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A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems

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OPERATIONS RESEARCH 2023年第6期71卷 2015页

作者： Petra, Cosmin G. Aravena, Ignacio Lawrence Livermore Natl Lab Livermore CA 94550 USA

We present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E's Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible singleelement contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E's GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.

关键词： optimal power flow computational optimization nonlinear programming large-scale optimization

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Optimal lane-changing trajectory planning for autonomous vehicles considering energy consumption

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EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期225卷

作者： Yao, Zhihong Deng, Haowei Wu, Yunxia Zhao, Bin Li, Gen Jiang, Yangsheng Southwest Jiaotong Univ Natl Engn Lab Integrated Transportat Big Data Appl Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Natl United Engn Lab Integrated & Intelligent Tran Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 611756 Sichuan Peoples R China Xihua Univ Sch Automobile & Transportat Chengdu 610039 Sichuan Peoples R China Nanjing Forestry Univ Sch Automobile & Traff Engn Nanjing 210037 Jiangsu Peoples R China

The emerging autonomous vehicles (AVs) technologies provide a new opportunity to design a better lanechanging trajectory to reduce traffic congestion. The existing research on lane-changing trajectory planning mainly focuses on fitting trajectory curves, and the lane-changing trajectory is not optimized from the perspective of optimal control. To address this limitation, this paper proposes an optimal lane-changing trajectory planning model for AVs. First, the vehicle lane-changing process is modeled as an optimal control problem to minimize fuel consumption. The control variables are acceleration and steering angle. Second, to simplify the optimal control model, the speed and acceleration are decomposed in X and Y directions. The nonlinear constraints of the optimal control model are transformed into linear constraints. Then, we discretize the time of the optimal control model and simplify the problem into nonlinear programming (NLP). Finally, taking the NGSIM database and polynomial trajectory curve as the benchmark, we verify that the optimal lanechanging trajectory can significantly save energy consumption, with an average reduction of 37.52% and 32.48%. Sensitivity analysis indicates that (1) the minimum fuel consumption of lane-changing trajectory corresponds to optimal lane-changing duration and an optimal longitudinal displacement;(2) the more significant the speed difference (i.e., initial speed and final speed) before and after lane-changing, the greater the fuel consumption of lane-changing;(3) the fuel consumption of lane-changing increases with the increase of lateral displacement.

关键词： Lane -changing trajectory Fuel consumption Autonomous vehicles Optimal control nonlinear programming NGSIM

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Application of Fuzzy Multi-Objective programming to Regional Sewer System Planning

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PROCESSES 2023年第1期11卷 183页

作者： Huang, Chung-Fu Chen, Wei-Ting Kao, Chuan-Ksing Chang, Han-Jung Kao, Po-Min Wan, Terng-Jou Zhaoqing Univ Sch Environm & Chem Engn Zhaoqing 526061 Peoples R China Zhaoqing Univ Guangdong Prov Key Lab Environm Hlth & Land Resour Zhaoqing 526061 Peoples R China St Marys Jr Coll Med Nursing & Management Dept Cosmet Applicat & Management Yilan 26644 Taiwan Natl Yunlin Univ Sci & Technol Dept Safety Hlth & Environm Engn Yunlin 64002 Taiwan Natl Yunlin Univ Sci & Technol Ctr Green Sustainable & Innovat Yunlin 64002 Taiwan Natl Yunlin Univ Sci & Technol Bachelor Program Ind Technol Yunlin 64002 Taiwan

Planning of sewer systems typically involves limitations and problems, regardless of whether traditional planning methods or optimization models are used. Such problems include non-quantifiability, fuzzy objectives, and uncertainties in decision-making variables which are commonly applied in the planning of any process. Particularly, uncertainties have prevented the inclusion of these variables in models. Consequently, the theoretical optional solution of the mathematical models is not the true optimum solution to practical problems. In this study, to solve the above problems for regional sewer system planning, multi-objective programming (MOP), nonlinear programming, mixed-integer programming, and compromise fuzzy programming were used. The objectives of this study were two-fold: (1) determination of the necessary decision-making variables or parameters, such as the optimum number of plants, piping layout, size of the plant, and extent of treatment;(2) establishment of a framework and methodology for optimal planning for designing a regional sewer system, matching demanded targets with the lowest cost, which would achieve the aim of lower space and energy requirements as well as consumption and high treatment efficiency for the purpose of meeting effluent standards. The findings of this study revealed that individual regional sewage treatment plants could be merged to form a centralized system. Land acquisition was difficult;thus, reducing the number of plants was required. Therefore, the compromise-fuzzy-based MOP method could effectively be used to build a regional sewer system plan, and the amount of in-plant establishment reached its maximized value with a minimized cost.

关键词： regional sewer system planning multi-objective programming nonlinear programming mixed-integer programming compromise fuzzy programming

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Mathematical programming Models for Shale Oil & Gas Development: A Review and Perspective

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COMPUTERS & CHEMICAL ENGINEERING 2023年第1期177卷

作者： Drouven, Markus G. Cafaro, Diego C. Grossmann, Ignacio E. Natl Energy Technol Lab Pittsburgh PA 15236 USA Univ Nacl Litoral Santa Fe Argentina Carnegie Mellon Univ Pittsburgh PA 15213 USA

In this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.

