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Short-term multi-objective optimal scheduling of the integrated power grid-abandoned coal mine energy system

RESULTS IN ENGINEERING 2024年 22卷

作者： Liu, Jing Li, Rui Wu, Tao China Univ Min & Technol Beijing Sch Mech & Elect Engn Beijing 100083 Peoples R China

In order to meet the urgent needs of upgrading the coal industry, energy exploitation of abandoned coal mines which may be rich in water resources and renewable resources brooks no delay. At present, the framework design and simple energy flow analysis for the reuse of abandoned coal mine resources have been basically formed. However, profound studies on the complex interaction behavior and the coordinated optimal scheduling of the integrated power grid-abandoned coal mine energy system (IPGACMES) with distributed renewable energy and underground pumped hydro energy storage (UPHES) are still lacking. In this paper, a novel multi-objective optimal coordinated scheduling model of IPGACMES is proposed aiming to achieve the lowest operation cost and the minimal carbon emissions. Especially, load balance constraint as well as operation constraints of thermal units, wind/PV units, UPHES, power-to-gas (P2G), power to hydrogen (P2H) and hydrogen fuel cells (HFC) are all considered. Different case studies have been carried out to illustrate the feasibility and effectiveness of the presented optimal scheduling model. Better economic and environmental benefits are achieved in terms of a 3.52 % decline in operation cost and a 4.58 % reduction in carbon emissions. In addition, the renewable energy curtailment is decreased 83.7% whereby the use of P2G and P2H units.

关键词： Abandoned coal mines Integrated energy system optimization algorithm P2G/P2H Renewable energy

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Combustion system optimization for the integration of e-fuels (Oxymethylene Ether) in compression ignition engines

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FUEL 2021年 305卷 121580-121580页

作者： Novella, Ricardo Bracho, Gabriela Gomez-Soriano, Josep Fernandes, Cassio S. Lucchini, Tommaso Univ Politecn Valencia CMT Motores Term Valencia Spain Politecn Milan Milan Italy

In this study, a numerical methodology for the optimization of the combustion chamber in compression ignited engines using OME as fuel is presented. The objective is to obtain a dedicated combustion system for an engine that is fueled with this alternative fuel improving the efficiency and reducing the emissions of NOx. This article proposes the integration between thea* optimization algorithm and CFD codes to evaluate the behavior of an engine fuelled with the low sooting fuel OME. Based on a diesel model validated against experimental data, a further model for OME fuel was implemented for evaluating the performance of the engine. The particle swarm algorithm (PSO) was modified based on the Novelty Search concepts and used asa* optimization algorithm. Several tools are coupled in order to create each CFD case where all the tools anda* optimization algorithm are coupled in a routine that automates the entire process. The result is an optimized combustion system that provides an increase of the efficiency (about 2.2%) and a NOx reduction (35.7%) in comparison with the baseline engine with conventional fuel. In addition, a neuronal network was trained with all the results of all simulations performed during the optimization process, studying the influence of each parameter on the emissions and efficiency. From this analysis it was concluded that the EGR rate and injection pressure affects the NOx emissions with a range of variability of 63% and 38% respectively.

关键词： Internal combustion engines CFD codes optimization algorithm Alternative fuel OME

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Improving Courier Service Network Efficiency through Consolidations

Improving Courier Service Network Efficiency through Consoli...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Zhang, Wenxin Payan, Alexia P. Mavris, Dimitri N. Georgia Inst Technol Sch Aerosp Engn Aerosp Syst Design Lab 270 Ferst Dr Atlanta GA 30332 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

