TY - CHAP A1 - Pedersen, Jaap A1 - Schachler, Birgit A1 - Heider, Anya A1 - Pleßmann, Guido T1 - Distribution System Planning with Battery Storage using Multiperiod Optimal Power Flow T2 - 14th International Renewable Energy Storage Conference 2020 (IRES 2020) N2 - The ongoing energy transition introduces new challenges for distribution networks and brings about the need to expand existing power grid capacities. In order to contain network expansion and with it economic costs, utilization of various flexibility options to reduce expansion needs is discussed. This paper proposes a multiperiod optimal power flow (MPOPF) approach with a new continuous network expansion formulation to optimize the deployment of flexibility options under the objective of minimizing network expansion costs. In a comparison of the newly proposed continuous network expansion formulation with an existing mixed integer formulation and a continuous interpretation of the latter the here proposed formulation is shown to be useful in order to obtain a solvable problem and contain computational efforts. The presented MPOPF including the flexibility options storage units and curtailment is then assessed on synthetic medium voltage grids and applied to evaluate the benefit of a combined vs. a stepwise optimization of these flexibility options. It is demonstrated that using a local solver the proposed approach is applicable and yields a solution in reasonable time. Furthermore, it is shown that the combined optimization generally leads to a more efficient utilization of the considered flexibility options and therefore lower grid expansion costs than the stepwise consideration. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.2991/ahe.k.210202.007 VL - 6 SP - 41 EP - 48 ER - TY - JOUR A1 - Hennings, Felix A1 - Anderson, Lovis A1 - Hoppmann-Baum, Kai A1 - Turner, Mark A1 - Koch, Thorsten T1 - Controlling transient gas flow in real-world pipeline intersection areas JF - Optimization and Engineering N2 - Compressor stations are the heart of every high-pressure gas transport network. Located at intersection areas of the network they are contained in huge complex plants, where they are in combination with valves and regulators responsible for routing and pushing the gas through the network. Due to their complexity and lack of data compressor stations are usually dealt with in the scientific literature in a highly simplified and idealized manner. As part of an ongoing project with one of Germany's largest Transmission System Operators to develop a decision support system for their dispatching center, we investigated how to automatize control of compressor stations. Each station has to be in a particular configuration, leading in combination with the other nearby elements to a discrete set of up to 2000 possible feasible operation modes in the intersection area. Since the desired performance of the station changes over time, the configuration of the station has to adapt. Our goal is to minimize the necessary changes in the overall operation modes and related elements over time, while fulfilling a preset performance envelope or demand scenario. This article describes the chosen model and the implemented mixed integer programming based algorithms to tackle this challenge. By presenting extensive computational results on real world data we demonstrate the performance of our approach. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1007/s11081-020-09559-y VL - 22 SP - 687 EP - 734 PB - Springer Nature ET - 2 ER - TY - JOUR A1 - Zakiyeva, Nazgul A1 - Petkovic, Milena T1 - High-dimensional high-frequency time series prediction with a mixed integer optimisation method JF - Operations Research Proceedings 2023. OR 2023 N2 - We study a functional autoregressive model for high-frequency time series. We approach the estimation of the proposed model using a Mixed Integer Optimisation method. The proposed model captures serial dependence in the functional time series by including high-dimensional curves. We illustrate our methodology on large-scale natural gas network data. Our model provides more accurate day-ahead hourly out-of-sample forecast of the gas in and out-flows compared to alternative prediction models. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-93068 SN - 1438-0064 SP - 423 EP - 429 ER - TY - THES A1 - Rehfeldt, Daniel T1 - Faster algorithms for Steiner tree and related problems: From theory to practice KW - Steiner tree problem Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-85148 ER - TY - JOUR A1 - Aigner, Kevin-Martin A1 - Clarner, Jan-Patrick A1 - Liers, Frauke A1 - Martin, Alexander T1 - Robust Approximation of Chance Constrained DC Optimal Power Flow under Decision-Dependent Uncertainty JF - European Journal of Operational Research N2 - We propose a mathematical optimization model and its solution for joint chance constrained DC Optimal Power Flow. In this application, it is particularly important that there is a high probability of transmission limits being satisfied, even in the case of uncertain or fluctuating feed-in from renewable energy sources. In critical network situations where the network risks overload, renewable energy feed-in has to be curtailed by the transmission system operator (TSO). The TSO can reduce the feed-in in discrete steps at each network node. The proposed optimization model minimizes curtailment while ensuring that there is a high probability of transmission limits being maintained. The latter is modeled via (joint) chance constraints that are computationally challenging. Thus, we propose a solution approach based on the robust safe approximation of these constraints. Hereby, probabilistic constraints are replaced by robust constraints with suitably defined uncertainty sets constructed from historical data. The ability to discretely control the power feed-in then leads to a robust optimization problem with decision-dependent uncertainties, i.e. the uncertainty sets depend on decision variables. We propose an equivalent mixed-integer linear reformulation for box uncertainties with the exact linearization of bilinear terms. Finally, we present numerical results for different test cases from the Nesta archive, as well as for a real network. We consider the discrete curtailment of solar feed-in, for which we use real-world weather and network data. The experimental tests demonstrate the effectiveness of this method and run times are very fast. Moreover, on average the calculated robust solutions only lead to a small increase in curtailment, when compared to nominal solutions. Y1 - 2021 ER - TY - CHAP A1 - Tateiwa, Nariaki A1 - Shinano, Yuji A1 - Yamamura, Keiichiro A1 - Yoshida, Akihiro A1 - Kaji, Shizuo A1 - Yasuda, Masaya A1 - Fujisawa, Katsuki T1 - CMAP-LAP: Configurable Massively Parallel Solver for Lattice Problems T2 - HiPC 2021 proceedings N2 - Lattice problems are a class of optimization problems that are notably hard. There are no classical or quantum algorithms known to solve these problems efficiently. Their hardness has made lattices a major cryptographic primitive for post-quantum cryptography. Several different approaches have been used for lattice problems with different computational profiles; some suffer from super-exponential time, and others require exponential space. This motivated us to develop a novel lattice problem solver, CMAP-LAP, based on the clever coordination of different algorithms that run massively in parallel. With our flexible framework, heterogeneous modules