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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Kumar, Partik Abhyankar, Abhijit R. Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi110016 India

ISBN: (纸本)9798350396782

Non-intrusive load monitoring (NILM) can help in assessing the energy consumption behaviour of households in a cost-efficient way. This paper proposes a mixed integer quadratic programming (MIQP) based NILM framework in which appliances are modelled through their operating states, and the NILM problem is solved for segments in the aggregated power consumption profile. The appliance operating states and the segments are obtained with the iterative K-means clustering (IKMC) algorithm and the change point detection (CPD) framework, respectively. The optimization formulation is regularised with the l1-norm based penalty term, which promotes sparsity in the appliance operating states switching vector. Case studies are performed on the AMPds, REDD and the UK-DALE datasets and the performance of the proposed NILM framework is compared with the state-of-the-art NILM models. The comparison studies show that the proposed framework is more accurate and computationally efficient than the other models, even with the low sampling rate datasets. © 2023 IEEE.

关键词： change point detection energy consumption behaviour event detection mixed integer quadratic programming Non-intrusive load monitoring

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Convex formulations for optimal selection of controlled variables and measurements using mixed integer quadratic programming

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JOURNAL OF PROCESS CONTROL 2012年第6期22卷 995-1007页

作者： Yelchuru, Ramprasad Skogestad, Sigurd Norwegian Univ Sci & Technol NTNU Dept Chem Engn N-7491 Trondheim Norway

The appropriate selection of controlled variables is important for operating a process optimally in the presence of disturbances. Self-optimizing control provides a mathematical framework for selecting the controlled variables as combinations of measurements, c = Hy, with the aim to minimize the steady state loss from optimal operation. In this paper, we present (i) a convex formulation to find the optimal combination matrix H for a given measurement set and (ii) a mixed-integer quadratic programming (MIQP) methodology to select optimal measurement subsets that result in minimal loss. The methods presented in this paper are exact for quadratic problems with linear measurement relations. The MIQP methods can handle additional structural constraints compared to the branch and bound (BAB) methods reported in literature. The MIQP methods are evaluated on a toy test problem, an evaporator example, a binary distillation column example with 41 stages and a Kaibel column with 71 stages. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Control structure selection Self-optimizing control mixed integer quadratic programming quadratic optimization Plamwide control Optimal measurement selection

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A variable selection method for soft sensor development through mixed integer quadratic programming

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2017年 167卷 85-95页

作者： Jian, Weiyu Zhu, Lingyu Xu, Zuhua Chen, Xi Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Technol Coll Chem Engn Hangzhou 310014 Zhejiang Peoples R China

Soft sensors are widely employed in industry to predict quality variables, which are difficult to measure online, by using secondary variables. To build an accurate soft sensor, a proper variable selection is critical. In this project, a method of selecting the optimal secondary variables for a soft sensor model is proposed. It is formulated as a nested optimization problem. In each iteration, a mixed integer quadratic programming (MIQP) is conducted with the Bayesian information criterion (BIC) to estimate the prediction error. A warm start (WS) technique is developed to speed up the convergence. The proposed method is evaluated using a number of instances from the UCI Machine Learning Repository. The computational results demonstrate that this method is well suited for finding the best variable subsets. The method is successfully applied to build soft sensors for an industrial distillation column. The results show that the proposed method can effectively select feature variables that will improve the model prediction performance and reduce the model complexity. Comparisons with other methods, including the traditional partial least square technique, are also presented.

关键词： Soft sensor Variable selection mixed integer quadratic programming Bayesian information criterion

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A mixed integer quadratic programming for Dynamic Economic Dispatch With Valve Point Effect

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IEEE TRANSACTIONS ON POWER SYSTEMS 2014年第5期29卷 2097-2106页

作者： Wang, M. Q. Gooi, H. B. Chen, S. X. Lu, S. Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore DNV KEMA Clean Technol Ctr Singapore Singapore Xian Jiaotong Liverpool Univ Dept Elect Suzhou Jiangsu Peoples R China

In this paper a mixed integer quadratic programming (MIQP) is proposed to solve the dynamic economic dispatch (DED) with valve-point effect (VPE) where the non-linear and non-smooth cost caused by VPE is piecewise linearized. However if the DED with VPE is directly solved by the MIQP in a single step, the optimization suffers convergence stagnancy and will run out of memory. In this paper the multi-step method, the warm start technique and the range restriction scheme are combined with the MIQP. The optimization process can then break the convergence stagnancy and the computation efficiency can be greatly improved. When the system loss is considered, the loss formula is piecewise linearized. A post-processing procedure is proposed to eliminate the approximation error caused by linearization of the loss formula. The effectiveness of the proposed method is demonstrated by seven cases and the results are compared with those obtained by the previous published methods.

关键词： Dynamic economic dispatch mixed integer quadratic programming piecewise linearization system loss valve-point effect warm start technique

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A mixed integer quadratic programming Model for Topology Identification in Distribution Network

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第1期31卷 823-824页

作者： Tian, Zhuang Wu, Wenchuan Zhang, Boming Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

This letter presents a mixed integer quadratic programming (MIQP) based topology identification model, which is suitable for radially operated distribution networks. This approach finds the topology configuration with weighted least square (WLS) of measurement residues. Validity of the proposed method is demonstrated using an IEEE 33-bus test network.

