Energies — Open Access Journal

This study aims to determine the optimal configuration (position and operation duration) for wall mounted mechanical mixers based on the comparison of three-dimensional computational fluid dynamics (CFD) modelling results and physical data collected from the treatment plant. A three dimensional model of anoxic zone in 1, 2 and 3 of Northern Wastewater Treatment Plant (NWWTP) located at Cairns Regional Council, Cairns, Queensland, Australia was developed and validated. The model was used to simulate the flow pattern of the WWTP and the simulation results are in good agreement with the physical data varying between 0% to 15% in key locations. The anoxic zones were subject to velocities less than the desired 0.3 m per second however results for mixed liquor suspended solids (MLSS) concentration indicate that good mixing is being achieved. Results for suspended solids concentrations suggest that the anoxic zones are towards the upper limits recommended by literature for specific power dissipation. The duration for operation of mechanical mixers was investigated and identified that the duration could be reduced from 900 s down to 150 s. Alternative mixer positioning was also investigated and identified positioning which would increase the average flow velocity with decreased duration (150 s). The study identified that Council may achieve savings of $28,500 per year through optimisation of the mechanical mixers and would be expected to extend the operational life of the mixers. Full article

The methodological framework for assessing adaptability of the economy to changes in energy prices and risks to energy markets was developed. The study proposes indicators for assessing the level of adaptability of the economic sectors to changes in prices for energy carriers and to risks of energy markets. The model of decomposition of adaptability level of the economy sectors to changes in energy prices has been developed. The theoretical and empirical analysis of the influence of energy prices on adaptability level of enterprises and households is carried out. Based on the empirical analysis, it was found that adaptability level of the sectors of Ukrainian economy significantly differs both in the years of the investigated period and in sectors of the economy. At the same time, most indicators of the level of adaptability vary from 0.4 to 0.7. Consequently, the actual decline in the profit of enterprises was 40–70% lower than the potentially possible decrease in the profit of these enterprises due to the prices rising for energy carriers. Moreover sectors which are less vulnerable to the growth of prices show higher adaptability level.The possibility of using the obtained results in developing a state energy saving strategy is substantiated. Full article

This study aims to address the inherent uncertainty in plug loads and load extraction, distributed generation, and the inevitable circulating current in a parallel structure. Therefore, in this paper, an adaptive backstepping control scheme with an online parameter estimator (OPE) for a plug-and-play parallel converter system in a four-port power switcher is proposed. The adaptive backstepping control method was designed in the dq0 coordinate system to suppress the circulating current in the zero-component; the circulating current can be suppressed by using an embedded algorithm and omitting the extra controller. An adaptive update law was designed to weaken the influence of the arbitrary plug and extraction operations in the DC and AC buses to realize the plug-and-play function. The transient tracking performance is governed by the limitation of maximum total errors in the voltage and current. As a result, the settling times of the voltage, current, and power decreased. Additionally, to further improve the system robustness, an online inductance and resistance estimator was established using an optimal algorithm that solves the weighted least squares problem. In the estimator, there are no additional voltage and current sensors needed, and the mean squared error (MSE) of the estimation can be minimized. Simulation studies on a two-converter parallel system with a plug-and-play function were conducted using MATLAB/SIMULINK (R2018b, MathWorks, Natick, MA, USA) to verify the effectiveness of the proposed adaptive backstepping control strategy. The results show that this strategy improves system performance over that of a system with unbalanced parameters among a parallel structure with AC and DC system disturbances caused by arbitrary plug and extraction operations. Full article