run asynchronously in parallel on a large-scale distributed system while exchanging information, which drastically boosts the overall performance. We also implement full checkpoint-and-restart functionality, which is vital to high-dimensional lattice problems. Through numerical experiments with up to 103,680 cores, we evaluated the performance and stability of our system and demonstrated its high capability for future massive-scale experiments. Y1 - 2021 ER - TY - JOUR A1 - Xu, Xiaofei A1 - Chen, Ying A1 - Zhang, Ge A1 - Koch, Thorsten T1 - Modeling functional time series and mixed-type predictors with partially functional autoregressions* JF - Journal of Business and Economic Statistics N2 - In many business and economics studies, researchers have sought to measure the dynamic dependence of curves with high-dimensional mixed-type predictors. We propose a partially functional autoregressive model (pFAR) where the serial dependence of curves is controlled by coefficient operators that are defined on a two-dimensional surface, and the individual and group effects of mixed-type predictors are estimated with a two-layer regularization. We develop an efficient estimation with the proven asymptotic properties of consistency and sparsity. We show how to choose the sieve and tuning parameters in regularization based on a forward-looking criterion. In addition to the asymptotic properties, numerical validation suggests that the dependence structure is accurately detected. The implementation of the pFAR within a real-world analysis of dependence in German daily natural gas flow curves, with seven lagged curves and 85 scalar predictors, produces superior forecast accuracy and an insightful understanding of the dynamics of natural gas supply and demand for the municipal, industry, and border nodes, respectively. Y1 - 2021 U6 - https://doi.org/10.1080/07350015.2021.2011299 SP - 1 EP - 43 ER - TY - THES A1 - Lenz, Ralf T1 - Optimization of Stationary Expansion Planning and Transient Network Control by Mixed-Integer Nonlinear Programming Y1 - 2021 UR - http://dx.doi.org/10.14279/depositonce-12765 U6 - https://doi.org/10.14279/depositonce-12765 ER - TY - JOUR A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Vigerske, Stefan A1 - Winkler, Michael T1 - 制約整数計画ソルバ SCIP の並列化 JF - 統計数理 N2 - 制約整数計画(CIP: Constraint Integer Programs)は,制約プログラミング(CP: Constraint Programming),混合整数計画(MIP: Mixed Integer Programming),充足可能性問題(SAT: Satisfability Problem)の研究分野におけるモデリング技術と解法を統合している.その結果,制約整数計画は,広いクラスの最適化問題を扱うことができる.SCIP(Solving Constraint Integer Programs)は,CIP を解くソルバとして実装され,Zuse Institute Berlin(ZIB)の研究者を中心として継続的に拡張が続けられている.本論文では,著者らによって開発された SCIP に対する2 種類の並列化拡張を紹介する.一つは,複数計算ノード間で大規模に並列動作する ParaSCIPである.もう一つは,複数コアと共有メモリを持つ 1 台の計算機上で(スレッド)並列で動作する FiberSCIP である.ParaSCIP は,HLRN II スーパーコンピュータ上で,一つのインスタンスを解くために最大 7,168 コアを利用した動作実績がある.また,統計数理研究所の Fujitsu PRIMERGY RX200S5 上でも,最大 512 コアを利用した動作実績がある.統計数理研究所のFujitsu PRIMERGY RX200S5 上では,これまでに最適解が得られていなかった MIPLIB2010のインスタンスである dg012142 に最適解を与えた. N2 - The paradigm of constraint integer programming (CIP) combines modeling and solving techniques from the fields of constraint programming (CP), mixed-integer programming (MIP) and satisfability problem (SAT). This paradigm allows us to address a wide range of optimization problems. SCIP is an implementation of the idea of CIP and is now being continuously extended by a group of researchers centered at Zuse Institute Berlin (ZIB). This paper introduces two parallel extensions of SCIP. One is ParaSCIP, which is intended to run on a large scale distributed memory computing environment, and the other is FiberSCIP, intended to run on a shared memory computing environment. ParaSCIP has been run successfully on the HLRN II supercomputer utilizing up to 7,168 cores to solve a single difficult MIP. It has also been tested on an ISM supercomputer (Fujitsu PRIMERGY RX200S5 using up to 512 cores). The previously unsolved instance dg012142 from MIPLIB2010 was solved by using the ISM supercomputer. Y1 - 2013 UR - https://www.ism.ac.jp/editsec/toukei/pdf/61-1-047.pdf VL - 61 IS - 1 SP - 47 EP - 78 ER - TY - JOUR A1 - 品野, 勇治 T1 - 最適化研究における数値実験を中心とした アプリケーション駆動研究サイクル JF - 機関誌「オペレーションズ・リサーチ」 N2 - 最適化研究におけるアプリケーション駆動研究サイクルを紹介する.アプリケーション駆動研究サイクルは,学術機関での研究と企業における研究成果の利用とのつながりを良くする点では優れている.一方で,ソフトウェア開発・維持に多大な労力を要するため,日本の大学や研究機関における実施には困難さが伴う.ZIBにおいてアプリケーション駆動研究サイクルが,比較的うまく機能している背景を説明する.また,日本においてアプリケーション駆動研究サイクルを活性化するための第一歩として,論文投稿時に,論文中の数値実験に利用した全データ提出の義務化を提案したい. Y1 - 2014 UR - https://orsj.org/wp-content/corsj/or59-5/or59_5_247.pdf VL - 59 IS - 5 SP - 247 EP - 253 ER - TY - JOUR A1 - 藤澤, 克樹 A1 - 品野, 勇治 T1 - 最適化と計算の今後 ―大規模問題をどこまで解決できるのか?― JF - 機関誌「オペレーションズ・リサーチ」 N2 - 近年,大規模かつ複雑な最適化問題を高速に解く需要はさまざまな産業界や学術分野において急速に高まりつつある.これからの研究においては最先端理論 (Theory)+超大規模実データ (Practice)+最新計算技術(Computation) の三つを有機的に組み合わせることによって,実用に耐えうる解決策の提示と大規模最適化問題を扱う際の先例となることが求められている.本稿では最適化と計算に関する最新の傾向に触れるとともに,最適化の計算の今後についても考えていきたい. Y1 - 2014 UR - https://orsj.org/wp-content/corsj/or59-1/or59_1_11.pdf VL - 59 IS - 1 SP - 11 EP - 19 ER - TY - JOUR A1 - Wakayama, Yuki A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(時間集約によるモデル縮約とその効果) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation(Model Reduction by Time Aggregation and Its Effect) JF - エネルギー・資源学会第34回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - A hierarchical mixed-integer linear programming method to solve optimal design problems of energy supply systems efficiently has been proposed. The original problem is solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of each other at the lower level. In this paper, a method of reducing model by time aggregation is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. On one hand, the method may decrease the number of design variables and costraints at the upper level, and thus the computation time at the upper level. On the other hand, it may increase the numbers of generated design solution candidates and solved optimal operation problems, and thus the computation time at both the levels. Though a case study on the optimal design of a cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency. Y1 - 2018 SP - 401 EP - 404 ER - TY - JOUR A1 - Taniguchi, Shusuke A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Ohkura, Masashi A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(多目的最適化におけるK-ベスト解の探索) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Search for K-Best Solutions in Multiobjective Optimization) JF - エネルギー・資源学会第31回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - A mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed to solve the optimal design problem of energy supply systems efficiently is extended to search K-best solutions in multiobjective optimization: At the upper level, the optimal values of design variables are searched by the branch and bound method with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized independently at the respective periods set for variations in energy demands by the branch and bound method with the values of design variables given tentatively during the search at the upper level. A weighting method is employed for multiobjective optimization, and a weighted sum of the annual total cost and primary energy consumption is adopted as the objective function to be minimized. A practical case study on the optimal design of a cogeneration system is conducted. The validity and effectiveness of the proposed method are clarified, and the trade-off relationship between the annual total cost and primary energy consumption is confirmed. Y1 - 