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control optimization and dynamic response analysis of a combined semi-submersible floating wind turbine and point-absorber wave energy converters

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OCEAN ENGINEERING 2025年 320卷

作者： Xue, Lei Sergiienko, Nataliia Y. Ding, Boyin Cazzolato, Benjamin Wei, Zhiwen Yang, Yang Cao, Feifei Shi, Hongda Xue, Yu Ocean Univ China Coll Engn Qingdao Shandong Peoples R China Univ Adelaide Sch Elect & Mech Engn Ocean Renewable Energy Res Grp Adelaide SA Australia Ningbo Univ Fac Maritime & Transportat Ningbo Zhejiang Peoples R China Ocean Univ China Shandong Prov Key Lab Ocean Engn Qingdao Shandong Peoples R China

Hybridization of a floating offshore wind turbine (FOWT) with wave energy converters (WECs) is a solution providing additional stability and energy reliability to the FOWT. This paper investigates a wind-wave hybrid energy system (WWHES) consisting of a 5-MW semi-submersible FOWT and three point-absorber WECs. The main focus is on the effects of the integrated control optimization of the FOWT and WECs on the stability, loads and power outputs of the WWHES. Numerical simulations are performed using the Coupled Analysis Tool for Integrated Floating Energy Systems. The optimization of the FOWT control is implemented in Wind Energy with an Integrated Servo-control framework to minimize tower-base fore-aft bending moment, and the WEC control parameters are optimized to maximize the WEC power production. Various combinations of FOWT and WEC control strategies are investigated in terms of platform pitch motion, tower-base fore-aft bending moment and nacelle acceleration in the fore-aft direction. The considered FOWT control strategies include: baseline controller, Reference Open-Source controller (ROSCO) optimized for the FOWT (without accounting for the presence of WECs), and ROSCO optimized for the WWHES where the platform and three WECs are included as a rigid body. The results demonstrate that the integrated control optimization benefits the WWHES by simultaneously suppressing motion and enhancing power production, although sacrificing a small portion of power under conditions very close to the rated wind speed.

关键词： Floating offshore wind turbine Wave energy converters control optimization Dynamic response Power reliability

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control Re-optimization of a Series-Parallel Hybrid Powertrain Fueled with High-Octane Gasoline

Control Re-Optimization of a Series-Parallel Hybrid Powertra...

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2024 Vehicle Powertrain Diversification Technology Forum, VPD 2024

作者： Tan, Guikun Li, Ji Li, Yanfei Wang, Changhui Sun, Yuncai Xu, Anzhao Shuai, Shijin Xu, Hongming Tsinghua University China University of Birmingham United Kingdom Shandong Chambroad New Energy Holding Development Co. Ltd. China Co. Ltd. China

High-octane gasoline has the potential to improve engine efficiency but has been reported to marginally reduce and even increase vehicle fuel consumption. The objective of this study is to evaluate the fuel-saving effect of high-octane gasoline on series-parallel hybrid electric vehicles (HEVs) under the re-optimized powertrain control, including engine control and energy management. Firstly, a bench test was conducted on a spark ignition engine fueled with three fuels with research octane numbers of approximately 92, 95, and 98, named 92#, 95#, and 98#. Then the engine control parameter (i.e., spark advance) was re-optimized for maximum engine efficiency and acceptable particle number emissions with the knock constraint. Finally, the energy management was re-optimized for a series-parallel hybrid powertrain equipped with the engine. It was found that 95# and 98# even increased vehicle fuel consumption by 0.2% and 0.6% without the re-optimization of powertrain control compared with 92#, but reduced the fuel consumption by 2.1% and 3.8% with the re-optimization. The results indicated high-octane gasoline can reduce HEV fuel consumption but requires the re-optimization of powertrain control. The engine control re-optimization for high-octane gasoline increased the maximum torque and expanded the high-efficiency area toward higher torque in the engine efficiency map. Then the energy management re-optimization shifted the engine operating points to area with higher engine efficiency and reduced powertrain operation under low-efficiency series mode. The fuel-saving analysis indicated that, under the condition of re-optimizing only the control, high-octane gasoline is suitable for application in parallel or series-parallel HEVs rather than in series HEVs. © 2025 SAE International.

关键词： control optimization energy management Hybrid electric vehicle octane number

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control optimization through simulations of large scale solar plants for industrial heat applications 3rd

Control optimization through simulations of large scale sola...

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3rd International Conference on Solar Heating and Cooling for Buildings and Industry (SHC)

作者： Ben Hassine, Ilyes Sehgelmeble, Mariela Cotrado Soell, Robert Pietruschka, Dirk Zafh Net Res Ctr Sustainable Energy Technol D-70174 Stuttgart Germany SOLID Solarinstallationen & Design GmbH A-8020 Graz Austria

The European FP7 Project InSun;which started in April 2012;aims to demonstrate the reliability and efficiency of three different collector technologies suitable for heat production employed in diverse industrial processes in different climatic regions. These collectors are installed and will be monitored in detail over a period of almost two years. One of the plants is installed at Fleischwaren Berger GmbH located in Sieghartskirchen, Austria, a company which produces meat and sausage products. The second solar plant is installed at the company Laterizi Gambettola SRL (SOLTIGUA) located in Gambettola, Italy, which produces highly insulating hollow brick blocks for external walls of buildings. The control optimization and commissioning of the two solar plants has been carried out as a part of the InSun project. Considering measurements and results of simulations developed with dynamic models, potential improvements of the low-level control algorithms are presented for the two solar plants. (C) 2015 The Authors. Published by Elsevier Ltd.