With the deregulation of electricity market, generation companies must take part in strategic bidding by offering its bidding quantity and bidding price in a day-ahead electricity wholesale market to sell their electricity. This paper studies the strategic bidding of a generation company with thermal power units and wind farms. This company is assumed to be a price-maker, which indicates that its installed capacity is high enough to affect the market-clearing price in the electricity wholesale market. The relationship between the bidding quantity of the generation company and market-clearing price is then studied. The uncertainty of wind power is considered and modeled through a set of discrete scenarios. A scenario-based two-stage stochastic bidding model is then provided. In the first stage, the decision-maker determines the bidding quantity in each time period. In the second stage, the decision-maker optimizes the unit commitment in each wind power scenario based on the bidding quantity in the first stage. The proposed two-stage stochastic optimization model is an NP-hard problem with high dimensions. To tackle the problem of “curses-of-dimensionality” caused by the coupling scenarios and improve the computation efficiency, a modified Benders decomposition algorithm is used to solve the model. The computational results show the following: (1) When wind power uncertainty is considered, generation companies prefer higher bidding quantities since the loss of wind power curtailment is much higher than the cost of additional power purchases in the current policy environment. (2) The wind power volatility has a strong negative effect on generation companies. The higher the power volatility is, the lower the profits, the bidding quantities, and the wind power curtailment of generation companies are. (3) The thermal power units play an important role in dealing with the wind power uncertainty in the strategic bidding problem, by shaving peak and filling valley probabilistic scheduling. Full article

This paper proposed a distributed genetic algorithm (DGA) to solve the energy efficient coverage (EEC) problem in the wireless sensor networks (WSN). Due to the fact that the EEC problem is Non-deterministic Polynomial-Complete (NPC) and time-consuming, it is wise to use a nature-inspired meta-heuristic DGA approach to tackle this problem. The novelties and advantages in designing our approach and in modeling the EEC problems are as the following two aspects. Firstly, in the algorithm design, we realized DGA in the multi-processor distributed environment, where a set of processors run distributed to evaluate the fitness values in parallel to reduce the computational cost. Secondly, when we evaluate a chromosome, different from the traditional model of EEC problem in WSN that only calculates the number of disjoint sets, we proposed a hierarchical fitness evaluation and constructed a two-level fitness function to count the number of disjoint sets and the coverage performance of all the disjoint sets. Therefore, not only do we have the innovations in algorithm, but also have the contributions on the model of EEC problem in WSN. The experimental results show that our proposed DGA performs better than other state-of-the-art approaches in maximizing the number of disjoin sets. Full article

More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent nature of solar and wind power can in general cause large problems for power system control. Parallel to this process, the aging of existing infrastructure also imposes requirements to utility budgets in the form of a need for large capital investments in reconstruction or maintenance of key equipment. Synchrophasor and other synchronized measurement technologies are setting themselves as one of the solutions for larger wind power integration. With that aim, in this paper one possible solution for wind power control through data mining algorithms used on a large quantity of data gathered from phasor measurement units (PMU) is described. Developed model and algorithm are tested on an IEEE 14 bus test system as well as on real measurements made on wind power plants currently in operation. One such wind power plant is connected to the distribution grid and the other one to the transmission grid. Results are analyzed and compared. Full article

This paper proposes a highly efficient single-phase three-level neutral point clamped (NPC) converter operated by a model predictive control (MPC) method with reduced commutations of switches. The proposed method only allows switching states with none or a single commutation at the next step as candidates for future switching states for the MPC method. Because the proposed method preselects switching states with reduced commutations when selecting an optimal state at a future step, the proposed method can reduce the number of switchings and the corresponding switching losses. Although the proposed method slightly increases the peak-to-peak variations of the two dc capacitor voltages, the developed method does not deteriorate the input current quality and input power factor despite the reduced number of switching numbers and losses. Thus, the proposed method can reduce the number of switching losses and lead to high efficiency, in comparison with the conventional MPC method. Full article

Renewable energy sources (RES) are playing an increasingly important role in energy markets around the world. It is necessary to evaluate the benefits from a higher level of RES integration with respect to a more active cross-border transmission system. In particular, this paper focuses on the sustainable energy transitions for Finland and Italy, since they have two extreme climate conditions in Europe and quite different profiles in terms of energy production and demand. We developed a comprehensive energy system model using EnergyPLAN with hourly resolution for a reference year for both countries. The models include electricity, heat and transportation sectors. According to the current base models, new scenarios reflecting an RES increase in total fuel consumption have been proposed. The future shares of renewables are based on each nation’s potential. The outcomes of the new scenarios support the future national plans, showing how decarburization in an energy system can occur in relation to the European Roadmap 2030 and 2050. In addition, possible power transmission between Italy and Finland were investigated according to the vision of an integrated European energy system with more efficient cross-border activities. Full article

