Bladeless fans are more energy efficient, safer due to the hidden blades, easier to clean, and more adjustable than conventional fans. This paper investigates the influence of the airfoil’s outlet slit thickness on the discharge ratio by varying the outlet slit thickness of an Eppler 473 airfoil from 1.2 mm to 2 mm in intervals of 0.2 mm by using a k-omega SST turbulence model with an all y+ wall treatment used to numerically simulate in CFD. The computational results indicated that smaller slits showed higher discharge ratios. The airfoil with a 1.2 mm slit thickness showed a discharge ratio of 18.78, a 24% increase from the discharge ratio of the 2 mm slit. The effect of outlet angle on the pressure drop across the airfoil was also studied. Outlet angles were varied from 16° to 26° by an interval of 2°. The airfoil profile with a 24° outlet angle showed a maximum pressure difference of 965 Pa between the slit and leading edge. In contrast, the 16° outlet angle showed the least pressu... [more]

The global energy system is undergoing an undeniable change [...]

This paper describes the detailed modelling of a vibration-based miniature piezoelectric device (PD) and the analysis modes of operation and control of a voltage doubler boost converter (VDBC) circuit to find the PD’s optimal operating conditions. The proposed VDBC circuit integrates a conventional voltage doubler (VD) circuit with a step-up DC-DC converter circuit in modes 1−4, while a non-linear synchronisation procedure of a conventional boost converter circuit is employed in modes 5−6. This integration acted as the voltage boost circuit without utilising duty cycles and complex auxiliary switching components. In addition, the circuit does not require external trigger signals to turn on the bidirectional switches. This facilitates the operation of VDBC circuit at very low AC voltage (Vac ≥ 0.5 V). Besides this, the electrical characteristics of VDBC circuit’s input (i.e., PD) perfectly concurs with the studied testing scenarios using impedance power sources (mechanical shaker). Firs... [more]

When a permanent magnet synchronous motor (PMSM) is designed according to the traditional motor design theory, the performance of the motor is often challenging to achieve the desired goal, and further optimization of the motor design parameters is usually required. However, the motor is a strongly coupled, non-linear, multivariate complex system, and it is a challenge to optimize the motor by traditional optimization methods. It needs to rely on reliable surrogate models and optimization algorithms to improve the performance of the PMSM, which is one of the problematic aspects of motor optimization. Therefore, this paper proposes a strategy based on a combination of a high-precision combined surrogate model and the optimization method to optimize the stator and rotor structures of interior PMSM (IPMSM). First, the variables were classified into two layers with high and low sensitivity based on the comprehensive parameter sensitivity analysis. Then, Latin hypercube sampling (LHS) is us... [more]

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China’s power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China’s power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market p... [more]

This paper presents a practical usability investigation of recurrent neural networks (RNNs) to determine the best-suited machine learning method for estimating electric vehicle (EV) batteries’ state of charge. Using models from multiple published sources and cross-validation testing with several driving scenarios to determine the state of charge of lithium-ion batteries, we assessed their accuracy and drawbacks. Five models were selected from various published state-of-charge estimation models, based on cell types with GRU or LSTM, and optimisers such as stochastic gradient descent, Adam, Nadam, AdaMax, and Robust Adam, with extensions via momentum calculus or an attention layer. Each method was examined by applying training techniques such as a learning rate scheduler or rollback recovery to speed up the fitting, highlighting the implementation specifics. All this was carried out using the TensorFlow framework, and the implementation was performed as closely to the published sources a... [more]

Efficient simulation of the helical coiled once-through steam generator (H-OTSG) is crucial in the design and safety analysis of the high-temperature gas-cooled reactor (HTGR). The physical property and phase transformation of water in the steam generator brings great challenges during simulation. The water properties calculation routine occupies a large part of the computational time in the steam generator solution process. Thus, a thermohydraulic property library is developed based on the IAPWS-IF97 formulation in this work to reduce the computational cost. Here the formulation adopts the backward equation method to avoid iterations in thermodynamic property calculation. Moreover, two Newton-method-based simultaneous solutions are implemented as implicitly nonlinear solvers, including Jacobian-Free Newton−Krylov (JFNK) and Newton−Krylov (NK) methods, due to its excellent computational performance. These simultaneous solution algorithms are combined with the developed water property l... [more]