Service network design is a significant consideration for courier companies because an efficient design reduces operating costs while maintaining service quality. While companies typically rely on subject-matter experts knowledge to modify their service network design on a regular basis based on changes in demand, some of them have also developed an optimization-driven approach to improve the design of their service network in the long-term. Typically, service networks are based on a hub-and-spoke design. However, operating costs may be reduced by adding consolidations on the pickup and/or the delivery routes into and out of hubs. Consolidations are locations where packages can be aggregated from multiple spokes to go into a hub or can be disaggregated to be delivered to multiple destinations from a hub. This service network design feature ultimately reduces the number of aircraft used on each route and therefore decreases the operating costs. In this study, we use Integer Programming with hierarchical objectives to generate consolidation options. The proposed algorithm accounts for network-wide demand considerations and aims at reducing costs from operating several modes of transportation by minimizing the number of consolidation locations while ensuring that every package is served and gets delivered on time at its intended destination. The algorithm is being implemented on the entire domestic U.S. market and has the flexibility to generate one or more consolidation options for each group of packages going from a given origin to a given destination. Results from the optimization are compared to solutions from a heuristic approach based on a series of geographical and operational rules. Results show that the optimization approach is able to generate better consolidation options compared to the heuristic approach. In particular, allowing packages to consolidate at a maximum of three consolidation locations results in a two percent reduction in the total costs over i

关键词： Operating Costs Aeroplane Mathematical optimization Hub Airports optimization algorithm Aircraft Sizing

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Stability analysis of anti-dip bedding rock slopes using a limit equilibrium model combined with bi-directional evolutionary structural optimization (BESO) method

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COMPUTERS AND GEOTECHNICS 2021年 134卷 104116-104116页

作者： Liu, Tingting Ding, Luyang Meng, Fei Li, Xinping Zheng, Yun Wuhan Univ Technol Key Lab Roadway Bridge & Struct Engn Wuhan 430070 Hubei Peoples R China Chinese Acad Sci Inst Rock & Soil Mech State Key Lab Geomech & Geotech Engn Wuhan 430071 Hubei Peoples R China

Anti-dip bedding rock slope (ABRS) is a very common type of rock slopes in nature and engineering construction. However, the stability assessment of ABRSs is still a hard problem for geotechnical engineers due to the difficulty in finding the critical failure surface. In this work, a new method called LEM-BESO was proposed to tackle this problem based on limit equilibrium theory and bi-directional evolutionary structural optimization method. Two model tests reported in previous studies were employed to verify the correctness of the LEM-BESO method. Moreover, a comparative study of the LEM-BESO method and the genetic algorithm was also conducted. The highly consistent results demonstrate that using the LEM-BESO method can accurately predict the failure surface of the slope. Then, the LEM-BESO method was extended to study the influence of two key parameters (i.e. friction angle of the joints and tensile strength of the rock layers) on the failure mechanism of anti-dip bedding rock slopes. The results show that these two parameters have a significant influence on the stability of the slope. However, the failure surface is insensitive to the tensile strength of the rock layers. The LEM-BESO method provides an effective means for the stability evaluation and engineering design of ABRSs.

关键词： Anti-dip bedding rock slope (ABRS) Toppling failure Failure surface optimization algorithm Bi-directional evolutionary structural optimization (BESO)

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Self-scaling Collocation Methods Preserving Constants of Motion

Self-scaling Collocation Methods Preserving Constants of Mot...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Sagliano, Marco Hoelzel, Matthew German Aerosp Ctr GNC Dept D-28359 Bremen Germany Teraki GmbH D-10785 Berlin Germany

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

We present a class of self-scaling collocation integrators which, unlike explicit Runge-Kutta integrators, will automatically preserve quadratic constants of motion such as energy, linear momentum, and angular momentum, without the need for small stepsizes. However, collocation integrators in general require numerical optimization to solve an implicit set of equations which are difficult and computationally expensive to solve when the problem's Jacobian becomes ill-conditioned. Therefore, the integrators we present automatically scale the collocation conditions using a generalized eigenvalue problem (GEVP) approach, and exploit the Jacobian's structure to improve thea* optimization algorithm's precision and speed. Numerical results show that the presented integrators preserve invariants in a broader class of integration problems, with an improvement of approximately one order of magnitude over traditional Runge-Kutta 4(5) schemes.

