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31st Australasian Universities Power Engineering Conference (AUPEC)

作者： Fang, Yingjia Xiong, Binyu Qin, Kun Li, Yang Tang, Jinrui Wang, Zhenzhe Wuhan Univ Technol Sch Automat Wuhan Peoples R China State Grid Wuhan Elect Power Supply Co Dept Operat Maintenance Wuhan Peoples R China

ISBN: (纸本)9781665434515

The development of the smart grid promotes the rapid development of distributed generation (DG), while the intermittent nature of DG and the growing demand for electricity make it difficult for the grid to maintain the reliability and stability of the grid. Moreover, the time interval between peak demand of electricity usually differs from the peak supply provided by DG, which creates a mismatch between supply and demand. An energy storage system (ESS) can be an effective solution to improve the self-consumption of electricity generated by DG. In this paper, an optimization strategy of household energy management based on DG and ESS is proposed, which makes full use of the rechargeable characteristics of ESS and EV to improve the economy and flexibility of the system in the case of uncertain output prediction of DG. The objective is to minimize the cost of electricity consumption and user comfort. The actual situation of the users is taken into account, as well as the integration of renewable energy, energy storage, demand response, and other new technologies in the smart grid. Finally, the effectiveness of the proposed model and algorithm is verified by multi-scenario analysis.

关键词： home energy management system distributed generation energy storage system electric vehicle mixed-integer linear programming

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An MILP Approach to Scheduling of Expansion and Maintenance Measures in Electrical Transmission Grids 56

An MILP Approach to Scheduling of Expansion and Maintenance ...

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56th International Universities Power Engineering Conference (UPEC) - Powering Net Zero Emissions

作者： Schrief, Alexander B. Sander, Miriam Franken, Marco Moser, Albert Rhein Westfal TH Aachen Inst High Voltage Equipment & Grids Digitalizat & Aachen Germany

ISBN: (纸本)9781665443890

The increasing share of generation based on renewable energy sources and the resulting demand for transport capacities make grid expansion necessary. In order to conduct structural measures on the transmission grid, in many cases, the corresponding transmission lines need to be shut down. Measures include grid expansion and maintenance, with the completion of expansion measures changing the topology of the grid and allowing additional operational degrees of freedom. This contribution presents a novel approach based on mixed-integer linear programming to scheduling grid expansion and maintenance measures while optimizing grid operation. The method is applied to a synthetic 120-bus test system and the results show that suitable schedules can be obtained.

关键词： Power system planning Power system security Scheduling mixed-integer linear programming

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Multi-agent capacitated scheduling for profit-maximizing using a decomposition-based branch and cut algorithm

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2021年第2期16卷 73-82页

作者： Behnamian, J. Bu Ali Sina Univ Fac Engn Dept Ind Engn Hamadan Hamadan Iran

This paper considers a distributed production network scheduling that involves heterogeneous factories with the parallel machine. Although, each factory has its own local customers as a production agent, for better load balancing of machines in the production network, the jobs can transfer among factories. In order to make the problem more realistic, in addition to considering the ability of factories in processing of jobs, the capacity constraints of factories are also included in the scheduling. The aim of this paper is to maximize the profits of jobs such that each job is assigned to precisely one factory subject to their deadlines. To solve this problem, based on the decomposition algorithm, for the first time, an efficient decomposition-based branch and cut algorithm is designed. In this regard, first, the problem is formulated as a mixed-integer linear program (MILP), then using the Benders decomposition structure and after reformulating as an assignment subproblem and single factory scheduling subproblems, a branch and cut algorithm is proposed. Finally, the obtained results of the proposed algorithm, the original MILP, and non-cooperative local scheduling, all solved by CPLEX, are compared.

关键词： Scheduling distributed production network branch and cut mixed-integer linear programming production profits

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Small-scale LNG supply chain optimization for LNG bunkering in Turkey

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COMPUTERS & CHEMICAL ENGINEERING 2022年 162卷

作者： Doymus, Mehmet Sakar, Gul Denktas Yildiz, Seyda Topaloglu Acik, Abdullah Dokuz Eylul Univ Maritime Fac Dept Marine Transportat Engn Tinaztepe Campus TR-35390 Izmir Turkey Dokuz Eylul Univ Maritime Fac Dept Logist Management Tinaztepe Campus TR-35390 Izmir Turkey Dokuz Eylul Univ Engn Fac Dept Ind Engn Tinaztepe Campus TR-35390 Izmir Turkey Dokuz Eylul Univ Maritime Fac Dept Maritime Business & Adm Tinaztepe Campus TR-35390 Izmir Turkey

