in the whole flow field is studied to predict the cryopump’s behavior. Finally, the seismic c... [more]

A solid-state heat pump using the electrocaloric effect (ECE) provides a new idea for the future development of heat pumps. However, most of the electrocaloric (EC) heat pumps presented in the literature are low in efficiency and use at least one moving part, which significantly reduces the reliability of the heat pump and adds to its complexities. In this context, combining the positive and negative ECEs, we proposed a plate-laminar non-mobile EC heat pump adopting Gallium-based liquid metal as an intermediate medium to guarantee highly efficient heat transfer. Numerical simulation in COMSOL Multiphysics has been performed to investigate the correlation between different operating parameters and the performance of the EC heat pump. Changing the temperature span only, a COP of 8.13 and a UVHP of 746.1 W·dm−3 were obtained at a temperature span of 7 K. It was also found that the UVHP increased by 28.45% and COP increased by 25.46% after adding one layer of EC material. The electric-indu... [more]

The aim of this study was to investigate and compare investment opportunities in the financial markets of Saudi Arabia, a net oil-exporting country, and Turkey, a net oil-importing country, in the Middle East. The international capital asset pricing model (ICAPM) was extended by considering local factors proxied by country risk (CR) and oil price risk exposures of the excess returns of Saudi Arabia and Turkey. In this study, we employed the extended ICAPM in a two-state Markov-switching setting for the sample period of January 2005 to December 2018 to explore whether the risk premium is time-varying. The results suggested that systematic risk is time-varying depending on the state of the financial markets and is affected by both global and local factors. Saudi Arabia offered higher excess returns during the high-volatility regime compared to that of the World Index and enjoyed higher returns during the low-risk regime from oil price shocks. Turkey was negatively affected by oil price s... [more]

CO2 geological storage projects are an essential tool for China to achieve the double carbon target of energy savings and emission reductions. In order to safely and effectively control the implementation of injection projects and monitor the dynamics of CO2 injection, multi-dimensional and multi-disciplinary monitoring tools are required. Among them, microseismic monitoring is a key technology for predicting reservoir dynamics and reflecting reservoir geomechanical behavior. Such monitoring has been carried out previously for reservoirs in other countries, but experimental projects are also gradually being developed in China. In this paper, we focus on the research and analysis results of microseismic monitoring of carbon storage projects in various work areas. For different reservoir conditions, we explore combinations of the monitoring implementation methods in China, comparing the differences in each work area. We propose a joint well and ground microseismic monitoring method and a... [more]

Nowadays, almost 30% of total energy consumption (130 EJ) is consumed for the operation of buildings, mainly by space heating/cooling and ventilation systems, hot water preparation systems, lighting, and other domestic appliances. To improve the energy efficiency of buildings, several countries are promoting the use of renewable energy. The most promising systems include active and passive solar installations. In passive systems, the solar energy is collected, stored, reflected, or distributed by the roof ponds, natural convective loops, and the most popular direct gain walls and thermal storage walls (known as Trombe walls). This paper reviews the experimental and numerical studies devoted to the different solutions of Trombe walls, including solar chimneys integrated on the vertical walls, classic Trombe walls, Trombe walls with incorporated phase change materials, and photovoltaic Trombe walls. The actual state of the art is presented in the context of reducing energy consumption an... [more]

In this paper it is proposed the displacement control of a bearingless induction machine (BIM) with split winding and optimized drive structure using Active Disturbance Rejection Control (ADRC). Considering that the BIM is a multivariable, nonlinear, and time-varying system with coupled variables, advanced control techniques can be useful in order to make the system operate efficiently and with good dynamic performance. The ADRC considers the total disturbance, composed of unmodeled dynamics, nonlinearities, uncertainties, and load variations, as an extended state and estimates it in real-time through a state observer. This increases the overall robustness of the control system to disturbances of different natures. The application of the ADRC technique on the radial position control of the BIM used in this work showed that a Linear version of ADRC is not able to compensate for radial load disturbances but this drawback can be solved by the use of a nonlinear observer in the ADRC struct... [more]

