The variability of rail surfaces can result in wheel−rail slippage, which reduces the accuracy of subway braking systems, or even endangers the operation safety. It is necessary to conduct optimal anti-slip control with the estimation of the wheel−rail adhesion state. In this paper, an online super-twisting sliding mode anti-slip control strategy is proposed for subway vehicles. Firstly, real-time wheel−rail adhesion state estimation is performed by utilizing the recursive least squares algorithm under complex and variable rail surface conditions. Then, the differential evolution algorithm is adopted to search the current optimal slip velocity based on the wheel−rail adhesion state. The super-twisting sliding mode controller is designed to implement the optimal sliding velocity tracking. The controller exploits the high-order derivatives of the sliding mode to eliminate chatter vibration and avoid the effect of disturbance, improving the anti-slip control performance. Finally, the effe... [more]

In this paper, an interior permanent magnet (IPM) synchronous machine with multiflux barriers is proposed to meet the wide speed regulation application requirements of electric vehicles. Based on the flux barrier characteristic, an electromagnetic−mechanical coupling optimization strategy is employed for the machine design. In order to facilitate the optimization design, the rotor barriers are divided into two optimization zones, the maximum stress zone and the maximum deformation zone. The electromagnetic−mechanical coupling optimization strategy is divided into two stages accordingly. In the first stage, the machine is regarded as a synchronous reluctance machine by ignoring permanent magnets, where the dimensions of the arc-shaped barriers are optimized to achieve a large reluctance torque and small stress. In the second stage, the dimensions of the arc-shaped PMs and the elliptical barrier are optimized with three objectives of minimum torque ripple, minimum flux linkage, and minim... [more]

Low pollution, slight corrosion, and low cost are the main challenges in the conversion of biomass to biogas. In this work, based on the whole process optimization of biomass conversion, an effective method using an ultra-low concentration of FeCl2 was proposed to simultaneously promote the biochemical reaction and improve the pretreatment effect. The concentration of FeCl2 in the pretreatment was determined according to the requirements of the minimum amount which led to the optimal performance of the anaerobic system and had economical importance. The effects of FeCl2 in the pretreatment and anaerobic fermentation were evaluated by comparing with that of distilled water in the production of hydrolysis products and organic acids. The optimal condition was obtained at 180 °C and 10 min with 1 × 10−5 mol/L FeCl2 pretreatment. At that condition, hemicellulose achieved a high conversion of 97.6%, and the released xylose reached nearly 95%. At least 77.5% of the organic matter in the solut... [more]

In this paper, an innovative method for managing a smart-community microgrid (SCM) with a centralized electrical storage system (CESS) is proposed. The method consists of day-ahead optimal power flow (DA−OPF) for day-ahead SCM managing and its subsequent evaluation, considering forecast uncertainties. The DA−OPF is based on a data forecast system that uses a deep learning (DL) long short-term memory (LSTM) network. The OPF problem is formulated as a mathematical mixed-integer nonlinear programming (MINLP) model. Following this, the developed DA−OPF strategy was evaluated under possible operations, using a Monte Carlo simulation (MCS). The MCS allowed us to obtain potential deviations of forecasted data during possible day-ahead operations and to evaluate the impact of the data forecast errors on the SCM, and that of unit limitation and the emergence of critical situations. Simulation results on a real existing rural conventional community endowed with a centralized community renewable... [more]

Artificial lift methods have applications in oil wells where oil production is no longer possible due to natural reservoir energy, so this necessary energy is added by introducing lift methods. In order to achieve optimum production, the selection of an artificial lift method is very important. This paper uses fuzzy logic as a mathematical and conceptual model for selection of the optimal artificial lift method. The outcome or IF-THEN rules, as the central part of the model, is based on empirical data from the selected oil fields. Results are presented in two ways: according to the surfaces of irregular geometric bodies, and their gravity with the scattering of results, i.e., on smaller and greater possibilities of interpreting results when there are small differences in outputs. Finally, a sensitivity analysis of the model is presented.

Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs ch... [more]

Pipeline leakage of crude oil, refined oil or other petroleum derivatives can cause serious damage to the environment, soil, and more importantly, pose a serious threat to personal safety. The losses can be minimized to a degree by active control. Therefore, timely and effective control measures should be taken to minimize the leak volume whenever a pipeline leaks. However, the complexity of pipeline hydraulic systems makes it difficult to optimize control schemes for pipeline hydraulic devices under leak conditions, and existing studies rarely consider complex transient processes. This paper aims to establish a mixed integer linear programming model considering transient processes, hydraulic constraints, equipment constraints and flow constraints, and develop a detailed control scheme of the devices by the branch and bound algorithm. Moreover, it is the objective of the model to figure out the most optimal control plan to minimize the leakage. Experiments on a real-world liquid pipeli... [more]

Transformer state forecasting and fault forecasting are important for the stable operation of power equipment and the normal operation of power systems. Forecasting of the dissolved gas content in oil is widely conducted for transformer faults, but its accuracy is affected by data scale and data characteristics. Based on phase space reconstruction (PSR) and weighted least squares support vector machine (WLSSVM), a forecasting model of time series of dissolved gas content in transformer oil is proposed in this paper. The phase spaces of time series of the dissolved gas content sequence are reconstructed by chaos theory, and the delay time and dimension are obtained by the C-C method. The WLSSVM model is used to forecast time series of dissolved gas content, the chemical reaction optimization (CRO) algorithm is used to optimize training parameters, the bootstrap method is used to build forecasting intervals. Finally, the accuracy and generalization ability of the forecasting model are ve... [more]

In this study, 167 land parcels of downtown Shanghai, China, were used to investigate the relationship between parcel-level land use/land cover (LULC) components and associated summertime intra-surface urban heat island (SUHI) effect, and further analyze the potential of mitigating summertime intra-SUHI effect through the optimized LULC components, by integrating a thermal sharpening method combining the Landsat-8 thermal band 10 data and high-resolution Quickbird image, statistical analysis, and nonlinear programming with constraints. The results show the remarkable variations in intra-surface urban heat island (SUHI) effect, which was measured with the mean parcel-level blackbody sensible heat flux in kW per ha (Mean_pc_BBF). Through measuring the relative importance of each specific predictor in terms of their contributions to changing Mean_pc_BBF, the influence of parcel-level LULC components on excess surface flux of heat energy to the atmosphere was estimated using the partial le... [more]

The Eastern Wu tomb in Shangfang Town, Nanjing City is a brick tomb of the Six Dynasties in China, which is very famous for its big scale and complex structure. After being excavated, biodeterioration occurred on the interior wall of the tomb chambers due to the fluctuation of environmental factors, which threatens the cultural value of this architectural heritage. Biodeterioration is highly related to the mild temperature and the high humidity in the tomb chamber and condensation on the wall surface. To reduce biodeterioration in the Eastern Wu tomb, environment monitoring was carried out and the effect of the current protective shed on the Eastern Wu tomb was examined. The hygrothermal transfer model of the protective shed was developed to evaluate the effects of the optimization of the protective shed for reducing the condensation on the wall surface. The results show that condensation on the wall surface of the site was reduced by 53% in a year after the functional space utilizing... [more]

This paper investigates the cost-effectiveness of operation strategies which can be used to abate CO 2 emissions in a local multi-energy system. A case study is carried out using data from a real energy system that integrates district heating, district cooling, and electricity networks at Chalmers University of Technology. Operation strategies are developed using a mixed integer linear programming multi-objective optimization model with a short foresight rolling horizon and a year of data. The cost-effectiveness of different strategies is evaluated across different carbon prices. The results provide insights into developing abatement strategies for local multi-energy systems that could be used by utilities, building owners, and authorities. The optimized abatement strategies include: increased usage of biomass boilers, substitution of district heating and absorption chillers with heat pumps, and higher utilization of storage units. The results show that, by utilizing all the st... [more]

In this paper, an optimization model for biogas power plant feedstock mixture with respect to feedstock and transportation costs using a differential evolution algorithm (DEA) is presented. A mathematical model and an optimization problem are presented. The proposed model introduces an optimal mixture of different feedstock combinations in a biogas power plant and informs about the maximal transportation distance for each feedstock before being unprofitable. In the case study, the proposed model is applied to five most commonly used feedstock in biogas power plants in Croatia and Hungary. The research is performed for a situation when the biogas power plant is not owned by the farm owner but by a third party. An optimization procedure is performed for each scenario with a cost of methane production that does not exceed 0.75 EUR/m3 in 1 MWe biogas power plant. The results show the needed yearly amounts and the maximum transportation distance of each feedstock.

