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Layout and size optimization of sanitary sewer network using intelligent ants

ADVANCES IN ENGINEERING SOFTWARE 2012年 51卷 49-62页

作者： Moeini, R. Afshar, M. H. Iran Univ Sci & Technol Sch Civil Engn Envirohydroinformat Ctr Excellence Tehran Iran

The incremental solution building capability of ant algorithm is exploited in this paper for the efficient layout and pipe size optimization of sanitary sewer network. Layout and pipe size optimization of sewer networks requires that the pipe locations, pipe diameters and pipe slopes are optimally determined. This problem is a highly constrained mixed-integer nonlinear programming (MINLP) problem presenting a challenge even to the modern heuristic search methods. In this paper, the Ant Colony Optimization Algorithm (ACOA) is equipped with a Tree Growing Algorithm (TGA) to efficiently solve the sewer network layout and size optimization problem and its performance is compared with the conventional application of the ACOA. The method is based on the assumption that a base layout including all possible links of the network is available. The TGA is used to construct feasible tree-like layouts out of the base layout defined for the sewer network, while the ACOA is used to optimally determine the pipe diameters of the constructed layout. An assumption of sewer flow at maximum allowable relative depth is made allowing for the calculation of the optimal pipe slopes in the absence of any pump and drop in the network. Two different formulations are, therefore, proposed and their performances are tested against hypothetical problems. In the first formulation, ACOA is used in a conventional manner for pipe size optimization while an ad hoc engineering concept for the layout determination. In the second formulation, however. ACOA equipped with TGA is used to simultaneously determine both the layout and pipe sizes of the network. Proposed formulations are used to solve three hypothetical test examples of different scales and the results are presented and compared. The results indicate the ability of the proposed method to optimally solve the problem of layout and size determination of sewer networks. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Ant Colony Optimization Algorithm Tree Growing Algorithm Sanitary sewer network Layout Pipe size mixed-integer nonlinear programming

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New algorithms for nonlinear generalized disjunctive programming

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COMPUTERS & CHEMICAL ENGINEERING 2000年第9-10期24卷 2125-2141页

作者： Lee, S Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

Generalized disjunctive programming (GDP) has been introduced recently as an alternative model to MINLP for representing discrete/continuous optimization problems. The basic idea of GDP consists of representing discrete decisions in the continuous space with disjunctions, and constraints in the discrete space with logic propositions. In this paper, we describe a new convex nonlinear relaxation of the nonlinear GDP problem that relies on the use of the convex hull of each of the disjunctions involving nonlinear inequalities. The proposed nonlinear relaxation is used to reformulate the GDP problem as a tight MINLP problem, and for deriving a branch and bound method. Properties of these methods are given, and the relation of this method with the logic based outer-approximation method is established. Numerical results are presented for problems in jobshop scheduling synthesis of process networks, optimal positioning of new products and batch process design. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： generalized disjunctive programming branch and bound mixed-integer nonlinear programming nonlinear convex hull

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Modeling issues and implementation of language for disjunctive programming

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COMPUTERS & CHEMICAL ENGINEERING 2000年第9-10期24卷 2143-2155页

作者： Vecchietti, A Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA UTN Fac Reg Santa Fe INGAR Inst Desarrollo & Diseno Santa Fe NM USA

This paper describes a number of key modeling issues for the development of tools for solving nonlinear discrete/continuous problems where logic/disjunctive constraints are included in the formulation. A generalized hybrid representation of these problems is presented. A comparison between Constraint logic programming (CLP) and generalized disjunctive programming (GDP) is established together with several constraint transformations from CLP to GDP. The components and expressions of a modeling language for setting up disjunctions and logic constraints are proposed. The language allows the specification of problems with complex logic formulations. A parser is developed for the analysis and translation of the logic sentences into files ready to be used by the solvers. An overview of the solution algorithms is also given together with several aspects about the implementation as a superset of GAMS mathematical programming language. Examples illustrating the capabilities of the proposed system are described. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： generalized disjunctive programming mixed-integer nonlinear programming constraint logic programming modeling language

