Increasing interest in natural gas-fired gensets is motivated by District Heating (DH) network applications, especially in urban areas. Even if they represent customary solutions, when used in DH, duty regimes are driven by network thermal energy demands resulting in discontinuous operation, which affects their remaining useful life. As such, the attention on effective condition-based maintenance has gained momentum. In this paper, a novel unsupervised anomaly detection framework is proposed for gensets in DH networks based on Supervisory Control And Data Acquisition (SCADA) data. The framework relies on multivariate Machine-Learning (ML) regression models trained with a Leave-One-Out Cross-Validation method. Model residuals generated during the testing phase are then post-processed with a sliding threshold approach based on a rolling average. This methodology is tested against nine major failures that occurred on the gas genset installed in the Aosta DH plant in Italy. The results sho... [more]

Air contaminants can have detrimental effects on the performance and durability of proton exchange membrane (PEM) fuel cell vehicles. This research focuses on the experimental investigation of the effect of nitrogen monoxide (NO) in the cathode gas stream, which provokes a cell voltage decrease due to the partially reversible adsorption of NO on the platinum catalyst. The concentration and exposure time of NO in the cathode gas stream are varied at selected constant current densities and load ramps to assess the effects throughout the fuel cell system operating range. The results show the cell voltage loss in the presence of NO and reveal a near-catalyst saturation with increased injected NO mass. Additionally, several voltage recovery and mitigation strategies are introduced and discussed by presenting conclusions about the general effect of NO on a fuel cell system in operation. The most promising recovery strategy for fuel cell systems is identified, and the overall system degradati... [more]

With the wake effect between different wind turbines, a wind farm generally aims to achieve the maximum energy capture by implementing the optimal pitch angle and blade tip speed ratio under different wind speeds. During this process, the balance of fatigue load distribution is easily neglected because it is difficult to be considered, and, thus, a high maintenance cost results. Herein, a novel bi-objective optimal wind farm energy capture (OWFEC) is constructed via simultaneously taking the maximum power output and the balance of fatigue load distribution into account. To rapidly acquire the high-quality Pareto optimal solutions, the decomposition-based multi-classifier-assisted evolutionary algorithm is designed for the presented bi-objective OWFEC. In order to evaluate the effectiveness and performance of the proposed technique, the simulations are carried out with three different scales of wind farms, while five familiar Pareto-based meta-heuristic algorithms are introduced for per... [more]

This study discusses the influence of natural wind on the air flow of air-cooled condensers (ACCs) and then proposes a partition speed-regulation strategy for a fan group with enhanced generalized capability, which is of great practical significance for optimizing energy-saving operations. The stochastic time-varying features of natural wind are characterized by sine−Gaussian, Weibull, and composed winds. In a natural wind disturbance, using the Sugon Supercomputing Center, the transient numerical simulation of the dynamic evolution of the ACC flow field was found: the dynamic system of air flow is a typical time-varying nonlinear process. Cluster analysis was used to extract the nonlinear features of air flow, divide the fan group into four subregions with generalization capability, and implement a partitioned speed operation. It was found that giving priority to increasing the fan speed in the headwind partition can suppress the natural wind disturbance and improve the overall air fl... [more]

This article presents the results of an analysis of heat enhancement intensification using twisted tapes in linear absorbers for low-concentration parabolic trough collectors, a technology frequently considered as a supplementary energy source for industrial heat production. This contribution proposes a segmented application of different twisted tapes to intensify heat absorption. A 33.7 mm tubular absorber placed in the collector focal point with an aperture of 1.8 m was selected. The temperature range of the heat transfer fluid was chosen at 60−250 °C. The impact of inserts with twisted ratios of 1, 2 and 4 on system operation was analysed using the Ansys Fluent and mathematical model. The models used were validated based on experimental results from a parabolic trough collector with solar simulator test bench. The results indicated that for the range of mass flow between 0.15−0.3 kg/s, the most optimal is applying twisted ratio 1, except for the highest-temperature section. In this... [more]

This study proposes an optimal scheduling method for complex integrated energy systems. The proposed method employs a heuristic algorithm to maximize its energy, economy, and environment indices and optimize the system operation plan. It uses the k-means combined with box plots (Imk-means) to improve the convergence speed of the heuristic algorithm by forming its initial conditions. Thus, the optimization scheduling speed is enhanced. First of all, considering the system source and load factors, the Imk-means is presented to find the typical and extreme days in a historical optimization dataset. The output results for these typical and extreme days can represent common and abnormal optimization results, respectively. Thus, based on the representative historical data, a traditional heuristic algorithm with an initial solution set, such as the genetic algorithm, can be accelerated greatly. Secondly, the initial populations of the genetic algorithm are dispersed at the historical outputs... [more]