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak peri... [more]

Energy is one of the most important aspects of urban development and technological advancements. As its production and consumption are connected to several environmental, social, and economic issues covering all three sustainability pillars, strategic and targeted energy planning is vital to the smooth transition towards a more efficient and greener society. In accordance with the specific priorities of every state, sustainable energy planning should also satisfy the international trends, requirements, and targets, including the global commitments for sustainable development. As of this time, energy transition with further deployment of renewable energy and energy efficiency improvement are the priorities for a sustainable future. However, due to recent global events, a new situation has been established. The COVID-19 pandemic and the ongoing war in Ukraine have caused new circumstances challenging the recognized approaches for an effective sustainable energy strategy. While the global... [more]

The European carbon emission trading market is the largest and most mature market, while China’s carbon market has a short history. Institutionally, cross-market transaction is infeasible between the two markets. This paper investigates the long-run trend between the two markets as well as the price dynamics. Results show that a long-run trend exists between the Chinese and European carbon markets. Both markets possess self-correction capability in reducing price deviations, signaling a certain level of market efficiency. However, both markets also exhibit pricing inefficiency as historical price movements are able to impact prices. The European market informationally leads the Chinese market. Policy implications are that China should further upgrade its information disclosure system, such as unifying information disclosure standards across industries, and further develop its carbon derivatives markets to improve market transparency and market competition.

Proton exchange membrane fuel cell (PEMFC) is generally regarded as a promising energy conversion device due to its low noise, high efficiency, low pollution, and quick startup. The design of the catalyst layer structure is crucial in boosting cell performance. The traditional catalyst layer has high oxygen transmission resistance, low utilization rate of Pt particles and high production cost. In this study, we offer a sub-model for an order-structured cathode catalyst layer coupled to a three-dimensional (3D) two-phase macroscopic PEMFC model. In the sub-model of the cathode catalyst layer, it is assumed that carbon nanowires are vertically arranged into the catalyst layer structure, platinum particles and ionomers adhere to the surface, and water films cover the cylindrical electrode. The impacts of triple-phase contents in the catalyst layer on cell performance are investigated and discussed in detail after the model has been validated using data from existing studies. The results s... [more]

To combat climate change, the Chinese government has implemented a package of policies to support the development of the biogas power generation industry. However, the promotion of biogas power generation technology in China is relatively slow. Therefore, it is of practical significance to study the promotion of biogas power generation technology against the background of policy support. In order to study the effect of policy on the promotion of biogas power generation technology, a system dynamics model is constructed in this paper. The results show that under the feed-in tariff subsidy policy, biogas power generation technology can be well promoted because it has good economic and environmental effects. In addition, if the biogas power generation technology is considered to participate in carbon emission trading, the carbon price also has a positive impact on the promotion of biogas power generation technology because it increases the perceived economic value of biogas power generati... [more]

It is important to understand the features of an integrated renewable energy power system, especially for deregulated systems. The greatest obstacle to assimilating renewable energy generators with the existing electrical system is their unpredictability. Because wind energy is inconsistent, incorporating it into an established power system necessitates more planning. The effects of wind farm (WF) incorporation with fuel cells and a unified power flow controller (UPFC) on electric losses, voltage profile, generating price, and the economics of the system in a deregulated power market are examined in this paper. An impact analysis of integrating wind farms into controlled and uncontrolled situations is conducted. At two randomly selected locations in India, the real-time statistics of the actual wind speed (AWS) and forecasted wind speed (FWS) were merged for this study. The surplus charge rate and deficit charge rate are intended to evaluate the imbalance cost which is arising from the... [more]

Geothermal heat flow is an essential parameter for the exploration of geothermal energy. The cost is often prohibitive if dense heat flow measurements are arranged in the study area. Regardless, an increase in the limited and sparse heat flow observation points is needed to study the regional geothermal setting. This research is significant in order to provide a new reliable map of terrestrial heat flow for the subsequent development of geothermal resources. The Gradient Boosted Regression Tree (GBRT) prediction model used in this paper is devoted to solving the problem of an insufficient number of heat flow observations in North China. It considers the geological and geophysical information in the region by training the sample data using 12 kinds of geological and geophysical features. Finally, a robust GBRT prediction model was obtained. The performance of the GBRT method was evaluated by comparing it with the kriging interpolation, the minimum curvature interpolation, and the 3D int... [more]