2015 SP - 267 EP - 272 ER - TY - JOUR A1 - Takeuchi, Kotaro A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - エネルギー供給システムの 設計と運用の階層的関係を考慮した最適化 (運用を考慮した期間クラスタリングによるモデル縮約) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Model Reduction by Clustering Periods in Consideration of Operation) JF - エネルギー・資源学会第35回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) methods have been applied widely to such multi-period optimal design problems. A hierarchical MILP method has been proposed to solve the problems very efficiently. In addition, by utilizing features of the hierarchical MILP method, a method of reducing model by clustering periods has also been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, by utilizing features of the hierarchical MILP method, a method of clustering periods is proposed based on the optimal operational strategies of energy supply systems obtained by solving the relaxed optimal design problem. As a case study, the method is applied to the optimal design of a gas turbine cogeneration system, and it is clarified that the method is effective to enhance the computation efficiency in comparison with a conventional method of clustering periods regularly. Y1 - 2019 SP - 169 EP - 174 ER - TY - JOUR A1 - Kamada, Hiroki A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 混合整数線形モデルによる エネルギー供給システムのロバスト最適設計 (階層的最適化手法の適用) T1 - Robust Optimal Design of Energy Supply Systems Based on a Mixed-Integer Linear Model (Application of a Hierarchical Optimization Method) JF - エネルギー・資源学会第35回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed- integer linear model for constituent equipment. A robust optimal design problem has been formulated as a three-level min-max- min optimization one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering hierarchical relationships among design variables, uncertain energy demands, and operation variables. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, mixed-integer linear programming method in consideration of the hierarchical relationship between design and operation variables is applied to parts of the robust optimal design method which take long computation times to solve problems efficiently. In a case study, this revised method is applied to the robust optimal design of a cogeneration system with a simple configuration, and the validity and effectiveness of the method are ascertained. Y1 - 2019 SP - 163 EP - 168 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Taniguchi, Syusuke A1 - Ohkura, Masashi A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(手法の提案) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Proposal of Optimization Method) JF - 第33回エネルギー・資源学会研究発表会講演論文要旨集・講演論文集 N2 - A mixed-integer linear programming (MILP) method utilizing the hierarchical relationship between design and op- eration variables is proposed to solve the optimal design problem of energy supply systems efficiently: At the upper level, the optimal values of design variables are searched by the branch and bound method; At the lower level, the values of operation variables are optimized by the branch and bound method under the values of design variables given tentatively during the search at the upper level; Lower bounds for the optimal value of the objective function are evaluated, and are utilized for the bounding operations at both the levels. This method is implemented into open and commercial MILP solvers. Illustrative and practical case studies on the optimal design of cogeneration systems are conducted, and the validity and effectiveness of the proposed method are clarified. Y1 - 2014 SP - 183 EP - 188 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Taniguchi, Syusuke A1 - Ohkura, Masashi A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用階層的関係を考慮した最適化(K-ベスト解の探索) T1 - Optimization ofEnergy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Search for K-Best Solutions) JF - 日本機械学会第11回最適化シンポジウム2014講演論文集 N2 - A mixed-integer linear programming methodutilizing the hierarchical relationship between design and operation variables proposed ot solve the optimal design problem of energy supply systems efficiently is extended ot search K-best solutions: At the upper level, the optimal values ofdesign variables are searched with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized with the values of design variables given tentatively; The obtained solution is used to renew K-best incumbent solutions, and the upper bound for the value of the objective function for K-best solutions is replaced correspondingly. A practical case study is conducted, and the validity and effectiveness of the proposed method are clarified. Y1 - 2014 SP - 1 EP - 4 ER - TY - JOUR A1 - Wakayama, Yuki A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 階層的最適化によるエネルギ ー供給システムの最適設計・運用 (期間のクラスタリングに よるモデル縮約とその効果) T1 - Optimal Design and Operation of Energy Supply Systems by Hierarchical Optimization (Model Reduction by Clustering Periods and Its Effect) JF - 日本機械学会関西支部第93期定時総会講演会講演論文集 N2 - Ahierarchical mixed-integer linear programmingmethod has been proposed to solve optimal design problems of energy supply systems efficiently. In this paper, a method of reducing model by clustering periods is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Through acase study on the optimaldesign of a cogeneration system, ti is clarified how the model reduction si effective ot enhance the computation efficiency. Y1 - 2018 SP - 259 EP - 260 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Takeuchi, Kotaro A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (モデル縮約のための期間クラスタリング手法の比較) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Comparison of Time-Period Clustering Methods for Model Reduction) JF - 第38回エネルギー・資源学会研究発表会講演論文集 N2 - Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, three clustering methods are applied to time aggregation and compared with one another in terms of the computation efficiency. Especially, the k-medoids method is applied newly in addition to the time-series and operation-based methods applied previously. A case study is conducted on the optimal design of a gas turbine cogeneration system for district energy supply. Through the study, it turns out the k-medoids method is effective to shorten the computation time as compared with the time-series method, although it is necessary to set the number of clusters artifically in both the methods. It also turns out that the operation-based method is more effective than the k-medoids method in terms of the computation efficiency even with the number of clusters set automatically. Y1 - 2019 SP - 109 EP - 114 ER - TY - JOUR A1 - Takeuchi, Kotaro A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - エネルギー供給システムの 設計および運用の階層的関係を考慮した最適化 (多目的最適設計へのモデル縮約の適用) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Application of Model Reduction to Multiobjective Optimal Design) JF - エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) methods have been applied widely to such optimal design problems. A hierarchical MILP method has been proposed to solve the problems very efficiently. In addition, by utilizing features of the hierarchical MILP method, a method of reducing model by clustering periods based on the optimal operational strategies of equipment has been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, these methods are applied to the multiobjective optimal design of a cogeneration system by considering the annual total cost and primary energy consumption as the objective functions to be minimized. Through a case study, it turns out that the model reduction by the operation-based time-period clustering is effective in terms of the computation efficiency when importance is given to the first objective function, while it is not when importance is given to the second objective function. Y1 - 2020 SP - 724 EP - 729 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (蓄エネルギー機器を有するシステムへの適用) T1 - Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Application to Systems With Energy Storage Units) JF - 第40回エネルギー・資源学会研究発表会講演論文集 N2 - Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies has been extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of re- ducing model is extended by aggregating representative days and sampling times differently in consideration of the characteristics of storage units. A case study is conducted on the optimal design of a gas turbine cogeneration system with a thermal storage unit for district energy supply. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solution as compared with a conventional method. It also turns out that the model reduction with the special time aggregation is effective to shorten the computation time as compared with that without time aggregation in case that the number of candidates for equipment capacities is relatively small. Y1 - 2021 SP - 398 EP - 403 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した設計解の評価) T1 - Derivation and Evaluation of Approximate Optimal Design Solutions of Energy Supply Systems by Time Aggregation (Evaluation of Design Solutions Using Hierarchical Optimization) JF - エネルギー・資源学会第38回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to solve such an optimal design problem with a large number of periods efficiently is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to provide a time aggregation method for deriving aprroximate optimal design solutions and evaluting their values of the objective function. Especially, a method of evaluating design solutions is presented here using both methods of evaluating the robustness under uncertain energy demands and solving optimal design problems by a hierarchical approach. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach. Y1 - 2022 SP - 468 EP - 473 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した近似最適設計) T1 - Derivation and Evaluation of Approximate Optimal Design Solutions of Energy Supply Systems by Time Aggregation (Approximate Optimal Design Using Hierarchical Optimization) JF - 第41回エネルギー・資源学会研究発表会講演論文集 N2 - For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to efficiently solve such an optimal design problem with a large number of periods for variations in energy de- mands is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to propose a time aggregation approach for deriving suitable aprroximate optimal design solutions and evaluting their values of the objective function accurately. This time aggregation approach is realized by combining a robust optimal design method under uncertain energy demands and a hierarchical approach for solving large scale optimal design problems. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective upper and lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach. Y1 - 2022 SP - 144 EP - 148 ER - TY - JOUR A1 - Kamada, Hiroki A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 階層的最適化手法の援用による エネルギー供給システムのロバスト最適設計 T1 - Robust Optimal Design of Energy Supply Systems With Aid of a Hierarchical Optimization Method JF - エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集 N2 - A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed- integer linear model for constituent equipment. A robust optimal design problem has been formulated as a three-level min-max- min optimization one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering hierarchical relationships among design variables, uncertain energy demands, and operation variables. Since this problem must be solved by a special algorithm and is too difficult to solve even using a commercial solver, a hierarchical optimization approach has been applied to solve the problem but its application is limited only to small scale toy problems. In this paper, some strategies are introduced into the hierarchical optimization approach to enhance the computation efficiency for the purpose of applying the approach to large scale practical problems. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained. Y1 - 2020 SP - 730 EP - 735 ER - TY - JOUR A1 - Takeuchi, Kotaro A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - エネルギー供給システムの設計および運用の階層的関係を考慮した最適化 (k-メドイド法に基づく期間クラスタリングの適用) T1 - Optimization of Energy Supply Systems in Consideration of Hierachical Relationship Between Design and Operation (Application of Time-Period Clustering Based on k-Medoids Method) JF - 日本機械学会関西支部第95期定時総会講演会講演論文集 N2 - To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. A hierarchical mixed-integer linear programming method has been proposed to solve such an optimal design problem efficiently. In this paper, a method of reducing model by clustering periods with the k-medoids method is applied to the relaxed optimal design problem at the upper level. Through a case study, it is clarified how the proposed method is effective to enhance the computation efficiency in a large scale optimal design problem. Y1 - 2020 SP - 1 EP - 4 ER - TY - JOUR A1 - Kamada, Hiroki A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - 階層的最適化手法を用いた エネルギー供給システムのロバスト性評価 T1 - Evaluating Robustness of Energy Supply Systems Using a Hierarchical Optimization Method JF - 日本機械学会関西支部第95期定時総会講演会講演論文集 N2 - A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed-integer linear model for constituent equipment. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, a hierarchical optimization method is applied to two types of optimization problems for evaluating robustness to solve them efficiently. In a case study, the proposed method is applied to a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained. Y1 - 2020 SP - 1 EP - 4 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Evaluation of Design Alternatives for a Gas Turbine Cogeneration Plant Based on Multiobjective K-Best Solutions JF - International Conference on Power Engineering-2019 N2 - To realize the best performance in energy supply, it is an important task to determine types, capacities, and numbers of energy conversion equipment appropriately. It is also necessary to take account of seasonal and hourly variations in energy demands and corresponding operational strategies of equipment. The mixed-integer linear programming (MILP) method has been utilized widely to derive the optimal solution for such a design problem. From the design viewpoint, it is important to generate not only the optimal solution but also suboptimal ones which follow the optimal one without omission, what are called K-best solutions. In this paper, an MILP method utilizing the hierarchical relationship between design and operation variables is applied along with some strategies to efficiently drive K-best solutions of a multiobjective optimal design problem of a gas turbine cogeneration system for district energy supply. The annual total cost and primary energy consumption are adopted as the objective functions to be minimized. A case study is conducted, and K-best solutions with an allowable increase in the value of the combined objective function are derived for each value of the weight for the annual total cost. Through the study, it is clarified how the weight affects the computation