LNG (Liquefied Natural Gas) provides a viable option to comply with emission control measures as an alternative marine fuel. Supply chain optimization is critical for LNG bunkering development in the mar-itime context as it requires high capital-expenditure. This study proposes a model for optimizing the ship-to-ship LNG bunkering supply chain. The related problem is defined as a Multiple Period Maritime Fleet Size and Routing Problem. The proposed mathematical model has been solved for various demand scenarios obtained by multiple regression and forecasting as a case study of ship-to-ship LNG bunker deliveries in Turkey. The model presents an optimal solution as a tactical and strategic decision-making tool, finds the number and size of the LNG bunker barges and the optimum allocation of the barges and the distribution network within a ship-to-ship bunkering framework. Moreover, it provides a commercial framework for shipowners and suppliers by determining the breakeven point for investment decisions.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Small-scale LNG LNG bunkering LNG as a marine fuel Forecasting Optimization mixed-integer linear programming

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Integrated production and distribution planning for industrial gases supply chains

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COMPUTERS & CHEMICAL ENGINEERING 2022年 161卷

作者： Neiro, Sergio M. S. Madan, Tarun Pinto, Jose M. Maravelias, Christos T. Uberlandia Fed Univ UFU Sch Chem Engn Av Joao Naves de Avila 2121Bloco 5K BR-38408100 Uberlandia MG Brazil Linde PLC Linde Digital Amer Danbury CT 06810 USA Princeton Univ Dept Chem & Biol Engn Princeton NJ USA Princeton Univ Andlinger Ctr Energy & Environm Princeton NJ USA

A challenge in planning the operations of multisite production networks is the need to simultaneously balance production across sites while satisfying customers demand and keeping customer service levels high and overall costs low. Accordingly, we present a planning approach for the simultaneous optimization of production and distribution operations. Specifically, we consider a regional Argon supply chain, comprised of multiple production sites and customers, in which liquid Argon is distributed through tanker trucks under cryogenic conditions. The proposed approach first generates detailed routes and then uses these routes in an integrated model to fully optimize production and distribution. Using a series of case studies, based on industrially inspired data, we show that the proposed approach leads to high quality results for regional networks of real-world sizes.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Coordinated production-distribution plan Inventory routing mixed-integer linear programming Decomposition Industrial gases

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Zonal-Based Optimal Microgrids Identification

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ENERGIES 2022年第7期15卷 2446-2446页

作者： Albaker, Abdullah Alturki, Mansoor Abbassi, Rabeh Alqunun, Khalid Univ Hail Coll Engn Dept Elect Engn Hail 81451 Saudi Arabia

Even though many studies have been deployed to determine the optimal planning and operation of microgrids, limited research was discussed to determine the optimal microgrids' geographical boundaries. This paper proposes a zonal-based optimal microgrid identification model aiming at identifying the optimal microgrids topology in the current distribution systems through zoning the network into several clusters. In addition, the proposed model was developed as a mixed-integer linear programming (MILP) problem that identifies the optimal capacity and location of installing distributed energy resources (DERs), including but not limited to renewable energy resources and Battery Energy Storage Systems (BESS), within the determined microgrid's boundaries. Moreover, it investigates the impact of incorporating the BESS in boosting the DERs' penetration on the optimal centralized microgrid. Numerical simulations on the IEEE-33 bus test system demonstrate the features and effectiveness of the proposed model on identifying the optimal microgrid geographical boundaries on current distribution grids as well as its capability on defining the optimal sizes and locations of installing DERs within the microgrid's zonal area.

关键词： battery energy storage system (BESS) distributed energy resources (DERs) microgrids topology mixed-integer linear programming optimization

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Evolutionary neural network for learning of scalable heuristics for pickup and delivery problems with time windows

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年第0期169卷

作者： Jun, Sungbum Lee, Seokcheon Dongguk Univ Dept Ind & Syst Engn Seoul 04620 South Korea Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

In this paper, we address the pickup and delivery problem with time windows (PDP-TW) and heterogenous vehicles for minimisation of total tardiness by learning heuristics from a given set of solutions. In order to extract scalable heuristics from optimal or best feasible solutions, we propose a machine-learning (ML)-based approach called ENSIGHT (Evolutionary Neural network with Scalable Information for Generation of Heuristics for Transportation). ENSIGHT consists of three phases: solution generation, interpretation of solutions, and improvement of heuristics by an evolutionary neural network (ENN). First, a set of optimal or best feasible solutions for the training set of problem instances is acquired by using the proposed mathematical model. Second, as for the process interpreting those solutions, an approach for transforming them into training data by way of scalable input attributes as well as output discretisation is followed. Third, the ENN improves the learned heuristics by an evolutionary parameter optimisation process for minimization of total tardiness. To verify the performance of the proposed ENSIGHT, we conducted experiments and the results of which showed that it outperforms other ML techniques and the current dispatching rules (DRs). Moreover, the approach was demonstrated to be effective in learning scalable heuristics based on combined scalable inputs and discretisation as well as an evolutionary improvement process.