Since different incident waves will cause the same array to perform differently with respect to the wave energy converter (WEC), the parameters of the incident wave, including the incident angle and the incident wave number, are taken into account for optimizing the wave energy converter array. Then, the differential evolution (DE) algorithm, which has the advantages of simple operation procedures and a strong global search ability, is used to optimize the wave energy converter array. However, the traditional differential evolution algorithm cannot satisfy the convergence precision and speed simultaneously. In order to make the optimization results more accurate, the concept of an adaptive mutation operator is presented to improve the performance of differential evolution algorithm. It gives the improved algorithm a faster convergence and a higher precision ability. The three-float, five-float, and eight-float arrays were optimized, respectively. It can be concluded that the larger the size of the array is, the greater the interaction between the floats is. Hence, a higher efficiency of wave energy extraction for wave energy converter arrays is achieved by the layout optimization of the array of wave energy converters. The results also show that the optimal layout of the array system is inhomogeneously distributed and that the improved DE algorithm used on array optimization is superior to the traditional DE algorithm. Full article

Conventional gas turbines are approaching their efficiency limits and performance gains are becoming increasingly difficult to achieve. Pressure Gain Combustion (PGC) has emerged as a very promising technology in this respect, due to the higher thermal efficiency of the respective ideal gas turbine thermodynamic cycles. Up to date, only very simplified models of open cycle gas turbines with pressure gain combustion have been considered. However, the integration of a fundamentally different combustion technology will be inherently connected with additional losses. Entropy generation in the combustion process, combustor inlet pressure loss (a central issue for pressure gain combustors), and the impact of PGC on the secondary air system (especially blade cooling) are all very important parameters that have been neglected. The current work uses the Humphrey cycle in an attempt to address all these issues in order to provide gas turbine component designers with benchmark efficiency values for individual components of gas turbines with PGC. The analysis concludes with some recommendations for the best strategy to integrate turbine expanders with PGC combustors. This is done from a purely thermodynamic point of view, again with the goal to deliver design benchmark values for a more realistic interpretation of the cycle. Full article

The ability to predict consumption is an essential tool for the management of a power distribution network. The availability of an advanced metering infrastructure through smart meters makes it possible to produce consumption forecasts down to the level of the individual user and to introduce intelligence and control at every level of the grid. While aggregate load forecasting is a mature technology, single user forecasting is a more difficult problem to address due to the multiple factors affecting consumption, which are not always easily predictable. This work presents a hybrid machine learning methodology based on random forest (RF) and linear regression (LR) for the deterministic and probabilistic forecast of household consumption at different time horizons and resolutions. The approach is based on the separation of long term effects (RF) from short term ones (LR), producing deterministic and probabilistic forecasts. The proposed procedure is applied to a public dataset, achieving a deterministic forecast accuracy much higher than other methodologies, in all scenarios analyzed. This covers horizons of forecast from one minute to one year, and highlights the great added value provided by probabilistic forecasting. Full article

Voltage sag characterization is essential for extracting information about a sag event’s origin and how sag events impact sensitive equipment. In response to such needs, more characteristics are required, such as the phase-angle jump, point-on-wave, unbalance, and sag type. However, the absence of an effective automatic segmentation method is a barrier to obtaining these characteristics. In this paper, an automatic segmentation method is proposed to improve this situation. Firstly, an extended voltage sag characterization method is described, in which segmentation plays an important role. Then, a multi-resolution singular value decomposition method is introduced to detect the boundaries of each segment. Further, the unsolved problem of how to set a threshold adaptively for different waveforms is addressed, in which the sag depth, the mean square error, and the entropy of the sag waveform are considered. Simulation data and field measurements are utilized to validate the effectiveness and reliability of the proposed method. The results show that the accuracies of both boundary detection and segmentation obtained using the proposed method are higher than those obtained using existing methods. In general, the proposed method can be implemented into a power quality monitoring system as a preprocess to support related research activities. Full article