In the last decade, particular attention has been paid to the organic Rankine cycle (ORC) power plant, a technology that implements a classical steam Rankine cycle using low-boiling fluid of organic origin. Depending on the specific application and the choice of the designer, the ORC can be optimized using one or several criteria. The selected objectives reflect various system performance aspects, such as: thermodynamic, economic, environmental or other. In this study, a novel criterion called exergy utilization index (XUI) is defined and used to maximize the utilization of an energy source in the ORC system. The maximization of the proposed indicator is equivalent to bring the heat carrier outlet temperature to the ambient temperature as close as possible. In the studied case, the XUI is applied along with the total heat transfer area of the system, and the multi-objective optimization is performed in order to determine the optimal operating conditions of the ORC. Moreover, to reveal... [more]

The interest in studying energy systems’ resilience is increasing due to a rising awareness of the importance of having a secure energy supply. This growing trend is a result of a series of recent disruptions, among others also affecting electricity systems. Therefore, it is of crucial importance for policymakers to determine whether their country has a resilient electricity supply. Starting from a set of 12 indicators, this paper uses data envelopment analysis (DEA) to comprehensively evaluate the electricity supply resilience of 140 countries worldwide. Two DEA models are applied: (1) the original ratio-based Charnes, Cooper, and Rhodes (CCR) model and (2) a novel hybrid framework for robust efficiency analysis incorporating linear programming and Monte Carlo simulations. Results show that the CCR model deems 31 countries as efficient and hence lacks the capability to differentiate them. Furthermore, the CCR model considers only the best weight vectors for each country, which are not... [more]

This paper advances a practical tool for production forecasting, using a 2-segment Decline Curve Analysis (DCA) method, based on an analytical flow-cell model for multi-stage fractured shale wells. The flow-cell model uses a type well and can forecast the production rate and estimated ultimate recovery (EUR) of newly planned wells, accounting for changes in completion design (fracture spacing, height, half-length), total well length, and well spacing. The basic equations for the flow-cell model have been derived in two earlier papers, the first one dedicated to well forecasts with fracture down-spacing, the second one to well performance forecasts when inter-well spacing changes (and for wells drilled at different times, to account for parent-child well interaction). The present paper provides a practical workflow, introduces correction parameters to account for acreage quality and fracture treatment quality. Further adjustments to the flow-cell model based 2-segment DCA method are mad... [more]

The impact of environmental regulations implemented in the power industry that affect the consumption of solid fuels is of key importance to coal-based power generation systems, such as that in Poland. In this context, the main purpose of the paper was to determine the future demand for hard coal and brown coal in the Polish power sector by 2050 with reference to the environmental regulations implemented in the power sector. To achieve these goals, a mathematical model was developed using the linear programming approach, which reflected the key relationships between the hard and brown coal mining sector and the power sector in the context of the environmental regulations discussed. The environmental regulations selected had a great influence on the future demand for hard and brown coal in the power generation sector. The scope of this influence depended on particular regulations. The prices of CO2 emission allowances and stricter emissions standards stemming from the Industrial Emissio... [more]

In recent years, residential users have begun to be equipped with micro-CHP (combined heat and power) generation technologies with the aim of decreasing primary energy consumption and reducing environmental impact. In these systems, the prime mover supplies both thermal and electrical energy, and an auxiliary boiler and the national electrical grid are employed as supplementary systems. In this paper, a simulation model, which accounts for component efficiency and energy balance, was developed to replicate the interaction between the users and the energy systems in order to minimize primary energy consumption. The simulation model identified the optimal operation strategy of two residential users by investigating different energy system configurations by means of a dynamic programming algorithm. The reference scenario was compared to three different scenarios by considering independent energy systems, shared thermal and electrical energy storage and also the shared prime mover. Such a... [more]

A magnetic nano-solid acid catalyst Fe3O4-PDA-SO3H was synthetized through an efficient method, as an eco-friendly and more efficient catalyst. The obtained catalyst has uniform core-shell structure, appropriate particle size, and high acid density. Fe3O4-PDA-SO3H was applied to catalyze the esterification of levulinic acid (LA) with alcohols of different chain length to produce the levulinate esters. The catalytic effect was optimized from the aspects of catalyst dosage, reaction temperature, and acid-alcohol molar ratio. Furthermore, the response surface optimization method was used to obtain the optimal conditions. Verified under these conditions, the experimental results showed that the conversion rate of LA can reach 95.87%, which was much higher than common cationic exchange resin Amberlyst 36 and Amberlyst 46. Furthermore, the recovery and reuse of the Fe3O4-PDA-SO3H was demonstrated six times without obvious loss in the activity.