关键词： Pickup and delivery problem Machine learning Evolutionary neural network Scalable information mixed-integer linear programming

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MILP-based discrete sizing and topology optimization of truss structures: new formulation and benchmarking

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2022年第10期65卷 277-277页

作者： Brutting, Jan Senatore, Gennaro Fivet, Corentin Swiss Fed Inst Technol Lausanne EPFL Struct Xplorat Lab Passage Cardinal 13b CH-1700 Fribourg Switzerland Swiss Fed Inst Technol Lausanne EPFL Appl Comp & Mech Lab Lausanne Switzerland

Discrete sizing and topology optimization of truss structures subject to stress and displacement constraints has been formulated as a mixed-integer linear programming (MILP) problem. The computation time to solve a MILP problem to global optimality via a branch-and-cut solver highly depends on the problem size, the choice of design variables, and the quality of optimization constraint formulations. This paper presents a new formulation for discrete sizing and topology optimization of truss structures, which is benchmarked against two well-known existing formulations. Benchmarking is carried out through case studies to evaluate the influence of the number of structural members, candidate cross sections, load cases, and design constraints (e.g., stress and displacement limits) on computational performance. Results show that one of the existing formulations performs significantly worse than all other formulations. In most cases, the new formulation proposed in this work performs best to obtain near-optimal solutions and verify global optimality in the shortest computation time.

关键词： Structural optimization Truss Sizing optimization Topology optimization mixed-integer linear programming Gurobi

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Rail Transit Regenerative Braking Energy Recovery Optimization to Provide Grid Services

Rail Transit Regenerative Braking Energy Recovery Optimizati...

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IEEE Power and Energy Conference at Illinois (PECI)

作者： Talkington, Samuel Grijalva, Santiago Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (纸本)9781728186481

This paper develops an optimization framework for scheduling charging and dispatch of regenerative braking energy (RBE) generated by an electric train system fed by a reversible substation. The mixed-integer linear programming model presented seeks to maximize the RBE retained in the system within its physical constraints, demonstrating the potential for the storage of RBE for use in grid services and resilience applications such as outage response and security-constrained dispatch. Daily and yearly time series analyses are used to showcase energy cost reductions of up to 20% per year, and decreased reliance on power from the grid, leading to reduced lifecycle operation emissions. The model is calibrated on real LMP data from the New England Independent System Operator. Furthermore, the proposed modeling approach is able to capture energy consumption differences associated with selected operational and design parameters, and thus is applicable for policy or project-level analyses to motivate transit electrification decisions.

关键词： power system optimization electrified rail transit energy storage regenerative braking mixed-integer linear programming

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Novel p-Median-based Formulations for Maximizing Coverage in 5G/6G Wireless Networks 3

Novel <i>p</i>-Median-based Formulations for Maximizing Cove...

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3rd South American Colloquium on Visible Light Communications (SACVLC)

作者： Sandoval, Cesar Adasme, Pablo San Juan, Enrique Soto, Ismael Dehghan Firoozabadi, Ali Univ Santiago Chile Ctr Multidisciplinary Res Telecommun Technol CIMT Dept Elect Engn Fac Engn Ave Ecuador 3519 Santiago Chile Univ Tecnol Metropolitana Dept Elect Av Jose Pedro Alessandri 1242 Santiago Chile

ISBN: (纸本)9781665442251

In this paper, we consider the problem of maximizing user coverage for 5G/6G wireless communication networks subject to facility location and radial distance constraints. For this purpose, we propose two novel mixed-integer linear programming models which are constructed based on a classical combinatorial optimization problem referred to as the p-Median problem in the literature. In the classical p-Median problem, one seeks to find a subset of p facilities in order to assign users to them while minimizing the total distance costs between users and facilities. The novelty of our proposed models is the consideration of non-overlapping radial distance constraints between antennas (facilities). In particular, our first model maximizes the total number of users. Whilst the second one includes in the objective function the maximization of users and the minimization of the number of antennas to be activated. So far we solve instances with up to 100 antennas and 1000 users with the Gurobi solver. Our preliminary numerical results indicate that the first model is harder to solve to global optimality than the second one. The numerical results obtained also show that the increase in the number of radius allowed provides more flexibility and accuracy to the model, although at a higher computational cost. Finally, we highlight that the proposed models can be used for future developments of 5G/6G networks in order to improve coverage.

关键词： p-Median problem mixed-integer linear programming maximum user coverage in 5G/6G networks

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