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Sustainable design and control of a multi-sourced radiant heating system: non-linear optimization under thermal comfort constraints

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ENERGY CONVERSION AND MANAGEMENT 2025年 326卷

作者： Anwer, Mohamed H. Hassan, Muhammed A. Kassem, Mahmoud A. Araji, Mohamad T. Cairo Univ Fac Engn Mech Power Engn Dept Giza 12613 Egypt Univ Waterloo Sch Architecture 7 Melville St S Cambridge ON N1S 2H4 Canada

The demand for energy-efficient heating solutions in buildings is increasing consistently, necessitating tools to determine the system's optimal design and operation, while ensuring occupant comfort. This study develops a novel thermal comfort-constrained capacity-operation optimization framework for a multi-source (solar collectors, a biomass boiler, and a gas boiler) radiant floor heating system, addressing the limitations of existing literature that typically focus on non-linear optimization of single-source systems. The system incorporates two forms of thermal storage, namely a water tank and a thermally active floor slab, which magnifies the system's non-linearities. Hence, a non-linear interior-point optimization algorithm (Ipopt) is implemented in MATLAB (R) to minimize lifecycle costs (LCC). Unlike conventional approaches, the developed optimization framework has three novel features: i) it captures the dynamics and complex interactions between heat generation, storage, and consumption components, ii) it constrains temperature levels to ensure energy quality while simultaneously solving thermal comfort equations at each time step, accounting for the dynamic response of the building in subsequent steps, and iii) it balances various operational and sizing decision variables, capturing the bidirectional impacts of optimal system capacity and management. The results reveal that the tri-source system achieves an LCC of approximately 0.42 mil. CAD (Canadian dollars), equivalent to 0.3 mil. USD, and a competitive levelized cost of heat (LCOH) of 0.143 CAD kWh- 1 (0.1 USD kWh- 1), maintaining a stable operative temperature between 19 degrees C and 25 degrees C, with an average predictive mean vote (PMV) of -0.12, and total lifecycle CO2 emissions of 330.15 tons. Comparative analyses with simpler design variations indicate that the gas-only system incurs the lowest LCC at 0.302 mil. CAD (0.21 mil. USD), yet its emissions are nearly twice those of the tri-source syste

关键词： Radiant heating Solar energy Thermal energy storage non-linear optimization Life cycle analysis Carbon emissions

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non-linear optimization Approach to Determine Parameters of Small Salient-pole Synchronous Machines from the Short-circuit Test

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2010年第9期38卷 1076-1096页

作者： Tu, Xiaoping Dessaint, Louis-A Champagne, Roger Al-Haddad, Kamal Univ Quebec Ecole Technol Super Dept Elect Engn Montreal PQ H3C 3P8 Canada

The sudden three-phase short-circuit test is commonly used to derive synchronous machine parameters and has been standardized by the IEEE/IEC. However, because they ignore the quadrature axis and use an envelope-tracing technique, the standard methods are inconvenient in determining the parameters of small salient-pole synchronous machines, which have strong second harmonic short-circuit current and short time constants. This article presents an alternative procedure to determine equivalent circuit parameters of small salient-pole synchronous machines from the conventional short-circuit test. The machine steady-state parameters are determined by the standard methods, while the other parameters are estimated from the machine transient short-circuit currents using a non-linear optimization approach. The parameters of the direct- and quadrature-axes are both obtained with a single test. A new state-space linear model and a transient saturation model of synchronous machines in phase quantities are developed to predict the short-circuit test. The method is successfully applied for the parameter estimation of a synchronous motor/generator of 208 V, 1.5 kVA, and 60 Hz. The estimated parameters are validated under load as well as saturation conditions.

