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A Low-Complexity Channel Estimation in Internet of Vehicles in Intelligent Transportation Systems for 5G Communication

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JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING 2023年第1期35卷 1页

作者： Yan, Lichao Zhengzhou Univ Aeronaut Sch Intelligent Engn Zhengzhou Peoples R China

The objective of utilizing mmWave/subTHz bands in next-generation wireless communications is to be achieved. Despite this, since reconfigurable intelligent surface (RIS)-assisted systems depend on the transmission channel configuration, the system architecture design, and the methods used to derive channel state information (CSI) on a base station (BS) and RIS, channel estimation continues to be the main problem with these systems. This research proposes an innovative RIS-based and compressed sensing-based channel estimation technique for the internet of vehicles. To obtain the best phase shift matrix, the communication model must first be constructed, and the angle-of-arrival and departure are utilized. Channel estimation is then performed based on the perception matrix. The training overhead and complexity of the channel estimation are reduced by considering the position information of the vehicles in the optimal phase shift matrix. Simulation results show that the proposed algorithm exhibits better channel estimation and low complexity performance compared with existing algorithms.

关键词： 5G Networks Channel Estimation Complexity Intelligent Compressed Sensing Intelligent Reflecting Surface optimization algorithm Transportation System Vehicular Communication

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HYPERVELOCITY GLIDING MANEUVERS

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JOURNAL OF AIRCRAFT 1987年第8期24卷 572-574页

作者： TAUBER, ME NASA Ames Research Center Moffett Field California

The ability to maneuver within the atmosphere during orbital return is a major advantage of high-lift vehicles. For example, a maximum lift/drag ratio of nearly 2 affords the Space Shuttle orbiter a choice of several landing sites. In addition, the Shuttle can be rolled during entry while still maintaining a shallow glide trajectory. This roll maneuver during entry reduces the descent time and, therefore, the total heat input, although the heating rate is increased. One typical measure of maneuvering capability is the maximum lateral range that a vehicle can achieve;the solution to this problem was originally given. Another important maneuver consists of performing turns that change the vehicle's heading. This paper contains a brief analysis of turning maneuvers during gliding flight, including lateral distances traversed, at velocities up to circular satellite speed.

关键词： Aerodynamic Force Lift Drag Ratio Satellites Yaw Control Flight Altitude Earth NASA Ames Research Center optimization algorithm Space Shuttle Orbiter Mathematical Models

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Hybrid fuzzy evaluation algorithm for power system protection security assessment

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 189卷 106555-106555页

作者： Meyer, Georg Janick Lorz, Tobias Wehner, Rene Jaeger, Johann Dauer, Maximilian Krebs, Rainer Friedrich Alexander Univ Erlangen Nurnberg Erlangen Germany Siemens AG Erlangen Germany

System Protection Security Assessment is an important task in modern energy grids to ensure system security at all. The assessment system is particularly challenged by multivariate grid structures caused by volatile renewable infeeds. This paper presents an innovative strategy to evaluate the protection relay coordination of system-wide power grids. A way to calculate the quality of all protection relays based on realistic simulation data and independent of the protection method was sought. The hybrid algorithm consists of two major steps. First, a systematic analysis with various fault simulations is performed and the measurement results of all relays of all simulations are used as database. Subsequently, the use of fuzzy sets allows to express the quality of each relay setting regardless of its type. Specifically developed for the use of an optimization algorithm, finally, a new protection coordination is determined for an adapted version of the IEEE 9 bus grid. The results are validated, discussed and the effectiveness of the methodology compared to conventional setting rules.

关键词： Fuzzy evaluation Relay settings optimization algorithm Protection coordination Protection security assessment

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A water quality prediction model based on variational mode decomposition and the least squares support vector machine optimized by the sparrow search algorithm (VMD-SSA-LSSVM) of the Yangtze River, China

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2021年第6期193卷 363-363页

作者： Song, Chenguang Yao, Leihua Hua, Chengya Ni, Qihang China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China

Accurate and reliable water quality forecasting is of great significance for water resource optimization and management. This study focuses on the prediction of water quality parameters such as the dissolved oxygen (DO) in a river system. The accuracy of traditional water quality prediction methods is generally low, and the prediction results have serious autocorrelation. To overcome nonstationarity, randomness, and nonlinearity of the water quality parameter data, an improved least squares support vector machine (LSSVM) model was proposed to improve the model's performance at two gaging stations, namely Panzhihua and Jiujiang, in the Yangtze River, China. In addition, a hybrid model that recruits variational mode decomposition (VMD) to denoise the input data was adopted. A novel metaheuristic optimization algorithm, the sparrow search algorithm (SSA) was also implemented to compute the optimal parameter values for the LSSVM model. To validate the proposed hybrid model, standalone LSSVM, SSA-LSSVM, VMD-LSSVM, support vector regression (SVR), as well as back propagation neural network (BPNN) were considered as the benchmark models. The results indicated that the VMD-SSA-LSSVM model exhibited the best forecasting performance among all the peer models at Panzhihua station. Furthermore, the model forecasting results applied at Jiujiang were consistent with those at Panzhihua station. This result further verified the accuracy and stability of the VMD-SSA-LSSVM model. Thus, the proposed hybrid model was effective method for forecasting nonstationary and nonlinear water quality parameter series and can be recommended as a promising model for water quality parameter forecasting.

