The traditional load-shedding models usually use global optimization to get the load-shedding region, which will cause multiple variables, huge computing scale and other problems. This makes it hard to meet the requirements of timeliness in on-line power system operation risk assessment. In order to solve the problems of the present load-shedding models, a load-shedding model based on sensitivity analysis is proposed in this manuscript. By calculating the sensitivity of each branch on each bus, the collection of buses which have remarkable influence on reducing the power flow on over-load branches is obtained. In this way, global optimization is turned to local optimization, which can narrow the solution range. By comprehensively considering the importance of load bus and adjacency principle regarding the electrical coupling relationship, a load-shedding model is established to get the minimum value of the load reduction from different kinds of load buses, which is solved by the primal... [more]

In the presence of partial shading and other mismatch factors, bypass diodes may not offer complete elimination of excessive power dissipation due to cell reverse biasing, commonly referred to as hot-spotting in photovoltaic (PV) systems. As a result, PV systems may experience higher failure rates and accelerated ageing. In this paper, a cell-level simulation model is used to assess occurrence of hot-spotting events in a representative residential rooftop system scenario featuring a moderate shading environment. The approach is further used to examine how well distributed power electronics converters mitigate the effects of partial shading and other sources of mismatch by preventing activation of bypass diodes and thereby reducing the chances of heavy power dissipation and hot-spotting in mismatched cells. The simulation results confirm that the occurrence of heavy power dissipation is reduced in all distributed power electronics architectures, and that submodule-level converters offer... [more]

Background: Identifying the health status of wind turbines becomes critical to reduce the impact of failures on generation costs (between 25⁻35%). This is a time-consuming task since a human expert has to explore turbines individually. Methods: To optimize this process, we present a strategy based on Self Organizing Maps, clustering and a further grouping of turbines based on the centroids of their SOM clusters, generating groups of turbines that have similar behavior for subsystem failure. The human expert can diagnose the wind farm health by the analysis of a small each group sample. By introducing post-processing tools like Class panel graphs and Traffic lights panels, the conceptualization of the clusters is enhanced, providing additional information of what kind of real scenarios the clusters point out contributing to a better diagnosis. Results: The proposed approach has been tested in real wind farms with different characteristics (number of wind turbines, manufacturers, power,... [more]

In this paper, the formation of water in oil (W/O) model solution emulsions using untreated and oxidized asphaltenes as emulsifiers was evaluated. Emulsions were formed with deionized water and toluene at different water/toluene ratios (1:4, 1:1, and 4:1) and concentrations of asphaltenes of 100, 500, and 1000 mg/L. Asphaltenes were oxidized at two different temperatures of 373 and 473 K for various exposure times. Untreated and oxidized asphaltenes were characterized by thermogravimetric analyses, C, H, N, S and O elemental analyses, solvency tests in toluene, and qualitative structural indexes from Fourier-transform infrared spectroscopy. The emulsions were evaluated for stability, the percentage of oil in water (O/W) and W/O phases, interfacial tension (IFT), and mean droplet diameter. The asphaltenes solubility decreased up to 93% as the temperature of oxidation and the exposure time increased. The amount of W/O emulsion increases when asphaltene concentration, exposure time, and o... [more]

A marine energy system, which is fundamentally not paired with electric grids, should work for an extended period with high reliability. To put it in another way, by employing electrical utilities on a ship, the electrical power demand has been increasing in recent years. Besides, fuel cells in marine power generation may reduce the loss of energy and weight in long cables and provide a platform such that each piece of marine equipment is supplied with its own isolated wire connection. Hence, fuel cells can be promising power generation equipment in the marine industry. Besides, failure modes and effects analysis (FMEA) is widely accepted throughout the industry as a valuable tool for identifying, ranking, and mitigating risks. The FMEA process can help to design safe hydrogen fueling stations. In this paper, a robust FMEA has been developed to identify the potentially hazardous conditions of the marine propulsion system by considering a general type-2 fuzzy logic set. The general type... [more]

Actively controlling the camber angle to improve energy efficiency has recently gained interest due to the importance of reducing energy consumption and the driveline electrification trend that makes cost-efficient implementation of actuators possible. To analyse how much energy that can be saved with camber control, the effect of changing the camber angles on the forces and moments of the tyre under different driving conditions should be considered. In this paper, Magic Formula tyre models for combined slip and camber are used for simulation of energy analysis. The components of power loss during cornering are formulated and used to explain the influence that camber angles have on the power loss. For the studied driving paths and the assumed driver model, the simulation results show that active camber control can have considerable influence on power loss during cornering. Different combinations of camber angles are simulated, and a camber control algorithm is proposed and verified in... [more]