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Efficient Parasitic-aware gm/ID-based Hybrid Sizing Methodology for Analog and RF Integrated Circuits

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ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 2021年第2期26卷 1-31页

作者： Liao, Tuotian Zhang, Lihong Mem Univ Newfoundland Fac Engn & Appl Sci Dept Elect & Comp Engn St John NF A1B 3X5 Canada

As the primary second-order effect, parasitic issues have to be seriously addressed when synthesizing high-performance analog and RF integrated circuits (ICs). In this article, a two-phase hybrid sizing methodology for analog and RF ICs is proposed to take into account parasitic effect in the early design stage. It involves symbolic modeling and mixed-integer nonlinear programming (MINLP) in the first phase, and a many-objective evolutionary algorithm (many-OEA)-based sizing refiner in the second phase. With the aid of our proposed current density factor and piecewise curve fitting technique, the g(m)/I-D concept, which is typically utilized to solve the analog circuit design problem, can provide theoretical support to our accurate symbolic modeling. Thus, the intrinsic and interconnect parasitics can be accurately considered in our work with moderate modeling effort. A variety of electrical, geometric, and parasitic (including parasitic mismatch) constraints can be conveniently integrated into our MINLP problem formulation. Moreover, numerical simulations are embedded into the many-OEA-based sizing phase, which is able to tackle floorplan co-optimization. With such dynamic floorplan variation, the parasitics accuracy can be sustained along the evolution. The experimental results demonstrate high efficacy of our proposed parasitic-aware hybrid sizing methodology.

关键词： Analog and RF ICs circuit sizing circuit modeling floorplan optimization g(m)/I-D many-objective evolutionary algorithm mixed-integer nonlinear programming parasitic modeling

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Experimental validation of a real time energy management system for microgrids in islanded mode using a local day-ahead electricity market and MINLP

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ENERGY CONVERSION AND MANAGEMENT 2013年 76卷 314-322页

作者： Marzband, Mousa Sumper, Andreas Dominguez-Garcia, Jose Luis Gumara-Ferret, Ramon Catalonia Inst Energy Res IREC Barcelona Spain UPC EU Engn Tecn Ind Barcelona CITCEA UPC Dept Engn Elect Barcelona 08036 Spain Univ Politecn Cataluna EIS Engn Ind Barcelona Dept Engn Elect Ctr Innovacio Tecnol Convertidors Estat & Acciona E-08028 Barcelona Spain

Energy management systems (EMS) are vital supervisory control tools used to optimally operate and schedule Microgrids (MG). In this paper, an EMS algorithm based on mixed-integer nonlinear programming (MINLP) is presented for MG in islanding mode considering different scenarios. A local energy market (LEM) is also proposed with in this EMS to obtain the cheapest price, maximizing the utilization of distributed energy resources. The proposed energy management is based on LEM and allows scheduling the MG generation with minimum information shared sent by generation units. Load demand management is carried out by demand response concept to improve reliability and efficiency as well as to reduce the total cost of energy (COE). Simulations are performed with real data to test the performance and accuracy of the proposed algorithm. The proposed algorithm is experimentally tested to evaluate processing speed as well as to validate the results obtained from the simulation setup on a real MG Testbed. The results of the EMS-MINLP based on LEM are compared with a conventional EMS based on LEM. Simulation and experimental results show the effectiveness of the proposed algorithm which provides a reduction of 15% in COE, in comparison with conventional EMS. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Day-ahead market Energy management system Local energy market Single side auction Microgrid mixed-integer nonlinear programming Optimal scheduling and operation

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Optimal Power Flow Problem Solution Through a Matheuristic Approach

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IEEE ACCESS 2021年 9卷 84576-84587页

作者： Home-Ortiz, Juan M. Claro De Oliveira, Wmerson Sanches Mantovani, Jose Roberto Sao Paulo State Univ Dept Elect Engn BR-15385000 Ilha Solteira Brazil