关键词： control optimization solar thermal collectors large scale solar plant solar industrial heat applications

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control optimization of combined cooling and power system with prime mover of solid oxide fuel cell-gas turbine for building application 8th

Control optimization of combined cooling and power system wi...

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8th International Conference on Applied Energy (ICAE)

作者： Luo, X. J. Fong, K. F. City Univ Hong Kong Coll Sci & Engn Dept Architecture & Civil Engn Hong Kong Hong Kong Peoples R China City Univ Hong Kong Coll Sci & Engn Div Bldg Sci & Technol Hong Kong Hong Kong Peoples R China

This paper presents a control strategy for a combined cooling and power (CCP) system using a prime mover of solid oxide fuel cell (SOFC) with bottoming cycle of gas turbine (GT) for building application. Dynamic simulation model of the CCP system was developed in TRNSYS 17, and the control strategy was developed for year-round operation in response to the changing climatic and loading conditions. The capacity ratio of cells in operation;the ratio of exhaust heat delivered to GT;and the ratio of cooling load shared between absorption and compression chillers were chosen as the decision variables in the control strategy. In order to minimize the system energy consumption, particle swarm optimization (PSO) was constructed in MATLAB and coupled with TRNSYS 17 for control optimization. It was found that with the proposed control strategy, the yearly energy saving of the SOFC-GT CCP system would be 6.89% compared to the reference case. (C) 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

关键词： SOFC Gas turbine Combined cooling and power Particle swarm optimization control optimization

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control optimization for Increasing Energy Performance of Existing Buildings 11

Control Optimization for Increasing Energy Performance of Ex...

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11th International Conference on Ecological Vehicles and Renewable Energies (EVER)

作者： Onose, Bogdan-Alexandru Icpe SA Splaiul Unirii 313 Bucharest Romania

ISBN: (纸本)9781509024643

This paper presents the objective of the Energy IN TIME (EiT) project of developing more advanced control method for existing non-residential buildings. This approach will be based on advanced building simulation models to reduce the energy consumption and energy bill. The project methodology will cover the most accurate and up to date international standards for energy efficiency. A simulation reference models will be developed with both forecasted and real time data type: external (climate, energy tariffs), internal data (status, equipment, occupancy) and user behavior data. A continuous commissioning strategy will be develop to better cope with the deviations between operational plans and real operation of the building, together with a fault detection and diagnostic system, designed for overall system robustness and evaluating faulty operation scenarios. The project goes beyond existing building control techniques by implementing a prediction system for indoor comfort conditions and used behavior performance to further improve energy efficiency and equipment lifetime. This approach will allow the reduction of system inefficiencies and therefore will contribute significantly to improve building end-user comfort. EiT will centralize the remote control of different buildings in an automatic process and validate the solution in four different locations in Europe, with different climate typologies.

关键词： building energy management system energy efficiency energy management control optimization energy performance building simulation commissioning fault diagnostic system

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Inverse response compensation and control optimization of incineration plants with energy production

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COMPUTERS & CHEMICAL ENGINEERING 1998年第12期22卷 1879-1896页

作者： Manca, D Rovaglio, M Pazzaglia, G Serafini, G Politecn Milan Dipartimento Chim Ind & Ingn Chim G Natta I-20133 Milan Italy

A detailed analysis of municipal waste incineration plant, brings to light several typical operational problems such as the inverse response of the steam flowrate produced with respect to a waste feed flowrate variation. In fact, when the waste load is increased, it is generally presumed that the steam flowrate will increase since the burnable material available has increased. However, the waste temperature and moisture content correspond to an initial heat requirement that can reduce the combustion temperature. With such behavior a simple feedback control structure generates unacceptable oscillations of the controlled variable, which seriously compromise the stability of the process itself. This paper will try to address, to discuss and to solve the inherent problems related to the synthesis of a compensation control algorithm. A design for an improved control structure will be proposed through the use of a detailed dynamic simulation model of the incineration unit. Finally, this control strategy implemented on-line in an Italian municipal waste plant, through the interaction between a personal computer and a Digital control System (DCS) device, will provide the experimental closed-loop data to be compared with the theoretical ones and will make it possible to check the robustness and the effectiveness of the proposed configuration. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

关键词： incineration plants control optimization inverse response compensation

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GRADIENT-BASED COMBINED STRUCTURAL AND control optimization

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JOURNAL OF GUIDANCE control AND DYNAMICS 1987年第3期10卷 291-298页