At present, the condition assessment of transformer winding based on frequency response analysis (FRA) measurements demands skilled personnel. Despite many research efforts in the last decade, there is still no definitive methodology for the interpretation and condition assessment of transformer winding based on FRA results, and this is a major challenge for the industrial application of the FRA method. To overcome this challenge, this paper proposes a transformer condition assessment (TCA) algorithm, which is based on numerical indices, and a supervised machine learning technique to develop a method for the automatic interpretation of FRA results. For this purpose, random forest (RF) classifiers were developed for the first time to identify the condition of transformer winding and classify different faults in the transformer windings. Mainly, six common states of the transformer were classified in this research, i.e., healthy transformer, healthy transformer with saturated core, mecha... [more]

Wind turbine farms require efficient operation and maintenance strategies to ensure long-term profitability and cost-effectiveness. However, temperatures and dust accumulation can significantly affect turbine performance and increase maintenance costs. This study investigates the impact of air filter clogging on wind turbine nacelle temperature and performance by collecting data from the Supervisory Control and Data Acquisition (SCADA) system of wind farms in southern Jordan, including temperature, wind speed, and power generation. The findings demonstrate that uncleaned air filters can lead to inefficient heat dissipation, higher nacelle temperatures, and reduced power production. Turbines with uncleaned filters experienced an average nacelle temperature increase of 15.44 °C compared to 13.30 °C for turbines with clean filters, resulting in a difference in the power production of 66.54 kW.

Rods and plates at the connections in composite insulating material towers are commonly fixed to each other by metal bolts, which may cause electrical field distortion at the connections. So, the rod−plate connections are prone to partial discharge under polluted and wet conditions, and the resulting electric field and temperature changes can affect the mechanical and electrical performance of the whole tower. In this paper, an artificial pollution test synchronous observation platform with an infrared and visible light imager, leakage current, and voltage measurement was built to observe the dry band formation and partial discharge at the simplified rod−plate connections in the composite towers. Then, the electric field simulation of the rod−plate connection specimen showed the current density distribution. When combining the test and the simulation, it was concluded that the cause of the partial discharge was the distortion of the current density and, thus, measures to suppress the p... [more]

Energy is primarily obtained from fossil fuels and with the use of fossil fuels, we are increasing the emissions and greenhouse gases. It takes constant effort to meet the energy need from environmentally acceptable and renewable fuels. In order to find a replacement for depleting fossil fuel energy, a range of oxygenated fuels was investigated based on their accessibility and geographic areas. This work assessed the transesterification process’s feasibility of turning used fry oil into biodiesel fuel and its physiochemical characteristics. The performances of a diesel engine operating on biodiesel and diesel fuel were assessed and compared. Four different types of fry oils were utilized for the research on a diesel agricultural engine with indirect injection. The first fry, second fry, third fry, and restaurant fry were the various sorts of fry oil. Five different types of biodiesels and their blends were investigated for their engine efficiency and emission metrics. B40 (biodiesel 40... [more]

Transitional shale gas, rich in resources, is expected to be a practical contributor to the increase in shale gas reserves and production in China. Its exploration prospect has been demonstrated by several wells in the Daning-Jixian block on the eastern margin of the Ordos Basin. In this paper, the Lower Permian Shanxi Formation (P1s) and Taiyuan Formation (P1t) in the eastern margin of Ordos Basin were compared for organic geochemical parameters, revealing that the overflow fan + lagoon combination (OLC) of the third sub-member of the second member of Shanxi Formation (P1s23) and the marine + lagoon combination (MLC) of the first member of Taiyuan Formation (P1t1) are the most favorable shale gas intervals. The two intervals were comparatively analyzed with respect to mineral composition, brittleness, caprocks, and preservation conditions. It is found that the OLC of P1s23 has a similar porosity to and much lower permeability than the MLC of P1t1 (or MLC1) and a BET surface area of 10... [more]

Considering environmental issues such as greenhouse gas emissions associated with climate change and the depletion of fossil fuels, one of the possible solutions is the use of renewable energy sources. Wind energy is one of the most competitive and resilient energy sources in the world, which can play an important role in accelerating the global transition to green energy. The purpose of this study is to evaluate the allocative efficiency of 47 offshore wind energy companies in 9 European countries using the input-oriented BCC DEA model. The basic hypothesis is that by evaluating the relative efficiency of offshore wind energy companies in European countries, it is possible to determine a correlation between the results of efficiency between the two observed periods with slight deviations. The empirical results show no significant correlation between the score of relative efficiency and the country where the offshore wind energy company is located. On the other hand, the results are co... [more]