关键词： Distribution networks mixed integer quadratic programming topology identification

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Global optimization on non-convex two-way interaction truncated linear multivariate adaptive regression splines using mixed integer quadratic programming

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INFORMATION SCIENCES 2022年 597卷 38-52页

作者： Ju, Xinglong Rosenberger, Jay M. Chen, Victoria C. P. Liu, Feng Univ Oklahoma Price Coll Business Div Management Informat Syst Norman OK 73019 USA Univ Texas Arlington Dept Ind Mfg & Syst Engn Arlington TX 76019 USA Stevens Inst Technol Sch Syst & Enterprises Hoboken NJ 07030 USA

Multivariate adaptive regression splines (MARS) has been adopted as a popular surrogate function to model the unknown relationships between input and output variables in complex systems. Searching optimal solutions on the complicated surrogate response surface of MARS serves as important tasks in various applications. In this paper, we present an efficient and effective approach to find a global optimal value of MARS models that incorporate two-way interaction terms which are products of truncated linear univariate functions (TITL-MARS). Specifically, with a MARS model consisting of linear and quadratic structures, we can reformulate the optimization problem on TITL-MARS into a mixed integer quadratic programming problem (TITL-MARS-OPT), which can be further solved in a more principled way. To illustrate the effectiveness of our proposed approach TITLMARS-OPT, we come up with a genetic algorithm and a gradient descent algorithm to solve the original version of TITL-MARS, and we compared the performance of the proposed approach with the benchmark algorithms. Numerical experiments are conducted on a spectrum of examples with different levels of complexity, including 6 existing models and a real world application in the wind farm optimization. Our proposed approach can find a global optimal successfully and efficiently while the comparison algorithms fail to find a global optimal solution. In the end, Python code for TITL-MARS and TITL-MARSOPT is made available on GitHub( https://***/JuXinglong/TITL-MARS-OPT). (c) 2022 Elsevier Inc. All rights reserved.

关键词： Genetic algorithm Global optimization mixed integer quadratic programming Multivariate adaptive regression splines Gradient descent algorithm

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An approximation algorithm for indefinite mixed integer quadratic programming

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MATHEMATICAL programming 2023年第1-2期201卷 263-293页

作者： Del Pia, Alberto Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA Univ Wisconsin Wisconsin Inst Discovery Madison WI 53706 USA

In this paper, we give an algorithm that finds an e-approximate solution to a mixed integer quadratic programming (MIQP) problem. The algorithm runs in polynomial time if the rank of the quadratic function and the number of integer variables are fixed. The running time of the algorithm is expected unless P=NP. In order to design this algorithm we introduce the novel concepts of spherical form MIQP and of aligned vectors, and we provide a number of results of independent interest. In particular, we give a strongly polynomial algorithm to find a symmetric decomposition of a matrix, and show a related result on simultaneous diagonalization of matrices.

关键词： mixed integer quadratic programming Approximation algorithm Polynomial time Symmetric decomposition Simultaneous diagonalization

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A mixed integer quadratic programming formulation for the economic dispatch of generators with prohibited operating zones

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ELECTRIC POWER SYSTEMS RESEARCH 2007年第10期77卷 1292-1296页

作者： Papageorgiou, Lazaros G. Fraga, Eric S. UCL Ctr Proc Syst Engn Dept Chem Engn London WC1E 7JE England

In this paper, an optimisation-based approach is proposed using a mixed integer quadratic programming model for the economic dispatch of electrical power generators with prohibited zones of operation. The main advantage of the proposed approach is its capability to solve case studies from the literature to global optimality quickly and without any targeting of solution procedures. (c) 2006 Elsevier B.V. All rights reserved.

关键词： economic dispatch power generation mixed integer quadratic programming optimisation

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Identification of Network Parameter and Measurement Errors based on a mixed integer quadratic programming Model

Identification of Network Parameter and Measurement Errors b...

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IEEE Power-and-Energy-Society Innovative Smart Grid Technologies Conference (ISGT)

作者： Hou, Fangdi Guo, Ruipeng Yu, Xiuyue Wang, Liangyuan Zhejiang Univ Coll Elect Engn Hangzhou Zhejiang Peoples R China State Grids Fujian Elect Power Co Operat Dept Fuzhou Peoples R China

ISBN: (纸本)9781509051670

This paper investigates identification of parameter and measurement errors in the power network model. A mixed integer quadratic programming (MIQP) model is proposed in this paper to precisely identify multiple parameter and measurement errors. In the proposed MIQP model, erroneous parameters and measurements are involved with penalty factor in the aim of minimizing weighted least-squares (WLS) objective function. The proposed method has the desired property of accurate identification with avoiding over identification in the meantime. Parameter and measurement errors can also be distinguished simultaneously in MIQP model. All these features are verified via simulations that are carried out on IEEE 14-bus system.

关键词： mixed integer quadratic programming Measurement errors Parameter errors Parameter identification State estimation

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Trajectory Optimization for Freight Train with Section Time Constraints Using mixed integer quadratic programming 17

Trajectory Optimization for Freight Train with Section Time ...

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17th Conference on Industrial Electronics and Applications (ICIEA)

作者： Su Mingliang Ning Xingliang Zhang Zipei Sun Pengfei Wang Qingyuan Bai Baoxue China Energy Investment Co Ltd Shuohuang Railway Dev Co Ltd Suning Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

ISBN: (纸本)9781665409841

There are section time constraints (STC) between adjacent stations, which has limitations for the train control. In this paper, train trajectory optimization problem with STC is solved by mixed integer quadratic programming (MIQP). Nonlinear time constraints are linear approximated with logic variables and auxiliary real variables. mixed integer quadratic programming model is constructed to solve the problem. Real case study with real data is applied to simulation to verify the effectiveness of the optimization method. Simulation results indicates that the proposed method can achieve 21.2% energy saving than the practical driver control.

关键词： Freight train mixed integer quadratic programming train control

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