关键词： synchronous machine parameter estimation short-circuit non-linear optimization

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non-linear optimization of biotechnological processes by stochastic algorithms:: Application to the maximization of the production rate of ethanol, glycerol and carbohydrates by Saccharomyces cerevisiae

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JOURNAL OF BIOTECHNOLOGY 1999年第1期68卷 15-28页

作者： Rodríguez-Acosta, F Regalado, CM Torres, NV Univ La Laguna Fac Biol Dept Bioquim & Biol Mol Grp Tecnol Bioquim & Control Metab La Laguna 38206 Tenerife Spain

A non-linear optimization, based on an stochastic multi-start search algorithm, has been applied to the maximization of the production rates of ethanol, glycerol and carbohydrates by Saccharomyces cerevisiae. This optimization is applied to two alternative (non-linear) model representations of the same system, namely the Michaelis-Menten and the generalized mass action forms. We find a complete agreement between the results obtained using both representations. This is, maximization of the ethanol production rate requires modulation of up to six enzymes, while modification of only one enzyme is sufficient to obtain a significant improvement in the production rate of glycerol and carbohydrates. When the results are compared with those previously obtained using an indirect linear optimization method (Torres, N.V., Volt, E.O., Gonzalez-Alcon, C., Rodriguez, F. 1997. An integrated optimization method for biochemical systems. Description of method and application to ethanol, glycerol and carbohydrate production in S. cerevisiae. Biotechnol. Bioeng. 55(5), 758-772.), we find close agreement between both optimization techniques. Qualitatively, both optimization approaches render the same profile of enzymes to be modulated, while quantitatively, discrepancies arise when the objective function is the maximization of the ethanol production rate. Reasons for such discrepancies and an evaluation of the advantages of each method (linear vs non-linear) are given. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： non-linear optimization metabolic engineering metaheuristics biotechnology Saccharomyces cerevisiae ethanol glycerol carbohydrates

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non-linear optimization of a new robotic induction process for local heat treatment using thermal finite element analysis

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2016年第5-8期84卷 1013-1029页

作者： Gendron, Mathieu Boudreault, Eric Hazel, Bruce Xuan-Tan Pham Champliaud, Henri Ecole Technol Super Dept Mech Engn Montreal PQ H3C 1K3 Canada Hydroquebecs Res Inst IREQ Dept Robot Varennes PQ J3X 1S1 Canada

Performing high-quality repair on aging hydro power equipment is a challenging issue for utilities. Weld repair deteriorates the mechanical properties of the base metal in and around the heat-affected zone. For martensitic stainless steel runners, there is no way to perform post-weld heat treatment (PWHT) on site to restore those properties without dismantling, a very expensive job for such large components, typical of power utilities. To perform in situ high-quality repairs on such components, a new robotic heat treatment process is developed. Heat is generated and controlled using a flat spiral coil mounted on a compact, portable robot and moved over the area needing heat treatment. Unlike conventional induction heating, which requires a customized coil, this new approach combines a universal coil and a flexible robot to heat a broad range of complex shapes. One critical aspect is to set heating and path parameters in order to generate a target spatial and temporal temperature field. This paper proposes a numerical method combining thermal finite element analysis and a non-linear optimization algorithm to set these parameters. The temperature resulting from the electromagnetic field induced by the coil is modeled using an average heat input source to improve computation speed. Good agreement is obtained between numerical and experimental results for PWHT under laboratory conditions.

关键词： Local heat treatment Induction heating modeling non-linear optimization Finite element analysis Robotic process Crack repairs Cavitation damage repairs Erosion damage repairs

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non-linear optimization-Based Temperature Estimation of IPMSM

Non-linear Optimization-Based Temperature Estimation of IPMS...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Sun, Le Dhale, Sumedh Nalakath, Shamsuddeen Mohamadian, Mustafa Luedtke, Daniel Preindl, Matthias Emadi, Ali Nanjing Univ Sci & Technol 200 Xiaolingwei St Nanjing 210094 Jiangsu Peoples R China McMaster Univ 1280 Main St West Hamilton ON L8S 4L8 Canada FCA US LLC 1000 Chrysler Dr Auburn Hills MI USA Columbia Univ 500 W 120th St New York NY 10027 USA

