With the deployment of the TetraSpar demonstrator, a significant cost-reduction is realized in the field of offshore floating wind turbines. The TetraSpar floating wind turbine foundation brings a milestone that emphasizes on a modular and fully industrialized foundation that consists of main components already widely available in the current wind energy supply chain. In an effort to provide an open approach to the development of the concept, this paper aims at giving a description of the design in order to enable an educated discussion of different design philosophies and their influence on material usage and production times. The description of the different subcomponents of the system should allow any entity to build a model for comparison and/or benchmarking any of their own findings against this concept. It is the authors’ expectation that this open approach to technological discussion is paramount to obtaining continued cost-reduction in the area of floating offshore wind—for thi... [more]

The uncertainty of generation and load increases in the transmission network in the power market. Considering the transmission congestion risk caused by various uncertainties of the transmission network, the optimal operation strategies of the transmission network under various operational scenarios are decided, aiming for the maximum of social benefit for the evaluation of the degree of scenario congestion. Then, a screening method for major congestion scenario is proposed based on the shadow price theory. With the goal of maximizing the difference between the social benefits and the investment and maintenance costs of transmission lines under major congestion scenarios, a multi-stage transmission network planning model based on major congestion scenarios is proposed to determine the configuration of transmission lines in each planning stage. In this paper, the multi-stage transmission network planning is a mixed integer linear programming problem. The DC power flow model and the comm... [more]

The need for the statistical stability of data is increasing nowadays as the data resource has become a more and more important production factor. In this study, a set of general identification and correction models are established for data outlier modification. The research object we chose is the data of per capita energy consumption. Based on the joint diagnosis method of outliers and the regional convergence theory, the abrupt outliers are identified and corrected. The study finds that there is an outlier in the data of the Ningxia Hui Autonomous Region. According to the club grouping method, 30 provinces in China are divided into two clubs and the Ningxia Hui Autonomous Region is determined to be in the first club. We calculate the convergence rate and obtain the correction results combining the half-life cycle model.

Many developing countries suffer from high energy-import dependency and inadequate electrification of rural areas, which aggravates the poverty problem. In this work, Al-Tafilah in Jordan was considered as a case study, where the technical, economic, and environmental benefits of a decentralized hybrid renewable energy system that can match 100% of the city demand were investigated. A tri-hybrid system of wind, solar, and hydropower was integrated with an energy storage system and optimized to maximize the match between the energy demand and production profiles. The optimization aimed at maximizing the renewable energy system (RES) fraction while keeping the levelized cost of electricity (LCOE) equal to the electricity purchase tariff. The techno-economic analysis showed that the optimal system in Al-Tafilah comprises a 28 MW wind system, 75.4 MW PV, and 1 MW hydropower, with a 259 MWh energy storage system, for which a RES fraction of 99% can be achieved, and 47,160 MtCO2 are avoided... [more]

The smart grid is vulnerable to network attacks, thus requiring a high detection rate and fast detection speed for intrusion detection systems. With a fast training speed and a strong model generalization ability, the extreme learning machine (ELM) perfectly meets the needs of intrusion detection of the smart grid. In this paper, the ELM is applied to the field of smart grid intrusion detection. Aiming at the problem that the randomness of input weights and hidden layer bias in the ELM cannot guarantee the optimal performance of the ELM intrusion detection model, a genetic algorithm (GA)-ELM algorithm based on a genetic algorithm (GA) is proposed. GA is used to optimize the input weight and hidden layer bias of the ELM. Firstly, the input weight and hidden layer bias of the ELM are mapped to the chromosome vector of a GA, and the test error of the ELM model is set as the fitness function of the GA. Then, the parameters of the ELM intrusion detection model are optimized by genetic opera... [more]

Implemented in road transport enterprises (RTEs) on a large scale, telematics systems are dedicated both to the particular aspects of their operation and to the integrated fields of the total operational functioning of such entities. Hence, a research problem can be defined as the identification of their efficiency levels in the context of operational activities undertaken by RTEs (including more holistic effects, e.g., lowering fuel/energy consumption and negative environmental impacts). Current research studies refer to the efficiency of some particular modules, but there have not been any publications focused on describing the efficiency of telematics systems in a more integrated (holistic) way, due to the lack of a universal tool that could be applied to provide this type of measurement. In this paper, an attempt at filling the identified cognitive gap is presented through empirical research analysing the original matrix developed by the authors that refers to the efficiency rates... [more]