An improved modulated carrier control (MCC) method is proposed to offer high power factor (PF) and low total harmonic distortion (THD) at a wide input voltage range and load variation. The conventional MCC method not only requires a multiplier and divider, but also is hard to be implemented with a micro controller unit without a high frequency oscillator. To overcome the problem and maintain the advantages of the conventional MCC method, the proposed MCC method adopts a current integrator, an output voltage amplifier, a zero-current duration (ZCD) demodulator of the boost inductor, and a carrier generator. Thus, it can remove a multiplier and well, as it allows for being operable with a general micro control unit. This paper presents an operation principle of the proposed control method. To verify the proposed control method, experimental results with 400 W PFC boost converter is demonstrated.

The greatest requirement for Tunisian grid connections is low voltage ride through (LVRT). In fact, the network voltage generally results in a discrepancy between the generated active power and that which is delivered. This study was carried out to enhance the quality of the power injected into the grid by means of LVRT capability in Tunisian wind turbines using a permanent magnet synchronous generator (PMSG) controlled by the sliding mode control (SMC) approach based on direct power control (DPC) using space vector modulation (SVM). This approach was applied in order to control the active and reactive powers produced by the wind energy conversion system (WECS) and injected into the grid. Results obtained in MATLAB/Simulink simulations showed the efficiency of the introduced control strategy. An implementation in real time, using a dSpace1104 control board, was presented to illustrate the feasibility of the proposed control scheme and its effectiveness under fault conditions.

Optimal operation is an important aspect of energy efficiency that can be employed to reduce power consumption. In cooling systems, the chillers consume a large amount of electricity, especially if they are not optimally operated, therefore, they cannot produce the required or rated cooling load capacity. The objective of this paper is to improve coefficient of performance (COP) for the operation of chillers and to reduce power consumption. Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. Particularly, in contribution (1), two models are developed to predict/assess power consumption and cooling load capacity. While in contribution (2), the predictive model’s data obtained are used to classify the operating performance of the chiller and t... [more]

In order to explore a non-destructive method for measuring the polymerization degree (DP) of paper insulation in transformer, a new method that based on the optical properties of free fiber particles in transformer oil was studied. The chromatic dispersion images of fibers with different aging degree were obtained by polarizing microscope, and the eigenvalues (r, b, and Mahalanobis distance) of the images were extracted by the RGB (red, blue, and green) tricolor analysis method. Then, the correlation between the three eigenvalues and DP of paper insulation were simulated respectively. The results showed that the color of images changed from blue-purple to orange-yellow gradually with the increase of aging degree. For the three eigenvalues, the relationship between Mahalanobis distance and DP had the best goodness of fit (R² = 0.98), higher than that of r (0.94) and b (0.94). The mean square error of the relationship between Mahalanobis distance and DP (52.17) was also significantly low... [more]

In this paper, recent achievements in the application of the lattice Boltzmann method (LBM) to complex fluid flows are reported. More specifically, we focus on flows through reactive porous media, such as the flow through the substrate of a selective catalytic reactor (SCR) for the reduction of gaseous pollutants in the automotive field; pulsed-flow analysis through heterogeneous catalyst architectures; and transport and electro-chemical phenomena in microbial fuel cells (MFC) for novel waste-to-energy applications. To the authors’ knowledge, this is the first known application of LBM modeling to the study of MFCs, which represents by itself a highly innovative and challenging research area. The results discussed here essentially confirm the capabilities of the LBM approach as a flexible and accurate computational tool for the simulation of complex multi-physics phenomena of scientific and technological interest, across physical scales.