关键词： Dormand Prince Method Numerical optimization optimization algorithm Runge Kutta Integration Satellites Quaternions Orbital Period Taylor Series Earth Attitude Dynamics

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Short-Term Prediction of Remaining Life for Lithium-Ion Battery Based on Adaptive Hybrid Model With Long Short-Term Memory Neural Network and Optimized Particle Filter

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JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE 2022年第3期19卷 031004-031004页

作者： He, Ning Qian, Cheng He, Lile Xian Univ Architecture & Technol Sch Mech & Elect Engn Xian 710055 Peoples R China Xi An Jiao Tong Univ Minist Educ Key Lab Intelligent Networks & Network Secur Xian 710049 Peoples R China

As an important energy storage device, lithium-ion batteries have vast applications in daily production and life. Therefore, the remaining useful life (RUL) prediction of such batteries is of great significance, which can maintain the efficacy and reliability of the system powered by lithium-ion batteries. For predicting remaining useful life of lithium-ion batteries accurately, an adaptive hybrid battery model and an improved particle filter (PF) are developed. First, the adaptive hybrid model is constructed, which is a combination of empirical model and long short-term memory (LSTM) neural network model such that it could characterize battery capacity degradation trend more effectively. In addition, the adaptive adjustment of the parameters for hybrid model is realized via optimization technique. Then, the beetle antennae search (BAS) based particle filter is applied to update the battery states offline constructed by the proposed adaptive hybrid model, which can improve the estimation accuracy. Finally, remaining useful life short-term prediction is realized online based on long short-term memory neural network rolling prediction combined historical capacity with online measurements and latest offline states and model parameters. The battery data set published by NASA is used to verify the effectiveness of proposed strategy. The experimental results indicate that the proposed adaptive hybrid model can well represent the battery degradation characteristics and have a higher accuracy compared with other models. The short-term remaining useful life prediction results have good performance with the errors of 1 cycle, 3 cycles, and 1 cycle, above results indicate proposed scheme has a good performance on short-term remaining useful life prediction.

关键词： lithium-ion battery adaptive hybrid model particle filter optimization algorithm long short-term memory neural network remaining useful life

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One Shot optimization with Generalized Constraints

One Shot Optimization with Generalized Constraints

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Munguia, Brian C. Alonso, Juan J. Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

One-shot optimization is an efficient method for simultaneously solving and optimizing a problem, such as problems in aerodynamic shape optimization. The proposed one-shot framework uses a preconditioned design update in order to ensure convergence of the coupled primal, adjoint, and design solvers. This paper builds upon previous work which applied one-shot optimization to problems with equality constraints on top of the state and co-state equations. In particular, this work proposes a one-shot optimization framework for design problems with inequality constraints.

关键词： Aerodynamic Shape optimization NACA 0012 Python optimization algorithm Turbulence Models Renewable Energy Lift Coefficient Optimal Control Aircraft Design Software Tool

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Investigating How Commercial Supersonic Aircraft Operations Might Impact Subsonic Operations and Total CO₂ Emissions

Investigating How Commercial Supersonic Aircraft Operations ...

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AIAA Aviation Forum and Exposition

作者： Jain, Samarth Mane, Muharrem Crossley, William A. DeLaurentiO, Daniel A. Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Several companies are hoping to bring back commercial supersonic aircraft operations;some have plans to introduce new supersonic aircraft in the mid-2020s. A few studies that predict the operational and environmental impacts of introducing supersonic aircraft in airline fleets exist, but-to the authors' best knowledge-none predict the effects of how operating commercial supersonic aircraft as part of an airline's fleet might alter how the airline performs subsonic operations across the network in an effort to maintain profitability. The authors believe that the airlines might consider operating high-passenger-density versions of subsonic aircraft on routes that also see supersonic operations to compensate for the shifting of some of the premium subsonic passengers to the supersonic service, and to maintain their profitability on those routes at the least. The airlinesmay also implement changes to ticket prices for subsonic flights to continue to earn similar (or even higher) profits. This paper explores the impact this approach would have on overall operations by modeling the behavior of a profit-seeking airline (with a mixture of supersonic, subsonic, and high-passenger-density subsonic aircraft in its fleet) using the Fleet-Level Environmental Evaluation Tool (FLEET). Using a set of rules to identify potential supersonic routes and supersonic passenger demand, the FLEET simulation predicts supersonic aircraft operations on profitable routes and, then, how the airline satisfies the rest of its passenger demand with the high-density versions of subsonic aircraft on routes with supersonic operations, and current standard-density subsonic aircraft on routes with no supersonic operations, for a representative day for each year over a sequence of many years. The high-density version of subsonic aircraft considers the idea of removing some of the premium class seats in the aircraft and replacing them with a larger number of economy class seats, so that the total aircraft