With the proposed goal of “Carbon Neutrality”, photovoltaic energy is gradually gaining the leading role in energy transformation. At present, crystalline silicon cells are still the mainstream technology in the photovoltaic industry, but due to the similarity of defect characteristics and the small scale of the defects, automatic defect detection of photovoltaic cells (PV) by electroluminescence (EL) imaging is a challenging task. In order to better meet the growing demand for high-quality photovoltaic cell products in intelligent manufacturing and use, and ensure the safe and efficient operation of photovoltaic power stations, this paper proposes an improved abnormal detection method based on Faster R-CNN for the surface defect EL imaging of photovoltaic cells, which integrates a lightweight channel and spatial convolution attention module. It can analyze the crack defects in complex scenes more efficiently. The clustering algorithm was used to obtain a more targeted anchor frame for... [more]

The issue of depleting fossil fuels has emphasized the use of renewable energy. Multigeneration systems fueled by renewables such as geothermal, biomass, solar, etc., have proven to be cutting-edge technologies for the production of different valuable by-products. This study proposes a multigeneration system using a geothermal source of energy. The main outputs include power, space heating, cooling, fresh and hot water, dry air, and hydrogen. The system includes a regenerative Rankine cycle, a double effect absorption cycle and a double flash desalination cycle. A significant amount of electrical power, hydrogen and fresh water is generated, which can be used for commercial or domestic purposes. The power output is 103 MW. The thermal efficiency is 24.42%, while energetic and exergetic efficiencies are 54.22% and 38.96%, respectively. The COPen is found to be 1.836, and the COPex is found to be 1.678. The hydrogen and fresh water are produced at a rate of 0.1266 kg/s and 37.6 kg/s, res... [more]

Trombe walls are a passive solar technology that can contribute to the reduction of building heating loads. However, during warmer weather conditions, Trombe walls may cause overheating. In this work, we investigate the feasibility of using Trombe walls to perform multiple functions during warm weather conditions including (1) heating and storing water for building applications, (2) providing occupants with visibility to the outdoors, and (3) generating electric power. Experiments are performed on a small-scale prototype comprising a clear water storage container with a transparent window and a tinted acrylic sheet that is immersed in the water. Photovoltaic cells are placed on the bottom half of the front face of the water storage container. Results show that water at the top of the clear container can be heated to temperatures as high as 45 °C when subjected to solar-simulated radiation for five hours. Numerical simulations predict that similar temperatures can be reached if the Trom... [more]

This paper studies the implementation strategy of an online tracking simulation system for the 660 MW ultra supercritical circulating fluidized bed boiler (USCFB). The establishment of the online system can be divided into offline and online phases. In the offline phase, the high-precision model and initial condition database of the boiler are first established. After the initial conditions are loaded, the initial conditions are adjusted through mass and energy compensation to make the initial state of the model consistent with the current operating state of the unit. In the online phase, this paper analyzes the global sensitivity of the 660 MW USCFB, establishes an online tracking mechanism based on the PI controller, and conducts simulation tests. The experiment shows that the tracking simulation system established in this paper can track the analog signal quickly and accurately.

In modern power systems, the installation of a shunt capacitor bank is one of the cheapest and most widely used methods for improving the voltage profile. One shunt capacitor bank is composed of mass capacitor units and have ground, ungrounded, delta, wye connections that make configuration of capacitor banks is various. In the case of long-term operation, the failure of a single capacitor unit of a capacitor bank is likely to cause uneven voltage, which will lead to the breakdown and burning of the whole group, resulting in huge losses. The relay protection device can detect the simultaneous voltage and current of the capacitor. By utilizing these data from the relay, the abnormal state of the shunt capacitor banks at the initial stage of the fault can be found through monitoring the slight change in capacitance. Timely and early maintenance and repair would avoid capacitor bank faults and potentially greater economic losses. Capacitor banks have different connection modes. For ungrou... [more]