Retrofitting of industrial heat recovery systems can contribute significantly to meeting energy efficiency targets for industrial plants. One issue to consider when screening retrofit design proposals is that industrial heat recovery systems must be able to handle variations, e.g., in inlet temperatures or heat capacity flow rates, in such a way that operational targets are reached. Consequently, there is a need for systematic retrofitting methodologies that are applicable to multi-period heat exchanger networks (HENs). In this study, a framework was developed to achieve flexible and cost-efficient retrofit measures of (industrial) HENs. The main idea is to split the retrofitting processes into several sub-steps. This splitting allows well-proven (single period) retrofit methodologies to be used to generate different design proposals, which are collected in a superstructure. By means of structural feasibility assessment, structurally infeasible design proposals can be discarded from fu... [more]

One of the most important factors in determining the profitable production of microalgae biomass is the use of a cost effective growth medium that is rich in nutrients. The objective of the study was to determine the possibility of using digestates from anaerobic digestion of different feedstock mixtures as the media for Scenedesmus sp. cultivation. A different liquid digestate composition was obtained in terms of organic compounds, phosphorus, and nitrogen concentrations, depending on the substrates used in the anaerobic digestion. It was found that the highest biomass production was obtained when using digestate from anaerobic digestion of the feedstock mainly composed of microalgae biomass, which was characterized by low organic compounds concentration. In this case, the average biomass concentration reached 2382 mg total solids/L. A lower Scenedesmus sp. biomass yield was obtained using digestate from anaerobic digester processing feedstock based on maize silage and cattle menure.... [more]

Compared with conventional silicon (Si)-based Pulse Width Modulation (PWM) rectifiers, PWM rectifiers based on silicon carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have significant technical advantages and broad application prospects in terms of efficiency and power density, inherited from the high-speed switching feature. However, high-speed switching also induces gate-source voltage interference, which impacts the overall character of the conversion system. This paper considered the impact of gate-source voltage interference on loss, revealing an efficiency optimization for all-SiC PWM rectifiers. Firstly, this paper theoretically investigated the mechanism of improving the conversion system efficiency by using the 4-pin Kelvin packaged SiC MOSFETs. Then, based on the industrial product case study, loss distribution, using different package styles, was quantitatively analyzed. Finally, experiment test results verified the efficiency improvement of the PW... [more]

Smart cities directly rely on a variety of elements, including water, gas, electricity, buildings, services, transportation networks, and others. Lack of properly designed transportation networks may cause different economic and safety concerns. Highway−rail grade crossings are known to be a hazardous point in the transportation network, considering a remarkable number of accidents recorded annually between highway users and trains, and even solely between highway users at highway−rail grade crossings. Hence, safety improvement at highway−rail grade crossings is a challenging issue for smart city authorities, given limitations in monetary resources. In this study, two optimization models are developed for resource allocation among highway−rail grade crossings to minimize the overall hazard and the overall hazard severity, taking into account the available budget limitations. The optimization models are solved by CPLEX to the global optimality. Moreover, some heuristic algorithms are pr... [more]

Within the United States solar energy industry, there is a general motto of “set it and forget it” with solar energy. This notion is derived from much of the research and reliability studies around the photovoltaic (PV) panels themselves, not necessarily the PV system as a whole (including the inverter and other components). This implies that maintenance and regular monitoring is not needed. Yet many things can go wrong to cause the actual performance to deviate from the expected performance. If failures and/or unanticipated degradation issues go undetected, they will lead to reduced energy generation (and associated electricity credits) and/or potential loss of component warranty because of manufacturer turnover. Given the size of the problem and gaps with current solutions, the authors propose that PV system owners need an unbiased third-party off-the-shelf system-level predictive maintenance tool to optimize return-on-investment and minimize time to warranty claim in PV installation... [more]

Due to the pressures caused by the energy crisis, environmental pollution, and international regulations, the largest ship-producing nations are exploring renewable resources, such as wind power, solar energy, and fuel cells to save energy and develop more environmentally-friendly ships. Solar energy has recently attracted a great deal of attention from both academics and practitioners; furthermore, the optimization of energy management has become a research topic of great interest. This paper takes a solar-diesel hybrid ship with 5000 car spaces as its research object. Then, following testing on this ship, experimental data were obtained, a multi-objective optimization model related to the ship’s fuel economy and diesel generator’s efficiency was established, and a partial swarm optimization algorithm was used to solve a multi-objective problem. The results show that the optimized energy management strategy for a hybrid energy system should be tested under different electrical loads.... [more]

The Sea Surface Temperature (SST) is one of the key factors affecting ocean climate change. Hence, Sea Surface Temperature Prediction (SSTP) is of great significance to the study of navigation and meteorology. However, SST data is well-known to suffer from high levels of redundant information, which makes it very difficult to realize accurate predictions, for instance when using time-series regression. This paper constructs a simple yet effective SSTP model, dubbed DSL (given its origination from methods known as DTW, SVM and LSPSO). DSL is based on time-series similarity measure, multiple pattern learning and parameter optimization. It consists of three parts: (1) using Dynamic Time Warping (DTW) to mine the similarities in historical SST series; (2) training a Support Vector Machine (SVM) using the top-k similar patterns, deriving a robust SSTP model that offers a 5-day prediction window based on multiple SST input sequences; and (3) developing an improved Particle Swarm Optimization... [more]