Having a high theoretical capacity density of 4200 mAh g−1, silicon has been highlighted as one of the most promising anode materials for lithium-ion batteries. Countless silicon-based materials have been proposed and reported in research articles, mostly synthesized using bottom-up methods. While the infamous volume expansion issue can be settled with the bottom-up processes, the complicated protocols and high cost leave a non-neglectable gap between laboratory-scale and mass production. The top-down ball-milling method is still favored by industrial suppliers because of its simplicity and cost-effectiveness, even with compromised electrochemical performances. This paper reviews the latest development of ball-milling-based silicon anode materials. Although the ball-milling process seems straightforward, the procedures and parameters influencing the product have hardly been discussed in research papers compared to the bottom-up ones. This paper reviews recent advances in ball-milling-b... [more]

Geothermal energy is considered an essential renewable resource to generate flexible electricity. Geothermal resource assessments conducted by the U.S. Geological Survey showed that the southwestern basins in the U.S. have a significant geothermal potential for meeting domestic electricity demand. Within these southwestern basins, play fairway analysis (PFA), funded by the U.S. Department of Energy’s (DOE) Geothermal Technologies Office, identified that the Tularosa Basin in New Mexico has significant geothermal potential. This short communication paper presents a machine learning (ML) methodology for curating and analyzing the PFA data from the DOE’s geothermal data repository. The proposed approach to identify potential geothermal sites in the Tularosa Basin is based on an unsupervised ML method called non-negative matrix factorization with custom k-means clustering. This methodology is available in our open-source ML framework, GeoThermalCloud (GTC). Using this GTC framework, we dis... [more]

As the global energy crisis and environmental pollution become increasingly prominent, the development of new energy resources has become a global consensus [...]

This paper aims to establish a predictive model for battery lifetime using data analysis. The procedure of model establishment is illustrated in detail, including the data pre-processing, modeling, and prediction. The characteristics of lithium-ion batteries are introduced. In this study, data analysis is performed with MATLAB, and the open-source battery data are provided by NASA. The addressed models include the decision tree, nonlinear autoregression, recurrent neural network, and long short-term memory network. In the part of model training, the root-mean-square error, integral of the squared error, and integral of the absolute error are considered for the cost functions. Based on the defined health indicator, the remaining useful life of lithium-ion batteries can be predicted. The confidence interval can be used to describe the level of confidence for each prediction. According to the test results, the long short-term memory network provides the best performance among all addresse... [more]

This study measured the lifecycle carbon emissions of buildings in 30 Chinese provinces from 2005 to 2020 and decomposed the drivers of carbon emissions in the materialization stage and operation stage of building, respectively, using the Stochastic Impacts with the Regression on Population, Affluence, and Technology (STIRPAT) model in order to investigate the drivers of carbon emissions and their spatial influence effects in the building sector. The spatial Durbin model (SDM) was used to thoroughly investigate the spatial effects of carbon emissions and their drivers in the building sector under geographic and economic distances. According to the findings, China’s building sector has a high concentration of carbon emissions in the east and a low concentration in the west. There is also a sizable spatial autocorrelation, and the spatial spillover effects in the materialization and operation stages shift in opposite directions. To help the building sector to achieve the carbon peaking a... [more]

Photovoltaic (PV) power shows different fluctuation characteristics under different weather types as well as strong randomness and uncertainty in changeable weather such as sunny to cloudy, cloudy to rain, and so on, resulting in low forecasting accuracy. For the changeable type of weather, an ultra-short-term photovoltaic power forecasting method is proposed based on affinity propagation (AP) clustering, complete ensemble empirical mode decomposition with an adaptive noise algorithm (CEEMDAN), and bi-directional long and short-term memory network (BiLSTM). First, the PV power output curve of the standard clear-sky day was extracted monthly from the historical data, and the photovoltaic power was normalized according to it. Second, the changeable days were extracted from various weather types based on the AP clustering algorithm and the Euclidean distance by considering the mean and variance of the clear-sky power coefficient (CSPC). Third, the CEEMDAN algorithm was further used to dec... [more]

This paper takes advantage of the high control flexibility and fast response time of the interfacing power electronic converter for doubly fed wind turbine grid-connected systems to address inter-area oscillations caused by inadequate system damping in power systems. A reactive-power-coordinated damping controller for a doubly fed induction generator (DFIG) is proposed, and it makes use of second-order sliding-mode technology. The suggested controller improves damping performance by controlling the reactive power. It provides benefits such as a quicker damping rate and resilience to modeling errors and parameter changes. The simulation results indicate the system’s improved performance in inter-area oscillation damping and the robustness of the suggested control technique over a broad range of functional areas.