This study involved conducting an experimental and numerical investigation on the effects of the air-to-fuel ratio (AFR), engine speed, and engine load on the inlet gas component of a three-way catalyst (TWC) and on the effects of noble metal loading, noble metal ratio, and carrier pore density on the emission conversion efficiency. The results showed that AFR can significantly affect the raw emissions of NOx and total hydrocarbon (THC), and better emission conversion efficiency of a TWC can be reached when AFR is controlled between 0.995 to 1. Compared with engine speed, engine load has a relatively small effect on exhaust temperature but greatly affects the flow velocity and NOx and THC emissions. Increasing the content of Pt in the catalyst can improve the THC conversion efficiency. For low Pt and Pd-Rh catalysts, the THC conversion effect is significantly deteriorated. The content of Rh affects the NOx conversion, and NOx conversion efficiency at high speeds is significantly reduce... [more]

During recent decades, the equilibrium manifold expansion (EME) model has been considered as a powerful identification tool for complex industrial systems with the aim of system control and simulation. Based on a two-step “dynamic and static” identification method, an approximate nonlinear state-space model is built by using multiple polynomials. However, the existing identification method is only suitable for single-input (SI) systems, but not for multi-input (MI) systems, where EME models cannot guarantee global calculation stability. For solving such a problem, this paper proposes a corrected equilibrium manifold expansion (CEME) model based on gas turbine prior knowledge. The equilibrium manifold is extended in dimension by introducing similarity equations instead of the high dimensional polynomial fitting. The dynamic similarity criterion of similarity theory guarantees the global stability of the CEME model. Finally, the comparative test between the CEME model and the existing MI... [more]

Forests cover two-thirds of Japan’s land area, and woody biomass is attracting attention as one of the most promising renewable energy sources in the country. The Feed-in Tariff (FIT) Act came into effect in 2012, and since then, woody biomass power generation has spread rapidly. Gasification power generation, which can generate electricity on a relatively small scale, has attracted a lot of attention. However, the technical issues of this technology remain poorly defined. This paper aims to clarify the problems of woody biomass gasification power generation in Japan, specifically on the challenges of improving energy utilization rate, the problem of controlling the moisture content, and the different performance of power generation facilities that uses different tree species. We also describe the technological development of a 2 MW updraft reactor for gasification and bio-oil coproduction to improve the energy utilization rate. The lower heating value of bio-oil, which was obtained in... [more]

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018−2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016−2017 to 2018−2019).The result shows that in only three mines the efficiency is continuously impr... [more]

The fault prognostics of the photovoltaic (PV) power generation system is expected to be a significant challenge as more and more PV systems with increasingly large capacities continue to come into existence. The PV inverter is the core component of the PV system, and it is essential to develop approaches that accurately predict the occurrence of inverter faults to ensure the PV system’s safety. This paper proposes a fault prognostics method which makes full use of the similarities between inverter clusters. First, a feature space was constructed using the t-distributed stochastic neighbor embedding (t-SNE) algorithm. Then, the fast clustering algorithm was used to search the center inverter of each sampling time from the feature space. The status of the center inverter was adopted to establish the health baseline. Finally, the Gaussian mixture model was established with two data clusters based on the central inverter and the inverter to be predicted. The divergence of the two clusters... [more]

Ultra-short-term load demand forecasting is significant to the rapid response and real-time dispatching of the power demand side. Considering too many random factors that affect the load, this paper combines convolution, long short-term memory (LSTM), and gated recurrent unit (GRU) algorithms to propose an ultra-short-term load forecasting model based on deep learning. Firstly, more than 100,000 pieces of historical load and meteorological data from Beijing in the three years from 2016 to 2018 were collected, and the meteorological data were divided into 18 types considering the actual meteorological characteristics of Beijing. Secondly, after the standardized processing of the time-series samples, the convolution filter was used to extract the features of the high-order samples to reduce the number of training parameters. On this basis, the LSTM layer and GRU layer were used for modeling based on time series. A dropout layer was introduced after each layer to reduce the risk of overfi... [more]