time, the number of the K-best solutions, and the design specifications and the values of the objective functions for the K-best solutions. Y1 - 2019 SP - 1112 EP - 1117 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Hiramatsu, Yuto A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model JF - The 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022) N2 - In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified. As a result, it turns out how the values of these performance criteria are close to the optimal ones in relation to the uncertainty in energy demands. This work will be an important step toward developing a multiobjective robust optimal design method. Y1 - 2022 SP - 1937 EP - 1948 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Taniguchi, Syusuke A1 - Wakui, Tetsuya T1 - Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method JF - Energy N2 - For the purpose of making a decision in the optimal design of an energy supply system, it is important to investigate not only the optimal solution but also suboptimal ones which follow the optimal one without any omissions, what are called K-best solutions. In this paper, a mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed previ- ously is extended to search the K-best solutions very efficiently. In addition, methods for updating the incumbents are incorporated into the extended method for three options for the criterion set newly in deriving the K-best solutions. This extended method is implemented into open and commercial MILP solvers, and is applied to illustrative and practical case studies, respectively, on the optimal design of cogeneration systems. Through the studies, it turns out that the proposed method is much superior in terms of solution optimality and computation efficiency to a conventional method, and that the computation efficiency to derive one of the K-best solutions by the proposed method increases with the number of K-best solutions. In addition, features of the K-best solutions in the value of objective function are clarified. Y1 - 2019 U6 - https://doi.org/https://doi.org/10.1016/j.energy.2018.02.077 VL - 184 SP - 45 EP - 57 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Hiramatsu, Yuto A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model JF - Proceedings of the 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022) N2 - In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified. Y1 - 2022 SP - 1937 EP - 1948 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Takeuchi, Kotaro A1 - Wakui, Tetsuya T1 - Operation-based time-period clustering for optimal design of energy supply systems by a hierarchical MILP method JF - THE 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS(ECOS 2019) N2 - Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, a method of clustering periods has been proposed based on the optimal operational strategies of the systems to avoid a large decrease in the lower bound for the optimal value of the objective function by model reduction. This method has been realized only by solving the relaxed optimal design problem at the upper level in advance. The method can decrease the number of operation variables and constraints at the upper level, and thus can decrease the computation time at the upper level. Through a case study on the optimal design of a gas turbine cogeneration system, it is clarified how the proposed clustering method is effective to enhance the computation efficiency in comparison with the conventional one which clusters periods regularly in time series. Y1 - 2019 SP - 527 EP - 539 ER - TY - JOUR A1 - Le, Thi Thai A1 - Koch, Thorsten T1 - Effect of inertia force on the interface stability of a tangential-velocity discontinuity in porous media JF - International Journal of Multiphase Flow N2 - The present study investigates the stability of a tangential-velocity discontinuity in porous media during the withdrawing and injecting processes of natural gases from and into an underground gas storage. The focus is placed on analyzing the impact of inertia forces on the interface stability using the Forchheimer equations. Other publications have relied primarily on Darcy's law to describe flow stability in porous media. However, Darcy's law only adequately describes flows in which viscous forces dominate over inertia forces. As the flow rate increases, the significance of inertia forces becomes more pronounced, and Darcy's law becomes insufficient for considering such flows. Our findings indicate that even a slight consideration of the inertia effect leads to permanent destabilization of the discontinuity interface, regardless of the fluid viscosity or the Mach number. In contrast, when the inertia effect is neglected, the interface is stabilized across the entire Mach number range if the fluid viscosity is strong enough. Y1 - 2023 U6 - https://doi.org/10.1016/j.ijmultiphaseflow.2023.104612 VL - 169 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Day and time aggregations for optimal design of energy supply systems with storage units by a hierarchical MILP method JF - The 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022) N2 - Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies is extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of reducing model is extended by aggregating both representative days and sampling times separately in consideration of the characteristics of energy storage units. A case study is conducted on the optimal design of a cogeneration system with a thermal storage tank. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solutions in short computation times. It also turns out that the model reduction with day and time aggregations is effec- tive to shorten the computation times furthermore when the number of candidates for equipment capacities is relatively small. Y1 - 2022 SP - 1891 EP - 1902 ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Day and time aggregations for optimal design of energy supply systems with storage units by a hierarchical MILP method JF - PROCEEDINGS OF ECOS 2022 - THE 35 TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS N2 - Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies is extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of reducing model is extended by aggregating both representative days and sampling times separately in consideration of the characteristics of energy storage units. A case study is conducted on the optimal design of a cogeneration system with a thermal storage tank. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solutions in short computation times. It also turns out that the model reduction with day and time aggregations is effective to shorten the computation times furthermore when the number of candidates for equipment capacities is relatively small. Y1 - 2022 SP - 1891 EP - 1902 ER - TY - JOUR A1 - Rehfeldt, Daniel T1 - Faster Algorithms for Steiner Tree and related Problems: From Theory to Practice JF - OR News: Das Magazin der GOR Y1 - 2022 ER - TY - CHAP A1 - Zakiyeva, Nazgul A1 - Petkovic, Milena T1 - Modeling and Forecasting Gas Network Flows with Multivariate Time Series and Mathematical Programming Approach T2 - Operations Research Proceedings 2021. OR 2021. N2 - With annual consumption of approx. 