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Techno-economic relevance of absorption chillers to enhance existing 3GDH

ENERGY REPORTS 2021年 7卷 282-293页

作者： Nerot, B. Lamaison, N. Baviere, R. Lacarriere, B. Mabrouk, M. T. Univ Grenoble Alpes CEA Liten Campus Ines F-73375 Le Bourget Du Lac France Univ Grenoble Alpes CEA Liten DTCH F-38000 Grenoble France IMT Atlantique GEPEA Dept Energy Syst & Environm F-44307 Nantes France

This article studies the economical, technical and environmental aspects of a third generation district heating (DH) network with absorption chillers installed at substation level in order to satisfy the cooling demands. This network solution hence takes advantage of the distribution facilities of existing DH systems. The study aims at evaluating the technical and environmental performances of this new district heating architecture, when sized and operated according to an economic objective using the mixed integer linear programming (MILP) optimization formalism. It is compared to the case where cooling demands are met using individual chillers. The paper first presents the production, distribution, demand and storage models. Regarding the demand side, different heating and cooling scenarios are studied by varying the proportions of residential and tertiary buildings. The model is fed in a second part with data from the French context. In particular, we rely on typical French weather conditions, thermal loads and energy costs. The analysis of the results focuses on the cooling part. It appears that the thermal network solution achieves on average a 3.6% reduction in the levelized cost of space cooling energy. In the worst case space cooling exergy efficiency goes through a 82% decrease. GHG emissions decrease on average by 7.7% thanks to the absence of leakage of refrigerant with high global warming potential. Overall, these emissions are low due to the low carbon content of French electricity. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： District heating Transition Space cooling Absorption chiller mixed-integer linear programming French context

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A robust model for supplying LNG from different contracts considering overall and incremental discount options

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2021年第15期43卷 1805-1824页

作者： Yazdi, Amir Karbassi Komijan, Alireza Rashidi Raissi, Sadigh Modiri, Mahmoud Islamic Azad Univ Dept Ind Management South Tehran Branch Tehran Iran Islamic Azad Univ Firoozkoh Branch Dept Ind Engn Firoozkoh Iran Islamic Azad Univ Dept Ind Engn South Tehran Branch Tehran Iran

In order to transport natural gas to long distances, it is economical that the natural gas is converted into the liquefied natural gas (LNG). Several countries look forward to conclude the contract for purchasing LNG. In the present research paper, it was assumed that a customer (country) would be provided LNG due to its high demand for a long period. Different contracts that include overall and incremental discount options have been offered to the customers by different vendors. In addition, the customer may consider meeting a certain part of the demand from the spot market. Three factors are important while concluding the LNG contracts: the evaporation rate, the quality, and the operational costs. In the present study, first, the best level of each factor was concluded by utilizing the LINMAP method, following which a robust model was presented in order to determine the amount of LNG that should be purchased from each contract as well as from the spot market. The mathematical model was tested through a numerical example which included 10 contracts with different options.

关键词： Liquefied Natural Gas (LNG) LINMAP robust optimization mixed-integer linear programming

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Data-driven multi-layered intelligent energy management system for domestic decentralized power distribution systems

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JOURNAL OF BUILDING ENGINEERING 2023年 68卷

作者： Rahim, Sahar Ahmad, Haseeb COMSATS Univ Islamabad Dept Elect & Comp Engn Wah Campus Rawalpindi Punjab Pakistan Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China

Energy management techniques have been immensely adopted in residential, industrial, and commercial sectors to meritoriously flatten the load profile of consumers. In this article, a cutting-edge intelligent energy management system is proposed to analytically monitor and regulate the load demand of a residential area to meritoriously address the load balancing and scheduling optimization problem with an aim to design an autonomous domestic complex, less reliant on the focal power grid. To do so, single-and multi-objective functions are defined for the presented double-layered framework. In the first layer, a day-ahead scheduling problem is evaluated to achieve the mutual revenue of electricity utilities and consumers, while in the second layer, a real-time coordination scheme for robust energy transactions among appliances, multiple microgrids, and the main power system is examined. Herein, a 0 - 1 multiple knapsack problem incorporated with the mixed-integer linear programming method is used to formulate the system mathematical model. To evaluate the intended system model, three heuristic algorithms (genetic algorithm, wind-driven optimization, and their hybrid) are modified. Furthermore, the Monte-Carlo simulations are performed to mitigate the impact of randomness and avoid pre-convergence. From the results of extensive simulations, it is corroborated that the proposed methodology is robust, reliable, and eco-social compared to prior schemes. This article reveals that the hybrid approach outperformed the other two strategies in terms of energy consumption, electricity cost, peak-to-average ratio, and user comfort level.