ISBN: (纸本)9781538693100

In this paper, a non-linear optimization algorithm-based temperature estimation method is presented for interior permanent magnets synchronous motor (IPMSM). Commonly the online temperature estimation scheme is realized by an abstract model with lumped-parameter thermal network. A contribution of this paper is to simplify the model by combining the thermal and loss models with essential parameters. The motor loss calibration can be avoided by this unified model. The parameters are identified by quadratic programming method. Consequently, the identified system can estimate the node temperatures online. This paper presents experimental results based on a forced-coolant IPMSM to validate the proposed method.

关键词： Interior permanent magnet synchronous motor (IPMSM) non-linear optimization system identification temperature estimation

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non-linear optimization of Business Models in the Electricity Market 1

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13th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR)

作者： De Filippo, Allegra Lombardi, Michele Milano, Michela Univ Bologna DISI Viale Risorgimento 2 I-40136 Bologna Italy

ISBN: (数字)9783319339542

ISBN: (纸本)9783319339542;9783319339535

Demand Response mechanisms and load control in the electricity market represent an important area of research at international level, and the market liberalization is opening new perspectives. This calls for the development of methodologies and tools that energy providers can use to define specific business models. In this work we develop an optimization model to provide recommendations on time-of-use based prices to providers, taking into account some key factors of the customer and market behavior. We have tested our model on data from the Italian energy market, merging statistical census and population information. The main advantage of the model is that it provides a tool for sensitivity analysis, namely for understanding the impact of economical and behavioral parameters on the consumption profiles.

关键词： non-linear optimization Demand response Tariff optimization Business model definition Customer behavior modeling

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non-linear optimization for Parameter Estimation for Flood Forecasting

Non-Linear Optimization for Parameter Estimation for Flood F...

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International Congress on Modelling and Simulation (MODSIM07)

作者： Mohssen, M. Goldsmith, M. Lincoln Univ ESDD POB 84 Lincoln 7647 New Zealand Otago Reg Council Dunedin New Zealand

ISBN: (纸本)9780975840047

Floods are the response of a catchment area to severe rainfall events. Each catchment will have its unique response which is dependent on its own characteristics and the temporal and spatial distribution of the oncoming rainfall event. A non linear optimization technique has been applied to historical data for rainfall and river flows of the Kakanui catchment in North Otago, New Zealand, to estimate the parameters of a model based on the transfer function concept. The non linear optimization is based on Powell algorithm. Powell algorithm has been widely used in the literature, and it is more efficient and faster than the Simplex method (Press et al., 1989) Observed rainfall events at two locations in the Kakanui catchment, along with the corresponding observed flows of the river have been utilized to estimate the transfer function which represents the response of the Kakanui catchment to rainfall events. An adjusted form of Philip's equation for infiltration was used to estimate the abstraction of the rainfall event and obtain the effective rainfall which will contribute to the river flow. Weighing factors were assigned to each of the rainfall sites to obtain the best fit between observed and forecasted flows. Nine flood events were used for the calibration process, while two events were utilized for the validation of the derived model. The model has 19 parameters for the transfer function, 2 parameters for the hydrologic abstractions model, and 2 parameters for the weighing factors of the rainfall sites. This results in a total of 23 parameters for the developed model. The ratio of observed cumulative rainfall at Clifton Falls to the corresponding rainfall at the Dasher for historical events is not consistent, and varies significantly from one event to another. This indicates the high variability of the spatial distribution of rainfall events over the Kakanui catchment. As these rainfall events were used in the model calibration, it was difficult to obtain the corr

关键词： Flood Forecast Flood Modelling Rainfall-Runoff non-linear optimization

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non-linear optimization Applied to Angle-of-Arrival Satellite-Based Geolocation

Non-Linear Optimization Applied to Angle-of-Arrival Satellit...