As the traditional generation is gradually replaced by inverter-based resources, a lack of rotational inertia is now a common issue of modern power systems, which leads to an increasingly larger rate of change of frequency (RoCoF) following contingencies and may result in frequency collapse. As a crucial index of the frequency security and stability of power systems, the accurate estimation of the RoCoF can be a foundation for the development of advanced operations and control techniques of the future power system. This paper firstly analyzes the role of the RoCoF in typical blackouts occurring in recent years and discusses the physical and numerical nature of the RoCoF; then, by introducing the frequency spatial distribution of the power system, the paper discusses the concept of the “center” RoCoF that can present the frequency security and stability of the entire system. The estimation and prediction techniques of the maximal power system RoCoF following a contingency and the existi... [more]

To improve the viability of nuclear power plants, there is a need to reduce their operational costs. Operational costs account for a significant portion of a plant’s yearly budget, due to their scheduled-based maintenance approach. In order to reduce these costs, proactive methods are required that estimate and forecast the state of a machine in real time to optimize maintenance schedules. In this research, we use Bayesian networks to develop a framework that can forecast the remaining useful life of a centrifugal pump. To do so, we integrate survival analysis with Bayesian statistics to forecast the health of the pump conditional to its current state. We complete our research by successfully using the Bayesian network on a case study. This solution provides an informed probabilistic viewpoint of the pumping system for the purpose of predictive maintenance.

The degradation of solar photovoltaic (PV) modules is caused by a number of factors that have an impact on their effectiveness, performance, and lifetime. One of the reasons contributing to the decline in solar PV performance is the aging issue. This study comprehensively examines the effects and difficulties associated with aging and degradation in solar PV applications. In light of this, this article examines and analyzes many aging factors, including temperature, humidity, dust, discoloration, cracks, and delamination. Additionally, the effects of aging factors on solar PV performance, including the lifetime, efficiency, material degradation, overheating, and mismatching, are critically investigated. Furthermore, the main drawbacks, issues, and challenges associated with solar PV aging are addressed to identify any unfulfilled research needs. Finally, this paper provides new directions for future research, best practices, and recommendations to overcome aging issues and achieve the... [more]

As the climate crisis worsens, power grids are gradually transforming into a more sustainable state through renewable energy sources (RESs), energy storage systems (ESSs), and smart loads. Virtual power plants (VPP) are an emerging concept that can flexibly integrate distributed energy resources (DERs), managing manage the power output of each DER unit, as well as the power consumption of loads, to balance electricity supply and demand in real time. VPPs can participate in energy markets, enable self-scheduling of RESs, facilitate energy trading and sharing, and provide demand-side frequency control ancillary services (D-FCAS) to enhance the stability of the system frequency. As a result, studies considering VPPs have become the focus of recent energy research, with the purpose of reducing the uncertainty resulting from RESs distributed in the power grid and improving technology related to energy management system (EMS). However, comprehensive reviews of VPPs considering their formatio... [more]

The European electricity market model continues to evolve in the face of new challenges. This systematic literature review aims to assess the status of research and discussion on the current model and its market mechanisms. In addition, it aims to ascertain the kinds of modelling tools that have been used to model market mechanisms or formulate proposals for changes to current practice. The results show that the challenges of individual market mechanisms have been identified quite extensively in the research sample. However, the number of papers identified for inclusion in the systematic literature review was quite small, from which it can be concluded that there are surprisingly few publications focusing on this particular topic. Nevertheless, the trend indicates a probable increase in research in the subject area in the future. The general standpoint among researchers seems to be that the goals set by the EU are, as it were, a law of nature that cannot be deviated from. Consequently,... [more]

Based on the unique ubiquity of similar solvate structures found in solvate crystals and superconcentrated electrolytes, we performed a systematic study of four reported solvate crystals which consist of different lithium salts (i.e., LiMPSA, LiTFSI, LiDFOB, and LiBOB) solvated by acetonitrile (MeCN) based on first principles calculations. Based on the calculations, these solvate crystals are predicted to be electronic insulators and are expected to be similar to their insulating liquid counterpart (e.g., 4 M superconcentrated LiTFSI-MeCN electrolyte), which has been confirmed to be a promising electrolyte in lithium batteries. Although the MeCN molecule is highly unstable during the reduction process, it is found that the salt-MeCN solvate molecules (e.g., LiTFSI-(MeCN)2, LiDFOB-(MeCN)2) and their charged counterparts (anions and cations) are both thermodynamically and electrochemically stable, which can be confirmed by Raman vibrational modes through the unique characteristic variati... [more]

The permissible speed of suspended monorails in underground mines is determined by the internal regulations of each country and depends on the type of transportation. In the case of passenger transportation, the maximal driving speed in Polish underground mining regulations is 2 ms−1. Regarding the higher permitted driving speed in other countries, it is reasonable to consider changes to these regulations that would raise the permitted speed limit. Increasing the permissible travel speed would improve the efficiency of mining operations because of the significant reduction in the inefficient working time of miners traveling on the monorail from the shaft to their place of work. However, at the same time, an increase in the permissible speed of travel results in higher values of forces and accelerations affecting both the crew riding the train and the underground working infrastructure (the suspended route, slings, and arches yielding support). The results of the series of works carried... [more]