The overall cost of a hydropower plant is mainly due to the expenses of civil works, mechanical equipment (turbine and control units) and electrical components. The goal of a new draft tube design is to obtain a geometry that reduces investment costs, especially the excavation ones, but the primary driver is to increase overall machine efficiency, allowing for a reduced payback time. In the present study, an optimization study of the elbow-draft tube assembly of a Kaplan turbine was conducted. First, a CFD model for the complete turbine was developed and validated. Next, an optimization of the draft tube alone was performed using a design of experiments technique. Finally, several optimum solutions for the draft tube were obtained using a response surface technique aiming at maximizing pressure recovery and minimizing flow losses. A selection of optimized geometries was subsequently post-checked using the validated model of the entire turbine, and a detailed flow analysis on the obtain... [more]

The South African coalmining industry has a rich and long history and contributes significantly to the economic wellbeing of the country. Despite its importance in developing the economy, the industry is causing severe environmental challenges. For example, Emalahleni, a city situated in the Mpumalanga Province in South Africa, has been exposed for over a century to the continuous mining of coal. Challenges experienced include the sterilisation of land due to underground fires, water pollution, surface collapse, and acidification of topsoil. Previous work by the researchers formulated a conceptual framework aimed at addressing some of these challenges. In an extension of this work, the authors comprehensively enhance the preliminary framework on the strength of a set of qualitative propositions coupled with a parallel, exploratory survey. Interviews among various stakeholders were conducted, aimed at enhancing the components of the framework, followed by a focus group to validate the a... [more]

In light of the difficulty of the inspection and maintenance of a transmission line condition monitoring system in remote mountainous areas, this paper proposes a long-term online monitoring scheme based on a low power wide area network (LPWAN). Considering different failure rates, three monitoring periods of transmission lines in mountainous areas are proposed. An online monitoring framework of transmission lines in mountainous areas was designed based on long range radio (LoRa) and a cellular mobile network, and a dynamic group network model of LoRa was established. The multi-objective particle swarm optimization algorithm can be used to optimize the energy and delay of the system, and then the suitable working mode for the three monitoring periods can be obtained. The simulation results showed that the minimum packet loss rate of the system could be less than 1%, the energy consumption of the system was 80% lower than the existing monitoring system, and the service life of the syste... [more]

In this study, a multifunctional air and water source heat pump system was developed with a parallel refrigerant piping arrangement, which possessed six operational functions: space cooling (SC), space heating (SH), water heating (WH), water cooling (WC) and two composite operational modes. The two composite operational modes were the SC/WH mode and the SH/WH mode. The performance of the multifuctional heat pump system under different ambient conditions was investigated based on the testing standards of CNS 14464 and CNS 15466. In this study, the effect of the direct water heating (DWH) and circulating water heating (CWH) methods on the performance was investigated. It was found that the water heating performance of the system by the DWH method is better than that of the system by the CWH method. The water heating capacity and COPw,h of the DWH method can be improvement by 2.6% to 22.1% and 2.9% to 50.8%, respectively. Moreover, this study developed a refrigerant pressure balance metho... [more]

This study examined the feasibility of using non-sterilized swine wastewater for lipid production by an isolated microalga, Scenedesmus rubescens. Different dilution ratios using municipal wastewater as a diluent were tested to determine the suitable levels of microalgal growth in the wastewaters, its nutrient removal, and its lipid production. The highest lipid productivity (8.37 mg/L/d) and NH4+ removal (76.49%) were achieved in swine wastewater that had been diluted to 30 times using municipal wastewater. Various bacteria coexisted in the wastewaters during the cultivation of S. rubescens. These results suggest the practical feasibility of a system to produce lipids from swine wastewater by using microalgae.

According to the 2020 Climate Change Performance Index, Australia was ranked as the worst-performing country on climate change policy. The country has an ambivalent record of climate policy development as well as implementation, and has been criticized for its inaction. This paper considers why the country has been locked in climate policy “paralysis” through analyzing defining attributes of such a paralysis, and the tentative connections between domestic energy policies and international trade and development. We conducted a media content analysis of 222 articles and identified media narratives in three cases of energy projects in the country involving thermal coal exports, domestic renewable energy storage, and closure of a domestic coal power station. The analysis reveals that policy paralysis in Australian climate change policy can be traced back to the countervailing arguments that have been pervasive around domestic energy security, rural employment and international energy pover... [more]