关键词： Demand response Microgrid Genetic algorithm Wind-driven optimization 0 1 Multiple knapsack problems mixed-integer linear programming

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Enabling Research through the SCIP Optimization Suite 8.0

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ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE 2023年第2期49卷 22-22页

作者： Bestuzheva, Ksenia Besancon, Mathieu Chen, Wei-Kun Chmiela, Antonia Donkiewicz, Tim Van Doornmalen, Jasper Eifler, Leon Gaul, Oliver Gamrath, Gerald Gleixner, Ambros Gottwald, Leona Graczyk, Christoph Halbig, Katrin Hoen, Alexander Hojny, Christopher Van Der Hulst, Rolf Koch, Thorsten Luebbecke, Marco Maher, Stephen J. Matter, Frederic Muehmer, Erik Mueller, Benjamin Pfetsch, Marc E. Rehfeldt, Daniel Schlein, Steffan Schloesser, Franziska Serrano, Felipe Shinano, Yuji Sofranac, Boro Turner, Mark Vigerske, Stefan Wegscheider, Fabian Wellner, Philipp Weninger, Dieter Witzig, Jakob Zuse Inst Berlin Dept AIS2T Takustr 7 D-14195 Berlin Germany Beijing Inst Technol Sch Math & Stat 5 Zhongguancun South St Beijing 100081 Peoples R China Rhein Westfal TH Aachen Lehrstuhl Operat Res Kackertstr 7 D-52072 Aachen Germany Eindhoven Univ Technol Dept Math & Comp Sci POB 513 NL-5600 MB Eindhoven Netherlands Zuse Inst Berlin Dept ZIB AIS2T & I2DAMO GmbH Englerallee 19 D-14195 Berlin Germany Friedrich Alexander Univ Erlangen Nurnberg Dept Data Sci Cauerstr 11 D-91058 Erlangen Germany Univ Twente Dept Discrete Math & Math Programming POB 217 NL-7500 AE Enschede Netherlands Tech Univ Berlin Chair Software & Algorithms Discrete Optimizat Str 17 Juni 135 D-10623 Berlin Germany ZIB Dept A2IM Takustr 7 D-14195 Berlin Germany Univ Exeter Coll Engn Math & Phys Sci Harrison BldgStreatham CampusN Pk Rd Exeter EX4 4QF England Tech Univ Darmstadt Fachbereich Math Dolivostr 15 D-64293 Darmstadt Germany Zuse Inst Berlin Dept A2IM Takustr 7 D-14195 Berlin Germany Tech Univ Berlin Berlin Germany Zuse Inst Berlin GAMS Software GmbH Dept AIS2T Takustr 7 D-14195 Berlin Germany

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this article is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP's application as a research tool and as a platform for further developments. Furthermore, this article gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon SCIP.

关键词： Constraint integer programming linear programming mixed-integer linear programming mixed-integer nonlinear programming optimization solver branch-and-cut branch-and-price column generation parallelization mixed-integer semidefinite programming

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An Economic Dispatch for a Shared Energy Storage System Using MILP Optimization: A Case Study of a Moroccan Microgrid

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ENERGIES 2023年第12期16卷 4601-4601页

作者： El Barkouki, Bouthaina Laamim, Mohamed Rochd, Abdelilah Chang, Jae-won Benazzouz, Aboubakr Ouassaid, Mohammed Kang, Moses Jeong, Hakgeun Green Energy Pk Reg Rd Kelaa Km 3R206 Benguerir 43150 Morocco Mohammed V Univ Rabat Engn Smart & Sustainable Syst Res Ctr Mohammadia Sch Engineers Rabat 10090 Morocco Univ Hassan 2 LSIB Lab FST Mohammadia 28806 Morocco Hassan II Univ Casablanca Elect Engn & Intelligent Syst Lab ENSET Mohammedia Mohammadia 28830 Morocco Korea Inst Energy Res 152 Gajeong Ro Daejeon 34129 South Korea