In recent years, the fractional order model has been employed to state of charge (SOC) estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation.... [more]

Demand response aggregators have been developed and implemented all through the world with more seen in Europe and the United States. The participation of aggregators in energy markets improves the access of small-size resources to these, which enables successful business cases for demand-side flexibility. The present paper proposes aggregator’s assessment of the integration of distributed energy resources in energy markets, which provides an optimized reschedule. An aggregation and remuneration model is proposed by using the k-means and group tariff, respectively. The main objective is to identify the available options for the aggregator to define tariff groups for the implementation of demand response. After the first schedule, the distributed energy resources are aggregated into a given number of groups. For each of the new groups, a new tariff is computed and the resources are again scheduled according to the new group tariff. In this way, the impact of implementing the new tariffs... [more]

Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module) is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is succ... [more]

An adaptive online sequential extreme learning machine (AOS-ELM) is proposed to predict the state-of-charge of the battery cells at different ambient temperatures. With limited samples and sequential data for training during the initial design stage, conventional neural network training gives higher errors and longer computing times when it maps the available inputs to SOC. The use of AOS-ELM allows a gradual increase in the dataset that can be time-consuming to obtain during the initial stage of the neural network training. The SOC prediction using AOS-ELM gives a smaller root mean squared error in testing (and small standard deviation in the trained results) and reasonable training time as compared to other types of ELM-based learnings and gradient-based machine learning. In addition, the subsequent identification of the cells’ static capacity and battery parameters from actual experiments is not required to estimate the SOC of each cell and the battery stack.

In this paper, an assessment on the health index (HI) of transformers is carried out based on Neural-Fuzzy (NF) method. In-service condition assessment data, such as dissolved gases, furans, AC breakdown voltage (ACBDV), moisture, acidity, dissipation factor (DF), color, interfacial tension (IFT), and age were fed as input parameters to the NF network. The NF network were trained individually based on two sets of data, known as in-service condition assessment and Monte Carlo Simulation (MCS) data. HI was also obtained from the scoring method for comparison with the NF method. It is found that the HI of transformers that was obtained by NF trained by MCS method is closer to scoring method than NF trained by in-service condition assessment method. Based on the total of 15 testing transformers, NF trained by MCS data method gives 10 transformers with the same assessments as scoring method as compared to eight transformers given by NF trained by in-service condition data method. Analysis b... [more]

Rapid fluctuation of solar irradiance due to cloud passage causes corresponding variations in the power output of solar PV power plants. This leads to rapid voltage instability at the point of common coupling (PCC) of the connected grid which may cause temporary shutdown of the plant leading to non-availability of energy in the connected load and distribution grid. An estimate of the duration and frequency of this outage is important for solar energy generators to ensure the generation and performance of the solar power plant. A methodology using PVsyst (6.6.4, University of Geneva, Geneva, Switzerland) and PSCAD (4.5, Manitoba HVDC Research Centre, Winnipeg, MB, Canada) simulation has been developed to estimate the duration and frequency of power outages due to rapid fluctuation of solar irradiance throughout the year. It is shown that the outage depends not only on the solar irradiance fluctuation, but also on the grid parameters of the connected distribution grid. A practical case s... [more]

Boundary layer ingestion is a promising method to decrease the propulsive power consumption of an aircraft, and therefore the fuel consumption. This leads to a reduced environmental impact and an improved cost-efficiency. To get a better understanding of this method and to estimate its benefits, the modelling of a propulsor located at the upper rear centerbody of a blended wing body aircraft is presented in this paper. A parallel compressor model approach is used to analyse the impact of the ingested low velocity fluid which leads to a non-uniform inflow. The required boundary layer data are generated with an analysis tool for 2D subsonic airfoils. Some parameter variations are conducted with the developed programme to study their impact on the power saving potential. In addition, a simple estimation for the benefit of embedded aeroengines is given. Despite the drawback from fan efficiency due to the inflow distortion, the results show a significant decrease in required propulsive powe... [more]

The structural and optimal operation of an Energy Hub (EH) has a tremendous influence on the hub’s performance and reliability. This paper envisions an innovative methodology that prominently increases the synergy between structural and operational optimization and targets system cost affordability. The generalized energy system structure is presented theoretically with all selective hub sub-modules, including electric heater (EHe) and solar sources block sub-modules. To minimize energy usage cost, an energy hub is proposed that consists of 12 kinds of elements (i.e., energy resources, conversion, and storage functions) and is modeled mathematically in a General Algebraic Modeling System (GAMS), which indicates the optimal hub structure’s corresponding elements with binary variables (0, 1). Simulation results contrast with 144 various scenarios established in all 144 categories of hub structures, in which for each scenario the corresponding optimal operation cost is previously calculat... [more]