作者： MILLER, DF SHIM, J Wright State University Dayton Ohio

This paper considers the combined structural and control optimization problem for flexible systems. The sum of structural mass and controlled system energy terms is minimized simultaneously in structural and control parameters using gradient searches. The purpose of control is to effectively suppress structural vibrations due to initial excitations. Starting with a baseline structural design, the objectives of the combined structural/control optimization are twofold: 1) to reduce the structure's mass, and 2) to reduce total system strain, kinetic and control energies observed when the structure is excited. The appropriate weighting of energy and structural mass for balanced design and the dependence of optimal designs on initial conditions are discussed. The ideas presented are illustrated through numerical simulations using a 10-bar cantilevered truss. © 1987 American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： control optimization Trusses Structural optimization Vibration Suppression control Systems Numerical Simulation Finite Element Modeling Algebraic Riccati Equation Dynamic Response Cantilever Beam

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Reinforcement learning applied to wastewater treatment process control optimization: Approaches, challenges, and path forward

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CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2023年第20期53卷 1775-1794页

作者： Croll, Henry C. Ikuma, Kaoru Ong, Say Kee Sarkar, Soumik Iowa State Univ Dept Civil Construct & Environm Engn Ames IA 50011 USA Iowa State Univ Dept Mech Engn Ames IA USA

Wastewater treatment process control optimization is a complex task in a highly nonlinear environment. Reinforcement learning (RL) is a machine learning technique that stands out for its ability to perform better than human operators for certain high-dimensional, complex decision-making problems, making it an ideal candidate for wastewater treatment process control optimization. However, while RL control optimization strategies have shown potential to provide operational cost savings and effluent quality improvements, RL has proven slow to be adopted among environmental engineers. This review provides an overview of existing RL applications for wastewater treatment control optimization found in literature and evaluates five key challenges that must be addressed prior to widespread adoption: practical RL implementation, managing data, integrating existing process models, building trust in empirical control strategies, and bridging gaps in professional training. Finally, this review discusses potential paths forward to addressing each key challenge, including leveraging soft sensing to improve online data collection, working with process engineers to integrate RL programming with existing industry software, utilizing supervised training to build expert knowledge into the RL agent, and focusing research efforts on known scenarios such as the Benchmark Simulation Model No. 1 to build a robust database of RL agent control optimization results.

关键词： Artificial intelligence control optimization machine learning reinforcement learning wastewater treatment Hyunjung Kim and Scott Bradford

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Experimental investigation and control optimization of a ground source heat pump system

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APPLIED THERMAL ENGINEERING 2017年 127卷 70-80页

作者： Xia, Lei Ma, Zhenjun McLauchlan, Craig Wang, Shugang Univ Wollongong Sustainable Bldg Res Ctr Wollongong NSW 2522 Australia Dalian Univ Technol Fac Infrastruct Engn Dalian 116024 Peoples R China

This paper presents an experimental investigation and control optimization of a ground source heat pump (GSHP) system. A set of experimental tests was first carried out to examine the performance of the GSHP system under different ground loop differential pressure set-points and different configurations of the ground heat exchangers (GHEs). A model-based optimization strategy was then developed to determine the optimal operating speed of the variable speed pumps in the ground loop system, in which a hybrid optimization technique integrating a performance map-based near-optimal strategy and the exhaustive search method was used to search for the optimal solutions of the optimization problem. The results from the experiments showed that, for the GSHP tested, the coefficient of performance (COP) of the heat pump units increased while that of the whole GSHP system decreased with the increase of the ground loop differential pressure set-point. The GSHP system with GHEs in the parallel operation outperformed that in the series operation. Using the proposed model-based strategy, energy savings of 8.0% during the heating period, and 9.0% during the cooling period can be achieved in comparison to a rule-based strategy with two-stage control for variable speed pumps. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Experimental investigation control optimization GSHP Variable speed pumps

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Visualizing Movement control optimization Landscapes

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2022年第3期28卷 1648-1660页

作者： Hamalainen, Perttu Toikka, Juuso Babadi, Amin Liu, C. Karen Aalto Univ Dept Comp Sci Espoo 02150 Finland Stanford Univ Dept Comp Sci Stanford CA 94305 USA

A large body of animation research focuses on optimization of movement control, either as action sequences or policy parameters. However, as closed-form expressions of the objective functions are often not available, our understanding of the optimization problems is limited. Building on recent work on analyzing neural network training, we contribute novel visualizations of high-dimensional control optimization landscapes;this yields insights into why control optimization is hard and why common practices like early termination and spline-based action parameterizations make optimization easier. For example, our experiments show how trajectory optimization can become increasingly ill-conditioned with longer trajectories, but parameterizing control as partial target states-e.g., target angles converted to torques using a PD-controller-can act as an efficient preconditioner. Both our visualizations and quantitative empirical data also indicate that neural network policy optimization scales better than trajectory optimization for long planning horizons. Our work advances the understanding of movement optimization and our visualizations should also provide value in educational use.

关键词： Visualization Linear programming Animation Trajectory optimization Two dimensional displays Visualization animation movement synthesis trajectory optimization policy optimization control optimization

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