Energy storage systems are an effective solution to manage the intermittency of renewable energies, balance supply, and demand. Numerous studies recommend adopting a shared energy storage system (ESS) as opposed to multiple single ESSs because of their high prices and inefficiency. Thus, this study examines a shared storage system in a grid-connected microgrid. By modifying the power outputs of the energy resources, this work intends to implement an economic dispatch of a shared ESS in order to satisfy the power balance and lower the overall cost of electricity. In this context, an optimization problem was formulated and developed using a mixed-integer linear programming (MILP) model. Furthermore, a pilot project (the Solar Decathlon Africa Village) in the Green & Smart Building Park (GSBP), Benguerir, Morocco, was employed to evaluate and verify the proposed approach. Some comparable scenarios were therefore run in a MATLAB environment. The collected findings demonstrate the efficacy of the developed algorithm in terms of optimizing energy cost reductions and enhancing the integration of renewable resources into the Moroccan energy mix.

关键词： shared energy storage system energy management system economic dispatch microgrids mixed-integer linear programming power system

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Technoeconomic and environmental optimization of combined heat and power systems with renewable integration for chemical plants

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APPLIED THERMAL ENGINEERING 2023年第PartA期219卷

作者： Liu, Zuming Chakraborty, Arijit He, Tianbiao Karimi, Iftekhar A. Shanghai Jiao Tong Univ Coll Smart Energy Shanghai 200240 Peoples R China BITS Pilani Dept Chem Engn Goa Campus Sancoale 403726 Goa India China Univ Petr East China Coll Pipeline & Civil Engn Dept Gas Engn Qingdao Peoples R China Natl Univ Singapore Dept Chem & Biomol Engn 4 Engn Dr 4 Singapore 117585 Singapore

Chemical industry mainly uses fossil fuels as energy resources and thus causes substantial amount of carbon emissions. Combined heat and power (CHP) systems have become an effective solution for reducing energy consumption and carbon emissions. This paper presents a bi-objective mixed-integer linear programming framework for technoeconomic and environmental optimization of CHP systems for chemical plants, accounting for steam turbine network design and renewable integration. The bi-objective optimization problem is solved to achieve a trade-off between total annual cost (TAC) and carbon emissions. Two typical quad-pressure and dual-pressure chemical plants are employed for demonstration. The results show that the optimal CHP system has a TAC of 21.1 and 18.9 million USD as well as carbon emissions of 50 and 35 kton for quad-pressure and dual-pressure plants. Both systems feature a sharp reduction of 33.3% and 42.5% in emissions and a mild increase of 26.7% and 30.2% in TAC when comparing with TAC minimization. Moreover, we find that gas boiler is mainly responsible for carbon emissions, and replacing it with electric boilers is an promising alternative for further emission mitigation. We observe that photovoltaics capital price has a significant impact on system TAC and emissions, while employing only carbon tax is unable to achieve deep decarbonization. Hence, we recommend combining system design, renewable technology advances, and carbon tax synergistically for chemical industry decarbonization. Our methodology provides an effective and flexible framework for further investigation of decarbonization.

关键词： Combined heat and power System integration Renewable energy mixed-integer linear programming Multi-objective optimization

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A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market

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ENERGIES 2023年第20期16卷 7061页

作者： Cha, Seong-Hyeon Kwak, Sun-Hyeok Ko, Woong Changwon Natl Univ CWNU Dept Elect Engn 20 Changwondaehak Ro Chang Won 51140 South Korea

As the share of distributed generation increases, so do the opportunities for aggregators to participate in the electricity market. In particular, aggregators participating in both the day-ahead and real-time markets contribute to improving the reliability of the power system. In addition, aggregators seeking additional revenue can benefit from providing reserves in a joint electricity market environment. However, aggregated resources with uncertainty are limited because of the uncertain nature of both reserve provision and the amount of reserves they can provide. Therefore, this study proposes a robust optimization model for an aggregator to formulate a strategy for participation in the day-ahead markets and deploys energy control in the real-time operation. The serving ratio reflects the availability of the aggregator's reserve participation. Both the deployed up/down power and renewable energy in the real-time operation are considered as uncertain parameters to reflect the uncertainty. In the case study, we analyze the profit-maximization strategy of an aggregator that owns renewable energy resources and energy-storage systems under the variation interval for uncertain parameters and the serving ratio. The bidding strategies vary by the variation interval and the serving ratio.