In this paper, the combustion of methane hydrate over a powder layer is experimentally studied using thermal imaging and Particle Tracking Velocimetry (PTV) methods. The experiments are carried out at different velocities of the external laminar air-flow from zero to 0.6 m/s. Usually, simulation of methane hydrate combustion is carried out without taking into account free convection. A standard laminar boundary layer is often considered for simplification, and the temperature measurements are carried out only on the axis of the powder tank. Measurements of the powder temperature field have shown that there is a highly uneven temperature field on the layer surface, and inside the layer the transverse temperature profiles are nonlinear. The maximum temperature always corresponds to the powder near the side-walls, which is more than 10 °C higher than the average volumetric temperature in the layer. Thermal imager measurements have shown the inhomogeneous nature of combustion over the powder surface and the highly variable velocity of methane above the surface layer. The novelty of the research follows from the measurement of the velocity field using the PTV method and the measurement of methane velocity, which show that the nature of velocity at combustion is determined by the gas buoyancy rather than by the forced convection. The maximum gas velocity in the combustion region exceeds 3 m/s, and the excess of the oxidizer over the fuel leads to more than tenfold violation of the stoichiometric ratio. Despite that, the velocity profile in the combustion region is formed mainly due to free convection, it is also necessary to take into account the external flow of the forced gas U₀. Even at low velocities U₀, the velocity direction lines significantly deviate under the forced air-flow. Full article

The precise estimation of position is an essential concern for the control of a switched reluctance motor (SRM). Given the prominent role of position, the promising sensorless control approach for an SRM drive should be capable of providing accurate position. An inductance-based approach has been widely applied in the position estimation. However, the estimated accuracy suffers from the magnetic saturation effect, resulting in the poor performance of sensorless operation. This paper presents a reversible synchronization of commutation with the corresponding rotor position for SRM. With the consideration of magnetic saturation, the proposed approach is taken as a suitable candidate and plays an essential role in accommodating the requirement of optimal control. The relationship between a typical inductance position and magnetic circuit saturation is investigated. The instant of the intersections is sensed by comparing the instantaneous inductance of adjacent phases. Thus, the predicted position is obtained with the information of the special point and the calculated average speed. Compared with other existing methods, the proposed approach has the certain advantages, such as the ability to update the estimated speed and position six times per electrical period, which guarantees the estimated accuracy. The proposed approach is also valid even when the motor is operated at an acceleration state and heavy load operation. In addition, the requirement of the educated inductance structure is not unnecessary, less memory space is needed in the chip, and the accumulated error is eliminated. The simulation and experimental findings demonstrate the feasibility and practicality of the proposed position estimation approach with carrying out the inertial operation, load mutation, and high-speed test. Full article

This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. Also, it imposes a sinusoidal waveform of the current at the grid side, which allows active power filtering without a harmonic currents identification phase. The latter attempts to reduce the size and cost of the system as well as providing better performance. In addition, it can be implemented in a low-cost control platform due to its simplicity. A double-stage PV system is selected due to its flexibility in control, unlike single-stage strategies. Sliding mode control-based particle swarm optimization (PSO) is used to track the maximum power of the PV system. It offers high accuracy and good robustness. Concerning DC bus voltage of the inverter, the anti-windup PI controller is tuned offline using the particle swarm optimization algorithm to deliver optimal performance in DC bus voltage regulation. The overall system has been designed and validated in an experimental prototype; the obtained results in different phases demonstrate the higher performance and the better efficiency of the proposed system in terms of power quality enhancement and PV power injection. Full article