In the last decade, global discussions on the role of the Russian Federation in the energy supply system have continued to be relevant. Taking into account this context, the purpose of the article is to study the impact of the Russian oil and petroleum products market on sustainable development in the conditions of the “energy transition” declared in the country and to substantiate the mechanism of transition to a diversified energy model during the period of global geo-economic turbulence. The authors propose a methodological approach for conducting a comparative assessment of the level and dynamics of the development of the industry in the country and regions, based on the use of a set of objective indicators and the concept of taking into account the level and quality of life of the population. Using panel data on the country, federal districts and vertically integrated companies of Russia from 2005 to 2020 for empirical research, we found the determining influence of external and i... [more]

The Split-pi converter can suitably interface an energy storage system (ESS) with a DC microgrid when galvanic isolation is not needed. Usually, the ESS voltage is lower than the grid-side voltage. However, limitations in terms of the ESS current make the use of a high-voltage ESS unavoidable when high power levels are required. In such cases, the ESS voltage can be higher than the microgrid voltage, especially with low microgrid voltages such as 48 V. Despite its bidirectionality and symmetry, the Split-pi exhibits a completely different dynamic behavior if its input and output ports are exchanged. Thus, the present work aims to model the Split-pi converter operating with an ESS voltage higher than the grid-side voltage in three typical microgrid scenarios where the controlled variable is the converter’s output voltage. The devised state-space model considers the parasitic elements and the correct load model for each scenario. Furthermore, it is shown that the presence of the input LC... [more]

The rising cost and demand for energy have prompted the need to devise innovative methods for energy monitoring, control, and conservation. In addition, statistics show that 20% of energy losses are due to the mismanagement of energy. Therefore, the utilization of energy management can make a substantial contribution to reducing the unnecessary usage of energy consumption. In line with that, the intelligent control and optimization of energy management systems integrated with renewable energy resources and energy storage systems are required to increase building energy efficiency while considering the reduction in the cost of energy bills, dependability of the grid, and mitigating carbon emissions. Even though a variety of optimization and control tactics are being utilized to reduce energy consumption in buildings nowadays, several issues remain unsolved. Therefore, this paper presents a critical review of energy management in commercial buildings and a comparative discussion to impro... [more]

Reducing our carbon footprint is one of the biggest challenges facing humanity in the current millennium. In the last few years, researchers have focused their attention on balancing the demand and supply, thereby allowing better management of renewable energy resources. In this regard, many energy management strategies have been developed. Nevertheless, testing, evaluating, and comparing such approaches in multiple scenarios, and above all, assessing their generalization, is currently a hard, or even impossible, task. Furthermore, analyzing the impact of such strategies in Energy Communitys (ECs) is an underexplored task. This is due to the lack of existing EC datasets and simulators that allow users to evaluate and compare their approaches. Although there are some tools to generate demand and production profiles, they are all developed with a single purpose. To address these challenges, PROCSIM is presented: an open-source simulator designed especially to create energy community data... [more]

Given the spatial heterogeneity of the social-economic situations across different regions in China, the decomposition of emission reduction targets should be designed according to the actual characteristics of the industrial economy. There is concern about the loss of industrial competitiveness and leakage of CO2 emissions if just seven pilot carbon markets operate independently, so the national carbon market of the power sector was established in 2021. In this study, a China two-region CGE model including Guangdong (GD) and the rest of China (ROC) is built on an analysis of the long-term effects of CO2 prices in industrial sectors at the target 2030 peak. Based on this model, we constructed one business-as-usual scenario and six comparison carbon tax scenarios to quantify the CO2 cost impact for a wide range of manufacturing sectors and identify specific economic activities that face relatively high CO2 costs between the two regions. Based on the China two-region CGE model, the risks... [more]

Intelligent energy management in renewable-based power distribution applications, such as microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important in the context of the transition toward the decentralization, digitalization, and decarbonization of energy networks. Arguably, many challenges can be overcome, and benefits leveraged, in this transition by the adoption of intelligent autonomous computer-based decision-making through the introduction of smart technologies, specifically artificial intelligence. Unlike other numerical or soft computing optimization methods, the control based on artificial intelligence allows the decentralized power units to collaborate in making the best decision of fulfilling the administrator’s needs, rather than only a primitive decentralization based only on the division of tasks. Among the smart approaches, reinforcement learning stands as the most relevant and successful, particularly in power distribution management a... [more]