95 billion cubic meters and similar amounts of gas just transshipped through Germany to other EU states, Germany’s gas transport system plays a vital role in European energy supply. The complex, more than 40,000 km long high-pressure transmission network is controlled by several transmission system operators (TSOs) whose main task is to provide security of supply in a cost-efficient way. Given the slow speed of gas flows through the gas transmission network pipelines, it has been an essential task for the gas network operators to enhance the forecast tools to build an accurate and effective gas flow prediction model for the whole network. By incorporating the recent progress in mathematical programming and time series modeling, we aim to model natural gas network and predict gas in- and out-flows at multiple supply and demand nodes for different forecasting horizons. Our model is able to describe the dynamics in the network by detecting the key nodes, which may help to build an optimal management strategy for transmission system operators. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-08623-6_31 SP - 200 EP - 205 PB - Springer, Cham ER - TY - GEN A1 - Shinano, Yuji A1 - Vigerske, Stefan T1 - Smoothie: Mixing the strongest MIP solvers to solve hard MIP instances on supercomputers - Phase I development N2 - Mixed-Integer Linear Programming (MIP) is applicable to such a wide range of real-world decision problems that the competition for the best code to solve such problems has lead to tremendous progress over the last decades. While current solvers can solve some of the problems that seemed completely out-of-reach just 10 years ago, there are always relevant MIP problems that currently cannot be solved. With the Smoothie solver we intend to solve extremely hard MIP problems by building on the many years that went into the development of several state-of-the-art MIP solvers and by utilizing some of the largest computing resources available. The high-level task parallelization framework UG (Ubiquity Generator) is used and extended by Smoothie to build a solver that uses large-scale parallelization to distribute the solution of a single MIP on a shared- or distributed-memory computing infrastructure, thereby employing several established MIP solvers simultaneously. For the first development phase, which is the topic of this report, both FICO Xpress and Gurobi are used in concurrent mode on a single machine, while information on incumbent solutions and explored branch-and-bound subtrees is exchanged. A dynamic restarting mechanism ensures that solver configurations are selected that promise most suitable for the MIP to be solved. We report on initial findings using this early version of Smoothie on unsolved problems from MIPLIB 2017. T3 - ZIB-Report - 25-18 KW - MIPLIB, MIP, UG, Parallelization Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-101906 SN - 1438-0064 ER - TY - JOUR A1 - Le, Thi Thai A1 - Petkovic, Milena T1 - Predicting Fluid Interface Instability in Energy Systems for Sustainable Energy Transition JF - Operations Research Proceedings 2023. OR 2023. N2 - Due to the coexistence of different gases in underground storage, this work explores the interface stability's impact on energy storage, specifically during the injection and withdrawal of gases such as hydrogen and natural gas. A new approach of combing simulation and time series analysis is used to accurately predict instability modes in energy systems. Our simulation is based on the 2D Euler equations, solved using a second-order finite volume method with a staggered grid. The solution is validated by comparing them to experimental data and analytical solutions, accurately predicting the instability's behavior. We use time series analysis and state-of-the-art regime-switching methods to identify critical features of the interface dynamics, providing crucial insights into system optimization and design. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_45 SP - 349 EP - 356 PB - Springer ER - TY - GEN A1 - Zakiyeva, Nazgul A1 - Petkovic, Milena T1 - High-dimensional high-frequency time series prediction with a mixed integer optimisation method T2 - Operations Research Proceedings T3 - ZIB-Report - 23-30 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-93114 SN - 1438-0064 ER - TY - JOUR A1 - Le, Thi Thai A1 - Tran, Van Cuc A1 - Phung, Dang Hieu T1 - Numerical simulation of tidal flow in Danang Bay Based on non-hydrostatic shallow water equations JF - Pacific Journal of Mathematics for Industry N2 - This paper presents a numerical simulation of the tidal flow in Danang Bay (Vietnam) based on the non-hydrostatic shallow water equations. First, to test the simulation capability of the non-hydrostatic model, we have made a test simulation comparing it with the experiment by Beji and Battjes 1993. Simulation results for this case are compared with both the experimental data and calculations obtained from the traditional hydrostatic model. It is shown that the non-hydrostatic model is better than the hydrostatic model when the seabed topography variation is complex. The usefulness of the non-hydrostatic model is father shown by successfully simulating the tidal flow of Danang Bay. Y1 - 2016 U6 - https://doi.org/10.1186/s40736-015-0020-6 VL - 8 IS - 1 ER - TY - JOUR A1 - Le, Thi Thai A1 - Fukumoto, Yasuhide A1 - Koch, Thorsten T1 - Linear stability of a simple shear layer between two parallel streams in a shallow water flow JF - Physics Letters A N2 - The stability of shear layers in fluid flows is a crucial factor in forming vortices and jets and plays a fundamental role in the development of turbulence. Such shear layer instabilities are ubiquitous in natural phenomena, such as atmospheric and oceanic flows, contributing to the formation of weather systems and predicting tsunamis. This study specifically focuses on the stability of a shear layer sandwiched between two semi-infinite layers within a two-dimensional flow. The velocity profile of the shear layer is assumed to be linearly dependent on the vertical coordinate, while the velocity of the other layers remains uniform with differing strengths. The effect of viscosity and surface tension is ignored to simplify the analysis. The shallow water equations are used to analyze the interface stability of the shear layer, and the resulting dispersion relation between wave frequency and other wave characteristics is obtained. This relation incorporates Whittaker functions and their first derivatives and is used to derive appropriate limits corresponding to various physical conditions. Our study thus contributes to a deeper understanding of the stability of shear layers and their implications for natural phenomena. Y1 - 2024 U6 - https://doi.org/10.1016/j.physleta.2023.129264 VL - 493 PB - Elservier ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - An effective approach for deriving and evaluating approximate optimal design solutions of energy supply systems by time series aggregation JF - Frontiers in Energy Research N2 - It is important to design multi-energy supply systems optimally in consideration of their operations for variations in energy demands. An approach for efficiently solving such an optimal design problem with a large number of periods for variations in energy demands is to derive an approximate optimal design solution by time series aggregation. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. In this paper, an effective approach for time series aggregation is proposed to derive an approximate optimal design solution and evaluate a proper gap between the upper and lower bounds for the optimal value of the objective function based on a mixed-integer linear model. In accordance with aggregation, energy demands are relaxed to uncertain parameters and the problem for deriving an approximate optimal design solution and evaluating it is transformed to a three-level optimization problem, and it is solved by applying both the robust and hierarchical optimization methods. A case study is conducted on a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to derive much smaller gaps as compared with those obtained by a conventional approach. Y1 - 2023 U6 - https://doi.org/10.3389/fenrg.2023.1128681 VL - 11 SP - 1 EP - 14 ER - TY - JOUR A1 - 品野, 勇治 T1 - MIPLIB と Hans Mittelmann’s benchmarks JF - 機関誌「オペレーションズ・リサーチ」 N2 - 混合整数計画法 (Mixed Integer Programming: MIP) は,MIP を解くソフトウェアである MIP ソルバが大規模な現実問題を解けるようになったこともあり,現実問題を解く有用な OR の手法として広く知られるようになった.しかしながら,MIP ソルバの開発に欠かせないベンチマーク・データセットおよび性能測定方法についてはそれほど広く知られているとは言い難い.ベンチマーク・データセットは注意を払って作成しないと,多くのバイアスがかかってしまう.それらのバイアスを可能な限りのぞき,真に有用なベンチマーク・テストの結果を得るためには複数の人数で多大な労力を割く必要がある.本稿では,そのような MIP ソルバ開発の背景として重要な役割を果たしてきた MIPLIB と Hans Mittelmann’s benchmarks について解説する.また,本稿において Hans Mittelmann’s benchmarks は,BENCHMARKS FOR OPTIMIZATION SOFTWAREのページ (http://plato.asu.edu/bench.html) に示されているベンチマークである. Y1 - 2020 UR - https://orsj.org/wp-content/corsj/or65-1/or65_1_49.pdf VL - 65 IS - 1 SP - 49 EP - 56 ER - TY - JOUR A1 - 品野, 勇治 A1 - 藤井, 浩一 T1 - 使ってみよう線形計画ソルバ JF - 機関誌「オペレーションズ・リサーチ」 N2 - 本稿では,線形計画問題を解くソフトウェアである線形計画ソルバの標準的な利用方法と,原稿執筆時点で利用可能なソルバを可能な限り紹介する.筆者らはソルバ開発コミュニティの中で仕事をしているので,この機会に現在のソルバ開発現場の様子も紹介するとともに,各ソルバの特徴として何を紹介するべきかは,できる限り開発者,または,開発者に近い研究者に問い合わせて記述した.本稿は,多くの線形計画ソルバの選択肢がある中で,読者がもつ問題を解くのに最も適当なソルバを選択するための指針を与えることを主たる目的としている. Y1 - 2019 UR - https://orsj.org/wp-content/corsj/or64-4/or64_4_238.pdf VL - 64 IS - 4 SP - 238 EP - 245 ER - TY - CHAP A1 - Petkovic, Milena A1 - Zittel, Janina T1 - Forecasting and modeling the dynamics of large-scale energy networks under the supply and demand balance constraint T2 - Optimization in Green Sustainability and Ecological Transition. ODS 2023 N2 - With the emergence of ”Big Data” the analysis of large data sets of high-dimensional energy time series in network structures have become feasible. However, building large-scale data-driven and computationally efficient models to accurately capture the underlying spatial and temporal dynamics and forecast the multivariate time series data remains a great challenge. Additional constraints make the problem more challenging to solve with conventional methods. For example, to ensure the security of supply, energy networks require the demand and supply to be balanced. This paper introduces a novel large-scale Hierarchical Network Regression model with Relaxed Balance constraint (HNR-RB) to investigate the network dynamics and predict multistep-ahead flows in the natural gas transmission network, where the total in- and out-flows of the network have to be balanced over a period of time. We concurrently address three main challenges: high dimensionality of networks with more than 100 nodes, unknown network dynamics, and constraint of balanced supply and demand in the network. The effectiveness of the proposed model is demonstrated through a real-world case study of forecasting demand and supply in a large-scale natural gas transmission network. The results demonstrate that HNR-RB outperforms alternative models for short- and mid-term horizons. Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-47686-0_29 VL - 12 ER - TY - JOUR A1 - Tateiwa, Nariaki A1 - Shinano, Yuji A1 - Yasuda, Masaya A1 - Kaji, Shizuo A1 - Yamamura, Keiichiro A1 - Fujisawa, Katsuki T1 - Development and analysis of massive parallelization of a lattice basis reduction algorithm JF - Japan Journal of Industrial and Applied Mathematics N2 - The security of lattice-based cryptography relies on the hardness of solving lattice problems. Lattice basis reduction is a strong tool for solving lattice problems, and the block Korkine–Zolotarev (BKZ) reduction algorithm is the de facto standard in cryptanalysis. We propose a parallel algorithm of BKZ-type reduction based on randomization. Randomized copies of an input lattice basis are independently reduced in parallel, while several basis vectors are shared asynchronously among all processes. There is a trade-off between randomization and information sharing; if a substantial amount of information is shared, all processes might work on the same problem, which diminishes the benefit of parallelization. To monitor the balance between randomness and sharing, we propose a new metric to quantify the variety of lattice bases, and we empirically find an optimal parameter of sharing for high-dimensional lattices. We also demonstrate the effectiveness of our parallel algorithm and metric through experiments from multiple perspectives. Y1 - 2023 U6 - https://doi.org/10.1007/s13160-023-00580-z VL - 40 IS - 1 SP - 13 EP - 56 ER - TY - JOUR A1 - Le, Thi Thai A1 - Koch, Thorsten T1 - Instability of a tangential discontinuity surface in a three-dimensional compressible medium JF - Physics of Fluids N2 - Compressible flows appear in many natural and technological processes, for instance, the flow of natural gases in a pipe system. Thus, a detailed study of the stability of tangential velocity discontinuity in compressible media is relevant and necessary. The first early investigation in two-dimensional (2D) media was given more than 70 years ago. In this article, we continue investigating the stability in three-dimensional (3D) media. The idealized statement of this problem in an infinite spatial space was studied by Syrovatskii in 1954. However, the omission of the absolute sign of cos θ with θ being the angle between vectors of velocity and wave number in a certain inequality produced the inaccurate conclusion that the flow is always unstable for entire values of the Mach number M. First, we revisit this case to arrive at the correct conclusion, namely that the discontinuity surface is stabilized for a large Mach number with a given value of the angle θ. Next, we introduce a real finite spatial system such that it is bounded by solid walls along the flow direction. We show that the discontinuity surface is stable if and only if the dispersion relation equation has only real roots, with a large value of the Mach number; otherwise, the surface is always unstable. In particular, we show that a smaller critical value of the Mach number is required to make the flow in a narrow channel stable. Y1 - 2021 U6 - https://doi.org/10.1063/5.0033753 VL - 33 IS - 1 SP - 016106 ER - TY - CHAP A1 - Yokoyama, Ryohei A1 - Kamada, Hiroki A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - A Hierarchical Optimization Approach to Robust Design of Energy Supply Systems Based on a Mixed-Integer Linear Model T2 - Conference N2 - In designing energy supply systems, designers should heighten the robustness in performance criteria against the uncertainty in energy demands. In this paper, a robust optimal design method using a hierarchi- cal mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy sup- ply systems under uncertain energy demands based on a mixed-integer linear model. A robust optimal design problem is formulated as a three-level min-max-min MILP one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret cri- terion, and considering relationships among integer design variables, uncertain energy demands, and inte- ger and continuous operation variables. This problem is solved by evaluating upper and lower bounds for the minimum of the maximum regret of the performance criterion repeatedly outside, and evaluating lower and upper bounds for the maximum regret repeatedly inside. Since these different types of optimization problems are difficult to solve even using commercial MILP solvers, they are solved by applying a hierarchi- cal MILP method developed for ordinary optimal design problems with its modifications. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system. Through the study, its validity and effectiveness are ascertained, and some features of the obtained robust designs are clarified. Y1 - 2020 SP - 601 EP - 613 ER - TY - CHAP A1 - Yokoyama, Ryohei A1 - Takeuchi, Kotaro A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Effect of Model Reduction by Time Aggregation in Multiobjective Optimal Design of Energy Supply Systems by a Hierarchical MILP Method T2 - Conference N2 - The mixed-integer linear programming (MILP) method has been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems effi- ciently. As one of the strategies to enhance the computation efficiency furthermore, a method of reducing model by time aggregation has been proposed to search design candidates accurately and efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method and model reduction by time aggregation are applied to the multiobjective optimal design. In applying the model reduc- tion, the methods of clustering periods by the order of time series, based on an operational strategy, and by the k-medoids method are applied. As a case study, the multiobjective optimal design of a gas turbine cogeneration system with a practical configuration is investigated by adopting the annual total cost and pri- mary energy consumption as the objective functions to be minimized simultaneously, and the clustering methods are compared with one another in terms of the computation efficiency. It turns out that the model reduction by any clustering method is effective to enhance the computation efficiency when importance is given to minimizing the first objective function. It also turns out that the model reduction only by the k- medoids method is effective very limitedly when importance is given to minimizing the second objective function. Y1 - 2020 SP - 627 EP - 639 ER - TY - GEN A1 - Petkovic, Milena A1 - Zakiyeva, Nazgul T1 - Mathematical Optimization for Analyzing and Forecasting Nonlinear Network Time Series N2 - This work presents an innovative short to mid-term forecasting model that analyzes nonlinear complex spatial and temporal dynamics in energy networks under demand and supply balance constraints using Network Nonlinear Time Series (TS) and Mathematical Programming (MP) approach. We address three challenges simultaneously, namely, the adjacency matrix is unknown; the total amount in the network has to be balanced; dependence is unnecessarily linear. We use a nonparametric approach to handle the nonlinearity and estimate the adjacency matrix under the sparsity assumption. The estimation is conducted with the Mathematical Optimisation method. We illustrate the accuracy and effectiveness of the model on the example of the natural gas transmission network of one of the largest transmission system operators (TSOs) in Germany, Open Grid Europe. The obtained results show that, especially for shorter forecasting horizons, the proposed method outperforms all considered benchmark models, improving the average nMAPE for 5.1% and average RMSE for 79.6% compared to the second-best model. The model is capable of capturing the nonlinear dependencies in the complex spatial-temporal network dynamics and benefits from both sparsity assumption and the demand and supply balance constraint. T3 - ZIB-Report - 22-19 KW - nonlinear time series KW - mathematical optimization KW - energy networks Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-88037 SN - 1438-0064 ER - TY - GEN A1 - Hosoda, Junko A1 - Maher, Stephen J. A1 - Shinano, Yuji T1 - Combining Benders’ decomposition and parallelisation to solve large-scale adaptive network supply chain management problems N2 - Integrated supply chain network design—combining warehouse clustering with inter- and intra-cluster vehicle routing—is a fundamental feature of supply chain management problems. In this paper, a Benders’ decomposition-based parallel heuristic approach for the integrated long-haul and local vehicle routing problem is proposed. The proposed algorithm comprises lower- and upper-bound search algorithms running in parallel to find high-quality solutions for challenging supply chain management problems. A novel Benders’ decomposition approach is proposed to aid the improvement in the lower bound for large-scale problems. The results demonstrate that the Benders’ decomposition approach is effective in finding strong lower bounds and is beneficial for obtaining high-quality solutions. T3 - ZIB-Report - 24-12 Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-98744 SN - 1438-0064 ER - TY - GEN A1 - Fujii, Koichi A1 - Kim, Sunyoung A1 - Kojima, Masakazu A1 - Mittelmann, Hans D. A1 - Shinano, Yuji T1 - The Largest Unsolved QAP Instance Tai256c Can Be Converted into A 256-dimensional Simple BQOP with A Single Cardinality Constraint N2 - Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB; a 1.48% gap remains between the best known feasible objective value and lower bound of the unknown optimal value. This paper shows that the instance can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92.The converted BQOP is much simpler than the original QAP tai256c and it also inherits some of the symmetry properties. However, it is still very difficult to solve. We present an efficient branch and bound method for improving the lower bound effectively. A new lower bound with 1.36% gap is also provided. T3 - ZIB-Report - 22-18 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-88086 SN - 1438-0064 ER - TY - JOUR A1 - Shimada, Naoki A1 - Mako, Sato A1 - Yaegashi, Yuta A1 - Koch, Thorsten A1 - Le, Thi Thai T1 - An Application of Modified S-CLSVOF Method to Kelvin-Helmholtz Instability and Comparison with Theoretical Result JF - Journal of Chemical Engineering of Japan N2 - This study focuses on validating a two-phase flow solver based on the modified Simple Coupled Level Set and Volume of Fluid method (Uchihashi et al. (2023)) through viscous Kelvin-Helmholtz instability simulations. Our numerical simulation results are compared with the ones given by Funada and Joseph (2001) to provide reliable predictions of interface behavior under the influence of viscosity. The primary goal is to accurately assess the solver's ability to replicate theoretical analysis of interface behaviors under various conditions. First, the wave between two fluids of identical density is calculated. In addition, the effect of surface tension is investigated. By comparing growth rates, numerical simulations obtain well-agreements with the analytical results on the effect of the fluid viscosity, the wave number, and the surface tension. Finally, fluid density is changed to an air-water system. When relative velocity U is smaller than the criteria of relative velocity U_c given by analytical solutions, the wave is not broken. However, waves are splashed into droplets in the condition of U>U_c. This result agrees with the analysis by Funada and Joseph (2001). These findings provide a robust framework for applying the solver to more complex two-phase flow problems, supporting advancements in numerical simulations of fluid interfaces. Y1 - 2025 U6 - https://doi.org/10.1080/00219592.2025.2451953 VL - 58 IS - 1 PB - Taylor and Francis ER -