The optimal power flow (OPF) problem is a widely studied subject in the literature that has been solved through classical and metaheuristic optimization techniques. Nowadays, significant advances in computational resources and commercial optimization solvers allow solving complex optimization problems by combining the best of both worlds in approaches that are known as matheuristics, however, in order to solve the OPF problem, matheuristic approaches have been little explored. In this regard, this paper presents a novel Variable Neighborhood Descent (VND) matheuristic approach to solve the OPF problem for large-scale systems. The proposed algorithm combines the classic OPF model and the VND heuristic algorithm. The OPF problem is formulated as a mixed-integer nonlinear programming (MINLP) model, in which the objective function aims to minimize the fuel generation costs, subject to the physical and operational constraints of the power system. The integer variables of this MINLP model represent the control of taps positions of the on-load tap changers and the reactive shunt compensation equipment. To validate the proposed methodology, 17 power systems of specialized literature were tested with sizes from 14 to 4661 buses, and the obtained solutions are compared with the solutions provided by the commercial optimization solver Knitro. Results show the superiority of the proposed matheuristic algorithm compared with Knitro to solve the MINLP-OPF model for large-scale systems.

关键词： Matheuristic optimization mixed-integer nonlinear programming optimal power flow variable neighborhood search

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MILP model for integrated expansion planning of multi-carrier active energy systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第7期13卷 1177-1189页

作者： Ghasemi, Hosein Aghaei, Jamshid Gharehpetian, Gevork Babamalek Safdarian, Amir Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Amirkabir Univ Technol Elect Engn Dept Tehran Iran Sharif Univ Technol Elect Engn Dept Tehran Iran

In growing economic energy systems, the interdependency of various energy infrastructures has led to a change in countries' policies in their expansion planning of energy networks. In this study, a mixed-integer non-linear programming (MINLP) model is proposed for expansion planning of the multi-carrier systems including electricity and gas distribution networks. The optimal planning determines the best location, time, and alternative for network assets in order to minimise investment costs and reduce losses. Also, as another distinctive feature of this study, given the integration of electricity and gas distribution networks and the complexity of the problem, a new MILP model using linearisation methods is presented. In this planning model, several types of alternative plans and a set of candidates for the new placements or increase of the capacity of transformers, feeders, distributed generation, gas pipelines, and city gate stations are considered. The proposed MILP model provides the convergence of the problem to a global optimum response using the powerful commercial software. In addition, a solution based on Benders decomposition algorithm is finally proposed to reduce the solution time of the problem. Finally, the efficiency of the proposed model is evaluated by means of some simulation results.

关键词： natural gas technology investment power generation planning distribution networks integer programming power transmission planning pipelines linear programming nonlinear programming energy infrastructures countries energy networks mixed-integer nonlinear programming gas distribution networks optimal planning network assets electricity MILP model planning model alternative plans distributed generation gas pipelines integrated expansion planning multicarrier active energy systems economic energy systems

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Computer-Aided Design of Ionic Liquids as Solvents for Extractive Desulfurization

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AICHE JOURNAL 2018年第3期64卷 1013-1025页

作者： Song, Zhen Zhang, Chenyue Qi, Zhiwen Zhou, Teng Sundmacher, Kai East China Univ Sci & Technol Sch Chem Engn State Key Lab Chem Engn Max Planck Partner Grp Shanghai 200237 Peoples R China Max Planck Inst Dynam Complex Tech Syst Proc Syst Engn Sandtorstr 1 D-39106 Magdeburg Germany Otto von Guericke Univ Proc Syst Engn Univ Pl 2 D-39106 Magdeburg Germany

Although ionic liquids (ILs) have been widely explored as solvents for extractive desulfurization (EDS) of fuel oils, systematic studying of the optimal design of ILs for this process is still scarce. The UNIFAC-IL model is extended first to describe the EDS system based on exhaustive experimental data. Then, based on the obtained UNIFAC-IL model and group contribution models for predicting the melting point and viscosity of ILs, a mixed-integer nonlinear programming (MINLP) problem is formulated for the purpose of computer-aided ionic liquid design (CAILD). The MINLP problem is solved to optimize the liquid-liquid extraction performance of ILs in a given multicomponent model EDS system, under consideration of constraints regarding the IL structure, thermodynamic and physical properties. The top five IL candidates preidentified from CAILD are further evaluated by means of process simulation using ASPEN Plus. Thereby, [C5MPy][C(CN)(3)] is identified as the most suitable solvent for EDS. (c) 2017 American Institute of Chemical Engineers