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作者： Stephen D. Hartzell Air Force Institute of Technology

学位级别：硕士

Geolocation is a common application for satellite systems. This involves estimating an object's location (herein called the subject) based on noisy satellite data. Many geolocation methods exist; however, none are tailored specifically for the unique problems faced by satellite systems. Some satellites are so far from the subject being localized that by the time the satellite receives a signal from the subject it might have moved appreciably. Furthermore, some satellites or terrestial sensors may be much closer to the subject than others. Therefore, sensors may need to be weighted based upon their distance to the subject being localized. In addition, even if a subject can be localized, the confidence in this localization may be unknown. non-linear optimization is proposed, implemented, and analyzed as a means of geolocating objects and providing confidence estimates from passive satellite line-of-sight data. non-linear optimization requires an initial estimate. This estimate is provided by a triangulation method. The non-linear optimization then improves upon this estimate iteratively by finding estimates that are more likely to have produced the observed line-of-sight measurements. The covariance matrix of the geolocation parameters being estimated is naturally produced by the optimization which provides quantified confidence in the geolocation estimate. Simulations are developed to provide a means of evaluating the performance of the non-linear optimization algorithm. It was found that non-linear optimization can reduce the average error in geolocation estimates, provide improved estimation confidence, and accurately estimate its geolocation confidence for some subjects. The results from the theoretical development of the non- linear optimization algorithm and its simulated performance is quantified and discussed.

关键词： Geolocation non-linear optimization Triangulation Line-of-Sight Angle-of-Arrival

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Determination of confidence bounds and artificial neural networks in non-linear optimization problems

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NEUROCOMPUTING 2021年 463卷 495-504页

作者： Pineda, Luis R. Serpa, Alberto L. Univ Estadual Campinas Sch Mech Engn Dept Computat Mech Bloco L BR-13083890 Campinas SP Brazil

Feedforward is a type of ANN (artificial neural network) widely used in modeling linear and non-linear systems. This type of ANN is found in system identification, system control, and optimization. In most works on optimization with ANN embedded, the purpose of the ANN is to provide a surrogate model that approximates the objective function. Since the ANN is an algorithm that is trained with an experimental/ actual data set, it is imperative to know the limits of the data set and therefore avoid the extrapolation of the ANN. This work proposes a procedure where the network model domain is limited using the Quickhull algorithm, avoiding extrapolation. Also, this procedure allows for the quantification of the accuracy in the network's predictions, while taking into account the density of the training data within the network model domain. The procedure considers four essential steps: the modeling of the objective function, the model domain determination, the application of the operational constraints, and the optimization. Two examples of optimization are solved using this procedure, where the results are assessed according to the width of the confidence bounds, measuring how far or near the actual value is. (c) 2021 Elsevier B.V. All rights reserved.

关键词： non-linear optimization Artificial neural network Surrogate model Confidence bounds Convex hull

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Elasticity imaging of biological soft tissue using a combined finite element and non-linear optimization method

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2015年第2期23卷 179-196页

作者： Fu, Y. B. Chui, C. K. Teo, C. L. Kobayashi, E. Natl Univ Singapore Dept Mech Engn Singapore 117548 Singapore Univ Tokyo Dept Precis Engn Tokyo Japan

A novel material reconstruction method combining finite element (FE)-based direct inverse method and non-linear optimization algorithm is proposed for elasticity imaging of biological soft tissue. The biological soft tissue is represented using Neo-Hookean hyperelastic model. The FE-based direct inverse method provides an estimation of material parameter distribution which serves as the initial guess of the Levenberg-Marquardt optimization algorithm. Direct calculation of Jacobian matrix is proposed to improve the computational efficiency of the combined algorithm. Computer simulation demonstrated that the material parameters of soft tissue can be determined rapidly and accurately within a small tolerance using the proposed method. Our experimental results on a human lower leg demonstrated the clinical viability of this method.

关键词： inverse problems finite element method non-linear optimization elastography 74S05 74B20 15A29

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