关键词： Supersonic Transport Aircraft Operating Empty Weight Aircraft Performance Aircraft Technology Willingness to Pay Aviation optimization algorithm Propulsive Efficiency Commercial Aviation High Ticket Prices

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Automated Design of Standard Terminal Arrival Routes

Automated Design of Standard Terminal Arrival Routes

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AIAA Aviation Forum and Exposition

作者： Taylor, Christine Coats, Paden Pusateri, Adam Barnes, W. Justin Smith, Leland Mitre Corp Mclean VA 22102 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Procedure design is a workload intensive process, relying on the experience of design specialists to collect and mentally integrate a diverse set of information to create a desirable route. While designers can leverage automation to evaluate the feasibility of a proposed design, there is little support to guide design changes if criteria failures are returned. This paper proposes an algorithmic approach for generating automated recommendations of Standard Terminal Arrival route revisions that resolve certain common criteria failures. Specifically, the algorithm generates an integrated design space - captured as a three-dimensional grid - to provide a comprehensive view of the constraints and considerations impacting a potential design. Leveraging procedural criteria, the grid is then transformed into a network, permitting fast-time computation of candidate alternatives which are subsequently evaluated for both adherence to design criteria and the trade-space of performance objectives. The approach is demonstrated on two existing procedures that contain different types of failures, and in both case studies the algorithm generates multiple failure-free options that span the trade-space of performance metrics considered. The demonstrated success of the approach highlights the viability and utility of providing automation to support the procedure design process.

关键词： Coded Instrument Flight Procedures Airspace Region Performance Based Navigation Federal Aviation Administration Minimum Obstacle Clearance Altitude En Route Automation Modernization Aeroplane Shuttle Radar Topography Mission optimization algorithm Level Flight

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optimization of the eco-friendly solvent-free microwave extraction of Limnophila aromatica essential oil

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INDUSTRIAL CROPS AND PRODUCTS 2021年 165卷 113443-113443页

作者： Yingngam, Bancha Brantner, Adelheid Treichler, Monika Brugger, Nadine Navabhatra, Abhiruj Nakonrat, Prasit Ubon Ratchathani Univ Fac Pharmaceut Sci Dept Pharmaceut Chem & Technol Ubon Ratchathani 34190 Thailand Karl Franzens Univ Graz Inst Pharmaceut Sci Dept Pharmacognosy Univ Pl 4-1 A-8010 Graz Austria Rangsit Univ Dept Pharmacol Coll Pharm Pathum Thani 12000 Thailand Ubon Ratchathani Univ Dept Elect & Elect Engn Fac Engn Ubon Ratchathani 34190 Thailand

Seasonal variation can alter the profile, quantity, and bioactivity of secondary metabolites in aromatic plants. This study aimed to establish solvent-free microwave extraction (SFME) conditions for the recovery of essential oil from Limnophila aromatica (Lam.) Merr. aerial parts and investigate the influence of seasonality on this oil. The effects of key SFME variables, including the microwave power and irradiation time, on the essential oil yield were evaluated, and these variables were optimized using response surface methodology. The chemical composition and antioxidant and antiproliferative capabilities of the essential oils obtained under the selected SFME conditions during different seasons of the year were then analyzed. The optimal SFME process conditions for achieving the maximal essential oil yield were 700 W for 25 min. The most important variable influencing oil recovery was the irradiation time (p < 0.001), followed by the microwave power (p < 0.01). The applied extraction method offered essential oil yields during the different seasons ranging from 0.20 % to 0.24 % (v/w). The obtained essential oils showed the presence of forty-seven constituents, mainly limonene, perillaldehyde, (E)-4-caranone, (Z)-4-caranone, and alpha-pinene. Monoterpene hydrocarbons were the dominant class of compounds in the oils. Seasonality affected both the antioxidant and antiproliferative properties to different degrees. These findings are not only useful for identifying eco-friendly essential oil extraction conditions but also serve as a useful guide for informing agronomic practices during the planting and cultivation of the studied medicinal plant.

关键词： Aromatic plants Essential oil Extraction conditions optimization algorithm Response surface methodology Seasonal variation

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