Air leakage and its impact on the energy performance of dwellings has been broadly studied in countries with cold climates in Europe, US, and Canada. However, there is a lack of knowledge in this field in Mediterranean countries. Current Spanish building regulations establish ventilation rates based on ideal airtight envelopes, causing problems of over-ventilation and substantial energy losses. The aim of this paper is to develop a methodology that allows the characterization of the envelope of the housing stock in Spain in order to adjust ventilation rates taking into consideration air leakage. A methodology that is easily applicable to other countries that consider studying the airtightness of the envelope and its energetic behaviour improvement is proposed. A statistical sampling method has been established to determine the dwellings to be tested, considering relevant variables concerning airtightness: climate zone, year of construction, and typology. The air leakage rate is determi... [more]

After more than ten years of operation of EU-ETS trading, it is time to analyse the results and draw lessons from the experience. Economic research typically considers emission price as the main explanatory variables when measuring the effects of Emission Trading Systems. The novelty of this work is to analyse whether or not trade alone, as an institutional change, is effective in reducing greenhouse gases emissions. The objective of this paper is to analyse to what extent the EU-ETS as a “regulatory” instrument of the supply of allowances is responsible for the effectiveness of the carbon market as a basic tool in the reduction of emissions. The analysis also includes other overlapping policies aimed at fighting climate change, for example, the promotion of renewables. For the empirical analysis, an econometric model is estimated using panel data for the 28 European Union countries between 1990 and 2014. The econometric model include three dummy variables to measure the effectiveness... [more]

Wind speed prediction with spatio⁻temporal correlation is among the most challenging tasks in wind speed prediction. In this paper, the problem of predicting wind speed for multiple sites simultaneously is investigated by using spatio⁻temporal correlation. This paper proposes a model for wind speed prediction with spatio⁻temporal correlation, i.e., the predictive deep convolutional neural network (PDCNN). The model is a unified framework, integrating convolutional neural networks (CNNs) and a multi-layer perceptron (MLP). Firstly, the spatial features are extracted by CNNs located at the bottom of the model. Then, the temporal dependencies among these extracted spatial features are captured by the MLP. In this way, the spatial and temporal correlations are captured by PDCNN intrinsically. Finally, PDCNN generates the predicted wind speed by using the learnt spatio⁻temporal correlations. In addition, three error indices are defined to evaluate the prediction accuracy of the model on the... [more]

Synchronous-reference-frame phase-locked loop (SRF-PLL) is widely used in grid synchronization applications. However, under unbalanced, distorted and DC offset mixed grid conditions, its performance tends to worsen. In order to improve the filtering capability of SRF-PLL, a modified three-order generalized integrator (MTOGI) with DC offset rejection capability based on conventional three order generalized integrator (TOGI) and an enhanced delayed signal cancellation (EDSC) are proposed, then dual modified TOGI (DMTOGI) filtering stage is designed and incorporated into the SRF-PLL control loop with EDSC to form a new hybrid filter-based PLL. The proposed PLL can reject the fundamental frequency negative sequence (FFNS) component, DC offset component, and the rest of harmonic components in SRF-PLL input three-phase voltages at the same time with a simple complexity. The proposed PLL in this paper has a faster transient response due to the EDSC reducing the number of DSC operators. A smal... [more]

Because the limitations of water-based fracturing fluids restrict their fracturing efficiency and scope of application, liquid CO₂ is regarded as a promising substitute, owing to its unique characteristics, including its greater environmental friendliness, shorter clean-up time, greater adsorption capacity than CH₄ and less formation damage. Conversely, the disadvantage of high leak-off rate of CO₂ fracturing due to its very low viscosity determines its applicability in gas shales with ultra-low permeability, accurate measurement of shale permeability to CO₂ is therefore crucial to evaluate the appropriate injection rate and total consumption of CO₂. The main purpose of this study is to accurately measure shale permeability to CO₂ flow during hydraulic fracturing, and to compare the leak-off of CO₂ and water fracturing. A series of permeability tests was conducted on cylindrical shale samples 38 mm in diameter and 19 mm long using water, CO₂ in different phases and N₂ considering multi... [more]

Electric Vehicles (EVs) and hybrid Electric vehicles (HEVs) are going to reshape the future of the transportation sector. However, adopting large numbers of EVs and HEVs will impact the electric utilities as well. Managing the charging/discharging of substantial numbers of distributed batteries will be critical for the successful adoption of EVs and HEVs. Therefore, this paper presents a review study about the recent control and optimization strategies for managing the charging/discharging of EVs. The paper covers different control and operation strategies reported in the literature as well as issues related to the real time dispatching of EVs in the smart grids. In addition, challenges related to the stochastic nature of the driving characteristics of EVs are considered. Finally, some open problems related to the energy management of EVs will be presented.