Considerable prime global energy is used in the transport sector. Significant energy is lost to overcome the internal friction of engines in transport vehicles. Journal bearings are crucial tribo-pairs and passive components that cause energy loss. Frictional losses increase extensively during the warm-up period of an engine due to high lubricant viscosity. Recent tribological developments have shown that surface textures can be a potential solution to reduce friction. A numerical investigation is performed to evaluate the effect of surface texture on the frictional and lubrication performance of a journal bearing at varying thermal operating conditions in an internal combustion engine. Temperature variations during engine warm-up are considered with oil rheology to observe texture-based improvements. Surface texture substantially reduces frictional energy loss during engine warm-up. Eight different monograde and multigrade engine oils are considered, and consistency is observed in texture-based improved outcomes. Full article

Oxidation of biodiesel (BD) obtained from the decomposition of biomass can damage the fuel injection and engine parts during its use as a fuel. The excess heating of vegetable oils can also cause polymerization of the biodiesel. The extent of BD oxidation depends on its fatty acid composition. In this study, an accelerated oxidation test of BDs at 95 °C was investigated according to ASTM D 2274 by applying a long-term storage test for 16 weeks. The density, viscosity, and total acid number (TAN) of BDs increased because of the accelerated oxidation. Furthermore, the contents of unsaturated fatty acid methyl esters (FAMEs), C18:2 ME, and C18:3 ME in BDs decreased due to the accelerated oxidation. The ¹H-nuclear magnetic resonance spectrum of BDs that were obtained from the accelerated high temperature oxidation at 180 °C for 72 h differed from that of fresh BDs. The mass spectrum obtained from the analysis of the model FAME, linoleic acid (C18:2) methyl ester, which was oxidized at high temperature, indicated the formation of dimers and epoxy dimers of linoleic acid (C18:2) methyl ester by a Diels-Alder reaction. Full article

To address the challenges of the next generation of smart windows for energy-efficient buildings, new electrochromic devices (ECDs) are introduced. These include indium molybdenum oxide (IMO), a conducting oxide transparent in the near-infrared (NIR) region, and a NIR-emitting electrolyte. The novel electrolytes are based on a sol-gel-derived di-urethane cross-linked siloxane-based host structure, including short chains of poly (ε-caprolactone) (PCL(530) (where 530 represents the average molecular weight in g mol⁻¹). This hybrid framework was doped with a combination of either, lithium triflate (LiTrif) and erbium triflate (ErTrif₃), or LiTrif and bisaquatris (thenoyltrifluoroacetonate) erbium (III) ([Er(tta)₃(H₂O)₂]). The [email protected][Er(tta)₃(H₂O)₂] device presents a typical Er³⁺ NIR emission around 1550 nm. The figures of merit of these devices are high cycling stability, good reversibility, and unusually high coloration efficiency (CE = ΔOD/ΔQ, where Q is the inserted/de-inserted charge density). CE values of −8824/+6569 cm² C⁻¹ and −8243/+5200 cm² C⁻¹ were achieved at 555 nm on the 400th cycle, for [email protected]₃ and [email protected][Er(tta)₃(H₂O)₂], respectively. Full article

New energy solutions are needed to decrease the currently high electricity costs from conventional electricity-only central power plants in Cyprus. A promising solution is a decentralized, hybrid photovoltaic-solid oxide fuel cell (PV-SOFC) system. In this study a decentralized, hybrid PV-SOFC system is investigated as a solution for useful energy supply to a commercial building (small hotel). An actual load profile and solar/weather data are fed to the system model to determine the thermoeconomic characteristics of the proposed system. The maximum power outputs for the PV and SOFC subsystems are 70 and 152 kWe, respectively. The average net electrical and total efficiencies for the SOFC subsystem are 0.303 and 0.700, respectively. Maximum net electrical and total efficiencies reach up to 0.375 and 0.756, respectively. The lifecycle cost for the system is 1.24 million USD, with a unit cost of electricity at 0.1057 USD/kWh. In comparison to the conventional case, the unit cost of electricity is about 50% lower, while the reduction in CO₂ emissions is about 36%. The proposed system is capable of power and heat generation at a lower cost, owing to the recent progress in both PV and fuel cell technologies, namely longer lifetime and lower specific cost. Full article