关键词： VMD SSA LSSVM Water quality prediction optimization algorithm Hybrid model

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Aggregated Use of Energy Flexibility in Office Buildings

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ENERGIES 2023年第2期16卷 961页

作者： Patricio, Joao Tabanez Lopes, Rui Amaral Majdalani, Naim Aelenei, Daniel Martins, Joao NOVA Sch Sci & Technol P-2829516 Caparica Portugal Ctr Technol & Syst CTS UNINOVA P-2829516 Caparica Portugal Univ Lisbon IST IN Tecn Lisboa P-1049001 Lisbon Portugal

Due to climate change consequences, all Member States of the European Union signed an agreement with the goal of becoming the first society and economy with a neutral impact on the planet by 2050. The building sector is one of the highest energy consumers, using 33% of global energy production. Given the global increase for energy demand, implementing energy flexibility strategies is crucial for a better integration of renewable energy sources and a reduction of consumption peaks arising from the electrification of energy demand. The work described in this paper aims to develop an optimization algorithm to use the existing aggregated energy flexibility in office buildings to reduce both the electric energy costs of each office, considering the tariffs applied at each moment and the total power peak, aiming to reduce the entire building's cost of the contracted power, considering the Portuguese context. The obtained results conclude that it is possible to reduce both the costs associated with electric energy consumption and contracted power. Nevertheless, since the cost of contracted power has a lower impact on the overall energy bill, it is more beneficial to focus only on the reduction of costs associated with electric energy consumption in the considered case study.

关键词： energy flexibility energy management energy consumption modeling EnergyPlus optimization algorithm

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Optimized Bezier-curve-based command generation and robust inverse optimal control for attitude tracking of spacecraft

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AEROSPACE SCIENCE AND TECHNOLOGY 2022年第0期121卷 107183-107183页

作者： Wang, Peng Zhang, Xiaobing Nanjing Univ Sci & Technol Sch Energy & Power Engn Nanjing Peoples R China

In this paper we address the optimized attitude command generation and robust inverse optimal control design for the spacecraft attitude tracking with large angle slews. Firstly, with the reference attitude command described in a Bezier curve through the spherical linear interpolation, an optimized reference command is generated to meet the principles of small energy consumption and short turning time. The applied optimization combines the particle swarm optimization algorithm and genetic algorithm based on information entropy to guarantee the diversity of the population and improve the global search capabilities. Next, a robust inverse optimal control is developed for the attitude tracking of the obtained optimized reference attitude command, consisting of an inverse optimal Lyapunov approach for performance guarantee and an arctangent-based integral sliding mode control for the disturbance attenuation. A stronger generality of the control Lyapunov function is obtained for the inverse optimality. Furthermore, the developed control efforts are of smaller amplitudes due to introducing the auxiliary angular velocity for the smooth transition to the reference attitude command. Finally, simulation results are included to show the performance of the proposed scheme. (c) 2021 Elsevier Masson SAS. All rights reserved.

关键词： Attitude control Inverse optimal control optimization algorithm Bezier curve Arctangent-based sliding mode control

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Analyzing the Societal Cost of Electric Roads Compared to Batteries and Oil for All Forms of Road Transport

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ENERGIES 2022年第5期15卷 1925页

作者： Coban, Hasan Huseyin Rehman, Aysha Mohamed, Abdullah Ardahan Univ Dept Elect Engn TR-75002 Ardahan Turkey Univ Gujrat Dept Math Gujrat 50700 Pakistan Future Univ Egypt Univ Res Ctr New Cairo 11745 Egypt

This article is designed to demonstrate that electric roads are an affordable way to electrify all forms of road transport-not only cars, but also buses and trucks. Electric roads represent a way to power electric vehicles without relying solely on batteries. The idea is that when an electric vehicle reaches an electric road, it stops using power from the battery and instead uses power directly from the road itself. The primary challenge for electric vehicles is still the perception of a compromised quality of life in owning an electric vehicle due to a limited range compared with petrol and diesel cars, today. This paper introduces a new technology, currently experiencing rapid development, that can not only overcome range anxiety but make electric vehicles better, in terms of range, than petrol and diesel cars today. Furthermore, not only can this research help to arrange this, but it can also help, for the first time, to cost-effectively electrify heavy-duty transport, such as trucks and buses, which would be a huge breakthrough in terms of sustainability, as it is very important to start supplying electricity to heavy-duty vehicles. The case study provides a very hypothetical example of a trip with and without an electric road, covering a total of 26,011 km of highways and main roads. The results indicate that building electric roads is cheaper than many other alternatives. If a large battery is replaced with a smaller battery for each new vehicle sold, after 3 years, enough savings will be made to electrify all highways and main roads in Turkey. This paper can help transport operators and policymakers develop strategies to accelerate the adoption of electric vehicles by appropriately implementing electric road infrastructure.