Aiming at the problems of power flow fluctuation and voltage exceeding standard caused by high permeability distributed power supply access, this paper proposes a load state perception early warning method for distribution networks. Firstly, the random behavior characteristics and voltage early warning mechanisms of power supply and load in distribution networks are analyzed, the dynamic model of distribution networks based on complex network theory is established, and the risk index of voltage exceeding limits under the conditions of high permeability distributed power supply access is put forward. Secondly, the random power flow of distribution networks based on the Monte Carlo method is studied by sampling and analyzing the dynamic model of distribution networks. Then, the risk calculation and safety assessment of voltage exceeding limits are carried out on the currently extracted model, and the risk control strategy of distribution network operation is put forward. Finally, an impr... [more]

European Union (EU) countries pay meticulous attention to environmental issues and achieve carbon-free development. In this direction, reducing greenhouse gas emissions and extending renewable energy are the primary goals. At the same time, the energy price and declining energy efficiency increase countries’ environmental expenditures and hinder their capabilities for economic growth. Against this backdrop, this research aims to examine the influence of environmental regulations, renewable energy, and energy efficiency on green economic growth. The originality of the study is twofold: first, it evaluates the green economic growth of a country, which simultaneously reveals the options for economic growth and the capability to eliminate its negative effect on the environment by applying the Global Malmquist−Luenberger productivity index; second, it develops an econometric model based on panel data for EU countries for 2000−2020 to investigate the nonlinear impact of environmental regulat... [more]

In mobile devices such as aircraft and electric vehicles, due to limited space, there are strict requirements on the volume and weight of the compressor mounted on the vehicle. Therefore, high-speed scroll compressors have attracted more and more attention because of their small size and light weight. In this paper, the numerical calculations and analysis of the three-dimensional (3D) transient flows in a high-speed scroll refrigeration compressor were established and validated. Circumferential gas intake was used in the simulation. According to the actual compressor size, the mesh generation accurately considers clearances. The radial and the axial clearances were both set as 0.01 mm. A dynamic and high-quality hexahedral structured mesh was generated for the working chamber, and the problem of insufficient grid density in radial clearance was solved. When the rotational speed was set as 3000 rpm, 6000 rpm, and 9000 rpm alternatively, the difference in the volume efficiency of the sim... [more]

Liquid-cooled servers can be deployed to reduce the energy consumption and environmental footprint of hybrid-cooled data centers. A computational fluid dynamics (CFD) model can bring extremely useful insights and results for thermal simulations of air- and liquid-cooled servers in a single environment. In this study, a conjugate heat transfer (CHT) numerical model is developed and validated with experimental data to simulate heat transfer from the CPU to the air and cold plate considering the effect of thermal paste. The cooling performance of an in-house developed cold plate design is thoroughly investigated via the validated CHT model. A dataset containing one hundred samples of various flow, thermal and workload conditions was generated using the Latin hypercube sampling (LHS) method, which was further utilized in the series of CHT simulations. Finally, a novel empirical equation is proposed for the prediction of heat transfer from the CPU to the air. The accuracy of the proposed eq... [more]

Carbon dioxide (CO2) and hydrogen (H2) are essential energy vectors in the green energy transition. H2 is a fuel produced by electrolysis and is applied in heavy transportation where electrification is not feasible yet. The pollutant substance CO2 is starting to be captured and stored in different European locations. In Denmark, the energy vision aims to use this CO2 to be reacted with H2, producing green methanol. Typically, the production units are not co-located with consumers and thus, the required transportation infrastructure is essential for meeting supply and demand. This work presents a novel scheme to allocate the transportation costs of CO2 and H2 in pipeline networks, which can be applied to any network topology and with any allocation method. During the tariff formation process, coordinated adjustments are made by the novel scheme on the original tariffs produced by the allocation method employed, considering the location of each customer connected to pipeline network. Loc... [more]