Wind is an abundant, yet intermittent, source of renewable energy, with speeds changing both spatially and temporally over a wide range of time scales. While wind variability is well documented on large meteorological time scales and the behavior of turbulent flow at high frequencies is well understood, there remain questions in the literature regarding the intermediate region of these domains. Understanding wind variability at the microscale, here considering a frequency range of 10−2 Hz < f < 1 Hz, is key for wind turbine control and modeling. In this paper, we quantify the variability of wind conditions for the meteorological tower at the Eolos wind research station in Minnesota using power spectral density analysis. Spectral analysis of wind samples with similar mean wind speeds was conducted to test the hypothesis that the wind spectrum’s shape is independent of the mean wind speed. Historical wind speed data were compared and evaluated to identify diurnal, seasonal, and int... [more]

Efforts to direct the economies of many countries towards low-carbon economies are being made in order to reduce their impact on global climate change. Within this process, replacing fossil fuels with hydrogen will play an important role in the sectors where electrification is difficult or technically and economically ineffective. Hydrogen may also play a critical role in renewable energy storage processes. Thus, the global hydrogen demand is expected to rise more than five times by 2050, while in the European Union, a seven-fold rise in this field is expected. Apart from many technical and legislative barriers, the environmental impact of hydrogen production is a key issue, especially in the case of new and developing technologies. Focusing on the various pathways of hydrogen production, the essential problem is to evaluate the related emissions through GHG accounting, considering the life cycle of a plant in order to compare the technologies effectively. Anion exchange membrane (AEM)... [more]

This paper presents a novel framework that mathematically and optimally quantifies demand response (DR) provisions, considering the power availability of Internet of Things (IoT)-based house load management for the provision of flexibility in the smart grid. The proposed framework first models house loads using IoT windows and occupant behavior, and then integrates IoT-based house loads into DR programs based on a novel mathematical optimization model to provide the optimal power flexibility considering the penetration of IoT-based houses in distribution systems. Numerical results that consider a 33-bus distribution system are reported and discussed to demonstrate the effectiveness of flexibility provisions, from integrating IoT-based houses into DR programs, on peak load reduction and system capacity enhancement.

The article presents the use of the Texas Instruments LM5170EVM-BIDIR bidirectional DC/DC converter to control power distribution in a hybrid energy storage system based on a battery−ultracapacitor system. The paper describes typical topologies of connecting a battery with an ultracapacitor. The results of tests for calibration and identification of converter parameters are presented. The main innovation of the solution presented in this paper is the appropriate selection of the nominal voltage of the ultracapacitor so that the converter can be operated only in the constant current mode, in a cascade connection, excluding the low-efficiency constant voltage mode. This article demonstrated that such control allows for high efficiency and reduction of losses in the DC/DC converter, which is necessary in the case of mobile solutions. The amount of losses was determined depending on the control voltage in the operation modes of the converter: in the Step Up mode by increasing the voltage f... [more]

A smart hybrid energy system (SHES) is presented using a combination of battery, PV systems, and gas/diesel engines. The economic/environmental dispatch optimization algorithm (EEDOA) is employed to minimize the total operating cost or total CO2 emission. In the face of the uncertainty of renewable power generation, the constraints for loss-of-load probability (LOLP) and the operating reserve for the rechargeable battery are taken into account for compensating the imbalance between load demand and power supplies. The grid-connected and islanded modes of SHES are demonstrated to address a low-carbon community. For forecasting load demand, PV power, and locational-based marginal pricing (LBMP), the proper forecast model, such as long short-term memory (LSTM) or extreme gradient boosting (XGBoost), is implemented to improve the EEDOA. A few comparisons show that (i) the grid-connected mode of SHES is superior to the islanded-connected mode of SHES due to lower total operating cost and les... [more]

Accurate and efficient short-term forecasting of multiple loads is of great significance to the operation control and scheduling of integrated energy distribution systems. In order to improve the effect of load forecasting, a mogrifier-quantum weighted memory enhancement long short-term memory (Mogrifier-QWMELSTM) neural network forecasting model is proposed. Compared with the conventional LSTM neural network model, the model proposed in this paper has three improvements in model structure and model composition. First, the mogrifier is added to make the data fully interact with each other. This addition can help enhance the correlation between the front and rear data and improve generalization, which is the main disadvantage of LSTM neural network. Second, the memory enhancement mechanism is added on the forget gate to realize the extraction and recovery of forgotten information. The addition can help improve the gradient transmission ability in the learning process of the neural netwo... [more]