As the penetration of electric vehicles (EVs) accelerates according to eco-friendly policies, the impact of electric vehicle charging demand on a power distribution network is becoming significant for reliable power system operation. In this regard, accurate power demand or load forecasting is of great help not only for unit commitment problem considering demand response but also for long-term power system operation and planning. In this paper, we present a forecasting model of EV charging station load based on long short-term memory (LSTM). Besides, to improve the forecasting accuracy, we devise an imputation method for handling missing values in EV charging data. For the verification of the forecasting model and our imputation approach, performance comparison with several imputation techniques is conducted. The experimental results show that our imputation approach achieves significant improvements in forecasting accuracy on data with a high missing rate. In particular, compared to a... [more]

Various types of natural hazards are inextricably linked to the process of underground hard coal mining. Ventilation hazards—methane and spontaneous combustion of coal—are the most dangerous; they pose a major threat to the safety of the workers and decrease the effectiveness of the whole coal production process. One of the methods designed to limit the consequences of such hazards is based on the selection of a ventilation system that will be suitable for the given mining area. The article presents a case study of an active longwall area, where—due to increasing ventilation hazard (methane and spontaneous combusting of coal)—the whole system was rebuilt. The U-type ventilation system was used in the initial stage of the extraction process, however, it often generated methane in amounts that exceeded the allowable values. Consequently, such conditions forced the change of the ventilation system from a U−type to Y−type system. The new system was installed during the ongoing mining proce... [more]

Renewable Energy Communities consist in an emerging decentralized market mechanism which allows local energy exchanges between end-users, bypassing the traditional wholesale/retail market structure. In that configuration, local consumers and prosumers gather in communities and can either cooperate or compete towards a common objective, such as the minimization of the electricity costs and/or the minimization of greenhouse gas emissions for instance. This paper proposes data analytics modules which aim at helping the community members to schedule the usage of their resources (generation and consumption) in order to minimize their electricity bill. A day-ahead local wind power forecasting algorithm, which relies on state-of-the-art Machine Learning techniques currently used in worldwide forecasting contests, is in that way proposed. We develop furthermore an original method to improve the performance of neural network forecasting models in presence of abnormal wind power data. A techniqu... [more]

This paper proposes a method of determining the optimal tap settings for no-load distribution transformers with tap-changing capabilities that is practical to apply in real distribution networks. The risk of low voltage distribution networks violating voltage constraints is impacted by the increasing uptake of distributed energy resources and embedded generation. Some of this risk can be alleviated by suitably setting no-load transformer tap settings, however, modifying these taps requires customer outages and must be infrequent. Hence, loading over the entire year must be considered to account for seasonal variations when setting these taps optimally. These settings are determined using evolution strategy optimisation based on an average loading case. Monte Carlo simulations are used to calculate the probability that the terminal voltages on the distribution transformer secondary terminals violate the network voltage limits when the optimal set of taps for the average case is applied... [more]

The absence of an effective texturing technique for diamond-wire sawn multi-crystalline silicon (DWS mc-Si) solar cells has hindered commercial upgrading from traditional multi-wire slurry sawn silicon (MWSS mc-Si) solar cells. In this work, we present a novel method for the removal of diamond-wire-sawn marks in a multi-crystalline silicon wafer based on metal assisted chemical etching process with Cu/Ag dual elements and nano-structure rebuilding (NSR) treatment to make a uniform inverted pyramid textured structure. The temperature effect of NSR solution was systematically analyzed. It was found that the size of the inverted pyramid structure and the reflectance became larger with the increase of the NSR treatment temperature. Furthermore, the prepared unique inverted pyramid structure not only benefited light trapping, but also effectively removed the saw-marks of the wafer at the same time. The highest efficiency of 19.77% was obtained in solar cells with an inverted pyramid structu... [more]

Transmission system operator (TSOs) need to project the system state at the seasonal scale to evaluate the risk of supply-demand imbalance for the season to come. Seasonal planning of the electricity system is currently mainly adressed using climatological approach to handle variability of consumption and production. Our study addresses the need for quantitative measures of the risk of supply-demand imbalance, exploring the use of sub-seasonal to seasonal forecasts which have hitherto not been exploited for this purpose. In this study, the risk of supply-demand imbalance is defined using exclusively the wind energy production and the consumption peak at 7 pm. To forecast the risks of supply-demand imbalance at monthly to seasonal time horizons, a statistical model is developed to reconstruct the joint probability of consumption and production. It is based on a the conditional probability of production and consumption with respect to indexes obtained from a linear regression of principa... [more]

The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reduction.