Worldwide, the demand for power load forecasting is increasing. A multi-step power-load forecasting model is established based on Informer, which takes the historical load data as the input to realize the prediction of the power load in the future. The constructed model abandons the common recurrent neural network to deal with time-series problems, and uses the seq2seq structure with sparse self-attention mechanism as the main body, supplemented by specific input and output modules to deal with the long-range relationship in the time series, and makes effective use of the parallel advantages of the self-attention mechanism, so as to improve the prediction accuracy and prediction efficiency. The model is trained, verified and tested by using the power-load dataset of the Taoyuan substation in Nanchang. Compared with RNN, LSTM and LSTM with the attention mechanism and other common models based on a cyclic neural network, the results show that the prediction accuracy and efficiency of the... [more]

Developing renewable energy has become a major strategy for China to accelerate the energy transition and combat climate change. Accordingly, a guarantee mechanism for renewable energy consumption with renewable portfolio standards (RPS) has been set in China. However, currently, the top-down allocation of regional renewable energy consumption targets often has issues of unfairness and inefficiency. It is necessary to investigate the issue of how to stimulate the renewable energy consumption potential on the demand side and reasonably formulate the consumption responsibility weights of various market entities. This paper aimed to develop a new methodology for the weight allocation of renewable energy consumption responsibilities. In doing so, an integrated model of an evolutionary game and stochastic optimization was constructed between market entities and governments. Then, the equilibrium strategies of market entities and governments were obtained through the evolutionary game. Furth... [more]

The scarce availability of non-renewable sources and the staggering amount of pollution have inevitably provoked many countries to opt for renewable sources. Thence, invariably, more renewable energy-based applications are hoarded by market stakeholders. Compared to all spheres of renewable energy applications, a considerable part of the energy is pulled into transportation. Wireless power transfer techniques play a significant role in charging infrastructure, considering the current development and advancement in the automotive industry. It will promise to overcome the widely known drawbacks of wired charging in electric vehicles. The effectiveness of wireless charging depends on coil design, compensation techniques, and the airgap between the coils. However, coil misalignment, improper compensation topologies, and magnetic materials reduce the efficacy. We can improve efficacy by overcoming the problems mentioned above and optimizing charging distance, time, and battery size. This pa... [more]

Renewable energy sources are nowadays a viable choice to satisfy the rising energy consumption and promote the advancement of sustainable development. These systems are integrated into microgrids using a variety of technological solutions to ensure customer communication and distributed generation facilities in an optimal way. Energy management in microgrids refers to the information and control system that provides the necessary functionality to guarantee that the generating and distribution systems produce energy at the lowest expenses. This study analyzes the various optimization objectives, constraints, problem-solving techniques, and simulation tools used for connected and freestanding microgrids. It reviews the literature on energy control in microgrids powered by sustainable energy. Energy storage technology is also viewed as an intriguing alternative to managing the intermittent nature of renewable energy because of its advanced techniques, increased energy efficiency, and capa... [more]

This article presents the results of a techno-economic analysis of repowering a coal-fired power plant’s steam turbine system to instead accept heat produced by a pressurized water reactor-type small modular nuclear system (PWR SMR). This type of repowering presents a challenge due to the significantly lower steam pressure and temperature produced by the nuclear system. A 460 MW supercritical power unit with steam parameters of 28 MPa/560 °C/580 °C, operated in the Łagisza Power Plant in Poland, was selected for the analysis. After repowering, the turbine system would be fed with saturated steam from the steam generators of the SMRs at a pressure of 7 MPa and a temperature of 285 °C. In total, four options for repowering were analyzed. In all cases, the existing high-pressure section of the turbine was disconnected, and the existing low-pressure stages of the turbine, as well as all auxiliary and outward components (feedwater heaters, pumps, generator, condenser, condenser cooling, etc... [more]

Nowadays, there are many technological-intensive applications that claim to be “smart”. From smartphones to the smart grid, people relate the word smart with technical novelty, automation, enabled communication, and service integration. There is indeed a gap between those smart technologies and their intended “intelligence”; this has arisen an indirect debate between works focusing on automation and mechatronics design and others pursuing a conceptual approach based on fulfilling determinate objectives. One last approach relates the said smartness to deep learning methodologies. In this work, it is attempted to explore both perspectives by providing an overview of recent works around energy usage toward smart cities and the smart grid, pointing out the main conceptual pillars upon which both approaches stand. Certainly, there are enabling technologies supporting the smart concept overall; thus, this work addresses them to characterize “smart” not from technological or conceptual one-si... [more]