关键词： ionic liquid design extractive desulfurization UNIFAC-IL mixed-integer nonlinear programming process simulation

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A Novel Approximation of Security-Constrained Optimal Power Flow With Incorporation of Generator Frequency and Voltage Control Response

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第3期36卷 2438-2447页

作者： Avramidis, Iason-Iraklis Capitanescu, Florin Karagiannopoulos, Stavros Vrettos, Evangelos Luxembourg Inst Sci & Technol LIST L-4422 Belvaux Luxembourg Swissgrid CH-5001 Aarau Switzerland

This paper tackles key industry needs in the scope of the AC Security-Constrained Optimal Power Flow (SCOPF) framework, specifically two major challenging requirements regarding generators' post-contingency behavior: the (droop-based) frequency response and the voltage control mechanism (including PV/PQ switching). To this end, and to obtain a sufficiently accurate solution with a reasonable computational burden, we propose an approximation approach to SCOPF which extends significantly an existing algorithm with novel modelling elements: a continuous formulation to model generators' post-contingency responses based on successive approximations, a technique to evaluate the viability of contingencies with respect to the base case set-points, and the complexity reduction of all post-contingency states through network compression and power flow piecewise linearization. All new features are validated both separately and in unison, to monitor the improvement of the solution time and the potential degradation of the solution's quality. The proposed approach is successfully applied to three power system network models, the largest of which consists of 2,000 buses and more than 3,000 contingencies. Finally, the trade-off between the limitations in terms of solution quality and the benefits in terms of computational effort are assessed for all proposed approximations.

关键词： Generators Reactive power Voltage control Mathematical model Switches Computational modeling Frequency control Contingency filtering generator contingency response mixed-integer nonlinear programming network compression security-constrained optimal power flow

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Optimal synthesis of work and heat exchangers networks considering unclassified process streams at sub and above-ambient conditions

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APPLIED ENERGY 2018年 224卷 567-581页

作者： Onishi, Viviani C. Quirante, Natalia Ravagnani, Mauro A. S. S. Caballero, Jose A. Univ Coimbra Dept Elect & Comp Engn Polo 2 P-3030290 Coimbra Portugal Inst Syst Engn & Comp Coimbra INESC Coimbra Polo 2 P-3030290 Coimbra Portugal Univ Alicante Dept Chem Engn Ap Correos 99 E-03080 Alicante Spain Univ Estadual Maringa Dept Chem Engn Ave Colombo 5790 BR-87020900 Maringa PR Brazil

Work and heat exchanger networks have recently drawn increasing attention due to their paramount importance in achieving energy savings. In this work, we introduce a new optimization model for the cost-effective synthesis and energy integration of work and heat exchanger networks considering unclassified process streams (ie., streams whose classification as hot or cold streams cannot be defined a priori). Our innovative modelling approach combines mathematical programming techniques and the pinch location method to obtain an optimal network design with minimal cost, while adjusting pressure and temperature levels of unclassified streams. We propose disjunctive operators for the selection of pressure manipulation equipment, and streams identity classification depending on energy requirements and process operating conditions. In addition, our approach addresses previous shortcomings by eliminating the need for: (i) assigning a specific route of pressure manipulation;and, (ii) classifying streams as low or high-pressure streams;which provides further flexibility to the system. Our methodology is also able to effectively deal with variable inlet and outlet streams temperatures to reach specific optimization goals. The model is solved to global optimality through the minimization of the process total annualized cost. Besides improved computational performance, results from energy analyses reveal that streams classification during process optimization can be greatly advantageous for both subambient and above-ambient applications. In the liquefied natural gas process, it reduces up to 89% the energy demand when compared to literature records.

关键词： Simultaneous optimization Generalized disjunctive programming mixed-integer nonlinear programming Work and heat integration Pinch location method Variable temperatures

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