关键词： nonlinear programming

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The relationship between environmental degradation, energy use and economic growth in Nigeria: new evidence from non-linear ARDL

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INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT 2021年第1期15卷 81-100页

作者： Musibau, Hammed Oluwaseyi Shittu, Waliu Olawale Ogunlana, Fatai Olarewaju Univ Tasmania Tasmanian Sch Econ & Business Hobart Tas Australia Univ Econ Ho Chi Minh City Vietnam Univ Sains Malaysia Sch Social Sci Gelugor Malaysia Lagos State Univ Dept Econ Lagos Nigeria

Purpose The purpose of this paper is to study the relationship among environmental degradation, energy use and economic growth, thus lending a voice to testing the relevance, or otherwise, of the environmental Kuznets curve (EKC) hypothesis in Nigeria. Design/methodology/approach The authors rely on the secondary data obtained from World Bank's World Development Indicators for Nigeria, between 1981 and 2014. The non-linear autoregressive distributed lag (ARDL) technique is used after examining the unit root properties - using the augmented Dickey-Fuller and Phillips-Perron methods - and the long-run relationship - using the ARDL bounds approach to estimate the asymmetries in the effects of economic growth on the environment. Findings The findings of this study uphold the relevance of the EKC hypothesis in Nigeria, as the growth of GDP first reduces the environmental quality but raises it over time. Furthermore, the use of energy is found to deteriorate environmental quality, given that CO2 rises by 0.002% for a unit increase in the consumption of energy in Nigeria. Research limitations/implications A limitation to this research is the data coverage, which is just between 1981 and 2014, based on availability. One other limitation is the use of electric power consumption as a proxy for energy use (because of the difficulty in obtaining accurate data on energy consumption in Nigeria). Future research should, therefore, test different other proxies, to either agree with the findings or justify any deviation therefrom. Also, the use of up-to-date data is recommended as an improvement to this study, while a non-linear technique should be used on studies involving the panel of countries. Originality/value Many studies have examined this relationship by simply taking the square of GDP as a measure of its non-linear effect on the environment. The authors are one of the first who consider the asymmetric effect of economic growth on the environment through the non-linear ARDL

关键词： Nigeria Environment Least square estimation Correlation analysis Econometric nonlinear programming Autoregressive Energy consumption Economic growth NARDL Error correction models

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Optimal energy system scheduling using a constraint-aware reinforcement learning algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期152卷

作者： Shengren, Hou Vergara, Pedro P. Duque, Edgar Mauricio Salazar Palensky, Peter Delft Univ Technol Intelligent Elect Power Grids IEPG Grp NL-2628 CD Delft Netherlands Eindhoven Univ Technol Elect Energy Syst EES Grp NL-5612 AE Eindhoven Netherlands

The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms arise as a promising solution due to their data-driven and model-free features. However, current DRL algorithms fail to enforce rigorous operational constraints (e.g., power balance, ramping up or down constraints) limiting their implementation in real systems. To overcome this, in this paper, a DRL algorithm (namely MIP-DQN) is proposed, capable of strictly enforcing all operational constraints in the action space, ensuring the feasibility of the defined schedule in real-time operation. This is done by leveraging recent optimization advances for deep neural networks (DNNs) that allow their representation as a MIP formulation, enabling further consideration of any action space constraints. Comprehensive numerical simulations show that the proposed algorithm outperforms existing state-of-the-art DRL algorithms, obtaining a lower error when compared with the optimal global solution (upper boundary) obtained after solving a mathematical programming formulation with perfect forecast information;while strictly enforcing all operational constraints (even in unseen test days).

关键词： Energy management systems Distributed energy system Safe reinforcement learning Machine learning nonlinear programming

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Strategic rearrangement of retail shelf space allocations: Using data insights to encourage impulse buying

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EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期216卷

作者： Edirisinghe, Gihan S. Munson, Charles L. Western Kentucky Univ Gordon Ford Coll Business Dept Management 1906 Coll Hts Blvd 11058 Bowling Green KY 42101 USA Washington State Univ Carson Coll Business Dept Finance & Management Sci POB 644746 Pullman WA 99164 USA

Brick-and-mortar retailers are struggling to compete with online retailers, who increasingly use customer-generated data to provide highly customized experiences for their patrons to drive impulse purchases. Although brick-and-mortar retailers cannot offer such customization, they must identify innovative ways to transform their own point-of-sale transaction data into increased customer impulse buying. We propose a shelf allocation-relocation scheme for rearranging storewide product allocations over time to maximize impulse buying behavior. The proposed method provides a roadmap for optimally allocating shelf space when routine rearrangements of a retail store take place per store policy. To the best of our knowledge, this represents one of the first periodic storewide rearrangement studies to use customer tendencies with the current shelf arrangement as the basis for the subsequent one. We also introduce a novel approach for incorporating past transaction data insights of cross-selling elasticity into the Shelf Space Allocation Problem (SSAP) to encourage long-term new business creation through impulse purchases. The method applies insights from association rule mining to group highly affine and profitable product pairs, optimize the assignment of departments to store aisles, and determine the optimal within-aisle space allocations for the products of each department. Our major finding is that, based on the potential of generating multiple forms of impulse purchasing (visibility-driven purchasing, present-shelf impulse, and past-aisle impulse), our strategic rearrangement technique consistently outperforms visually rearranging shelf space allocations and several existing allocation techniques that utilize multi-level association rule mining, while, in many instances, exceeding the profit potential of a more traditional unchanged (one-time optimal) shelf space arrangement, depending on the nature of a retailer's target market. Our results also high-light the importa