关键词： electric road system battery-electric car electric vehicle sustainable transport profitability charging infrastructure optimization algorithm

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Optimal membership function based fuzzy proportional-integral controller for power control of molten salt breeder reactor core

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PROGRESS IN NUCLEAR ENERGY 2023年第1期161卷

作者： Acharya, Debasis Das, Dushmanta Kumar Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur India

The aim of this paper is to design an optimal membership function (MF)-based fuzzy PI (proportional integral) controller to control the core power of a nuclear reactor. The molten salt breeder reactor (MSBR) is extensively utilized for studying primary power management of nuclear reactors. Many challenges are associated with such systems, including mathematical modelling errors, parametric uncertainties, and external disturbances. Moreover, the liquid fuel used in MSBR systems makes it more challenging to design a suitable controller for the core relative power control of such systems. The conventional PI controller may not perform efficiently under such uncertainties in the MSBR system. Different types of perturbations can be handled by a fuzzy controller, if the coordination among fuzzy rules and membership functions of fuzzy variables is done accurately. The idea of this work is to optimize the settings (range and scale) of fuzzy MFs in a fuzzy base controller. The fuzzy controller will not be used directly in the system;rather, it will be used to tune a PI controller for the system where proper expert knowledge may not be available. A nonlinear dynamic acceleration coefficients -based class topper optimization (NDAC-CTO) algorithm is also developed to optimize the fuzzy membership functions. For load tracking with step disruption, the power control of the MSBR core is investigated. With the proposed controller, a significant improvement of 70 to 80 % in the settling time of the power profile of the MSBR system is achieved in comparison with the existing results.

关键词： Molten salt breeder reactor Proportional-integral control Fuzzy controller optimization algorithm

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Forecasting hydropower generation by GFDL-CM3 climate model and hybrid hydrological-Elman neural network model based on Improved Sparrow Search algorithm (ISSA)

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2021年第24期33卷 e6476-e6476页

作者： Wang, Haizhen Wu, Xuerui Gholinia, Fatemeh Inner Mongolia Univ Nationalities Coll Comp Sci & Technol Tongliao 028000 Mongolia Autono Peoples R China Chinese Acad Sci Shanghai Astron Observ Shanghai Peoples R China Univ Mohaghegh Ardabili Ardebil Ardabil Provinc Iran

One of the most sensitive factors affecting hydropower generation is climate change. The objective of this study is to forecast the hydropower generation under the influence of climate change for the next 50 years. For this purpose, the GFDL-CM3 model is used under three scenarios: RCP2.6, RCP4.5, and RCP8.5 to predict precipitation and temperature. Any change in the inlet flow to the turbine will cause changes in the hydropower output. Therefore, the more accurately the flow is estimated, the hydropower generation is forecasted more accurately. In this research, a hydrological-neural network hybrid model for flow prediction is presented in which the Improved Sparrow Search algorithm (ISSA) has been used. The results forecasting climate parameters showed that the average annual rainfall, runoff, and evaporation have a downward trend compared to the control period. The minimum and maximum annual temperatures have an increasing trend compared to the control period. To evaluate the hydropower generation Aras dam, the HEC-Ressim reservoir model is utilized. By comparing the average annual hydropower with the control period, it is known that the power generation will decrease in future years. The average annual electricity generated by hydropower under the scenario RCP2.6 and RCP4.5 and RCP8.5 in the next 50 years will decrease by approximately 3.36, 4.62, and 6.64 MW.

关键词： climate change GFDL-CM3 model hydropower generation optimization algorithm precipitation patterns

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Load Flow Assignments' Definition from Day-Ahead Electricity Market Interconnection Power Flows: A Study for Transmission Networks

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ENERGIES 2024年第6期17卷 1391页

作者： Fresia, Matteo Minetti, Manuela Procopio, Renato Bonfiglio, Andrea Lisciandrello, Giuseppe Orru, Luca Univ Genoa Dept Elect Elect Telecommun Engn & Naval Architect I-16145 Genoa Italy Terna SpA Rete Elettr Nazl I-00156 Rome Italy

The mass introduction of renewable energy sources (RESs) presents numerous challenges for transmission system operators (TSOs). The Italian TSO, Terna S.p.A., aims to assess the impact of inverter-based generation on system inertia, primary regulating energy and short-circuit power for the year 2030, characterized by a large penetration of these sources. The initial working point of the Italian transmission network has to be defined through load flow (LF) calculations before starting dynamical analyses and simulations of the power system. Terna 2030 development plan projections enable the estimation of active power generation and load for each hour of that year in each Italian market zone, as well as cross-zonal active power flows;this dataset differs from conventional LF assignments. Therefore, in order to set up a LF analysis for the characterization of the working point of the Italian transmission network, LF assignments have to be derived from the input dataset provided by Terna. For this purpose, this paper presents two methods for determining canonical LF assignments for each network bus, aligning with the available data. The methodologies are applied to a simplified model of the Italian network, but they are also valid for other transmission networks with similar topology and meet the future needs of TSOs. The methods are tested at selected hours, revealing that both approaches yield satisfactory results in terms of compliance with the hourly data provided.

关键词： transmission system grid flexibilization load flow optimization algorithm

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