关键词： Retailing Shelf space allocation Data mining Multi-level association rules nonlinear programming Heuristics

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A Novel Optimization Method for SHEPWM-Based Depth-Focused Electromagnetic Transmitting System

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Zhang, Xinhao Pang, Xiaoyu Liu, Weiyu Yu, Shengbao Li, Gang Jilin Univ Coll Instrumentat & Elect Engn Changchun 130021 Peoples R China State Grid Jilin Elect Power Co Ltd Training Ctr Changchun 130026 Jilin Peoples R China

The towed frequency-domain electromagnetic (TFEM) detection system is an effective tool for detecting underground anomalous targets. To improve detection efficiency and measurement accuracy for specific depth targets, the depth-focused waveform with multiple probing frequencies closely spaced in the spectrum was introduced. However, the transmitting coil impedance severely suppresses the transmission energy of the excitation signal, which will reduce the transmission efficiency and signal-to-noise ratio (SNR). To solve this problem, a novel optimization method for the traditional depth-focused transmitting system is proposed to simultaneously improve the transmission energy of multiple probing frequencies in the effective band. First, the traditional depth-focused waveform is optimized with the objectives of matching the desired spectrum and maximizing the transmission energy by the nonlinear programming approach, which provides closer spectral energy between the probing frequencies and less undesired harmonic pollution. Then, we design the corresponding broadband resonant compensator based on an improved LC series resonant circuit to simultaneously enhance multiple spectral amplitudes in the effective band. Furthermore, the enhancement effect of compensator parameters on the depth-focused waveforms is analyzed, and the design principle of compensator parameters is provided. Finally, the feasibility of the proposed optimization method is verified by simulation and laboratory experiments and the actual limitation of the novel scheme is discussed in detail.

关键词： & nbsp Broadband resonant compensator depth-focused waveform nonlinear programming towed frequency-domain electromagnetic (TFEM) detection transmitting system

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Sparse Balanced Layout of Spherical Voids in Three-Dimensional Domains

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CYBERNETICS AND SYSTEMS ANALYSIS 2021年第4期57卷 542-551页

作者： Stoyan, Y. G. Romanova, T. E. Pankratov, O., V Stetsyuk, P., I Stoian, Y. E. Natl Acad Sci Ukraine A Pidhornyi Inst Mech Engn Problems Kiev Ukraine Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine

The authors consider the optimization problem of layout of spherical voids in three-dimensional domains bounded by cylindrical and spherical surfaces and planes. The problem is reduced to arranging spherical objects in a composite container, with regard for the constraints on their "sparseness" and balance conditions (location of the gravity center of the system). A mathematical model in the form of a nonlinear programming problem is constructed. A method of fast search for feasible solutions based on the balanced homothetic transformations of 3D objects and methods of finding locally optimal solutions using the decomposition algorithm and r-algorithm are proposed. The results of numerical experiments are provided.

关键词： sparse layout spherical objects phi-function nonlinear programming r-algorithm

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Analysis of the Precision of a Second-Order Conic Model to Solve the Optimal Power Dispatch Problem in Electric Power Systems

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2021年第5期32卷 1356-1364页

作者： Yamaguti, Lucas do Carmo Home-Ortiz, Juan M. Pourakbari-Kasmaei, Mahdi Sanches Mantovani, Jose Roberto Sao Paulo State Univ Dept Elect Engn Ilha Solteira SP Brazil Aalto Univ Dept Elect Engn & Automat Espoo Finland

This paper presents in-depth comparative analyses of nonlinear nonconvex programming (NLNCP) and second-order conic programming (SOCP) models to solve the optimal power flow problem in electric power systems. For comparative purposes, two objective functions are considered (1) minimization of the active power generation costs and (2) minimization of the active power losses in the transmission branches. The robustness and precision of the NLNCP and SOCP models are analyzed and discussed considering the feasibility of the active and reactive power balance constraints and the values of the objective functions. The obtained operational points are verified through the solution of the AC power flow problem using the Newton-Raphson method. For both models, numerical experiments show consistent active power dispatch;however, limit violations in the reactive power generation limits are observed in the solutions obtained by the SOCP model. To address this issue, two variations in the formulation of the SOCP model are proposed (1) considering a penalty factor in the generation of reactive energy and (2) considering a minimum resistance in branches of the power system that have resistance equal to zero. The solution of these modified SOCP models can eliminate or significantly reduce reactive power dispatch limit violations.

关键词： Convex optimization nonlinear programming Optimal active and reactive power dispatch Second-order conic programming

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