关键词： aggregator day-ahead markets joint electricity market mixed-integer linear programming real-time operation reserve robust optimization serving ratio uncertainty

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A time-bucket MILP formulation for optimal lot-sizing and scheduling of real-world chemical batch plants

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COMPUTERS & CHEMICAL ENGINEERING 2023年第1期177卷

作者： Wallrath, R. Seeanner, F. Lampe, M. Franke, M. B. Bayer AG Kaiser Wilhelm Allee 1 D-51368 Leverkusen Germany SimPlan Syst GmbH Sophie Scholl Pl 6 D-63452 Hanau Germany Univ Twente Fac Sci & Technol Sustainable Proc Technol Proc Design & Optimizat Drienerlolaan 5 NL-7522 NB Enschede Netherlands

We propose a new time-bucket MILP model for lot-sizing and scheduling problems arising in chemical batch plants. The main idea behind time-bucket models is to partition time into fixed-length macroperiods and flexible length microperiods, that lie within the macroperiods. We show that the time-bucket model benefits from advantages of both continuous and discrete time representations. It allows to include important real world constraints, can be solved with moderate computational effort, and thus promotes MILP for large-scale, industrial problems. We investigate the scalability of the model and apply it to a formulation and filling process from an industrial agrochemical production with 7 formulation lines, intermediate buffer tanks, and 7 filling lines. We optimize a one month period with 50 intermediates, and 83 finished products. A comparison of the MILP solution to a discrete event simulation solution shows that 17% of production capacity can be freed up and significant improvement in on-time delivery.

关键词： mixed-integer linear programming Time-bucket formulation Lot-sizing and scheduling Chemical batch plants Flow shop optimization Multi-stage manufacturing process

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Integrated Reinforcement Learning and Optimization for Railway Timetable Rescheduling

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IFAC-PapersOnLine 2024年第10期58卷 310-315页

作者： Hengkai Zhang Xiaoyu Liu Dingshan Sun Azita Dabiri Bart De Schutter Delft Center for Systems and Control Delft University of Technology 2628CD Delft The Netherlands

The railway timetable rescheduling problem is regarded as an efficient way to handle disturbances. Typically, it is tackled using a mixed integer linear programming (MILP) formulation. In this paper, an algorithm that combines both reinforcement learning and optimization is proposed to solve the railway timetable rescheduling problem. Specifically, a value-based reinforcement learning algorithm is implemented to determine the independent integer variables of the MILP problem. Then, the values of all the integer variables can be derived from these independent integer variables. With the solution for the integer variables, the MILP problem can be transformed into a linear programming problem, which can be solved efficiently. The simulation results show that the proposed method can reduce passenger delays compared with the baseline, while also reducing the solution time.

关键词： Railway timetable rescheduling mixed-integer linear programming reinforcement learning

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Robust Topology Control of AC Power Networks With Injection Uncertainties

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IEEE Transactions on Power Systems 2025年

作者： Tiwari, Anamika Mohapatra, Abheejeet Sahoo, Soumya Ranjan Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Energy Technologies Area Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Integration of Renewable Energy Sources (RES) prompts a need for increased grid flexibility. While Optimal Transmission Switching (OTS) harnesses this flexibility, deterministic OTS fails to provide optimal topology for injection uncertainties from loads and RESs. This paper presents a novel two-level, three-stage formulation for robust AC OTS (ACOTS), addressing injection uncertainties in the day-ahead operation of power networks. Unlike previous formulations, the proposed model has no approximations of power flow equations. The master problem is a mixed integer linear programming (MILP) formulation that determines robust optimal network topology, serving as input to slave problems. The slave problems are solved sequentially, where the first slave is a deterministic AC Optimal Power Flow (ACOPF) problem, and the second slave unveils worst-case uncertainty, thereby co-optimizing dispatch in the considered uncertainty range. The proposed formulation is solved by Generalized Benders decomposition, which is devised with an accelerated convergence technique. Consideration of budget of uncertainty constraints reduces conservatism of optimal topology. Validation through Monte-Carlo Simulation-based ACOPF, appended with load curtailment, demonstrates the setpoints' robustness on NESTA and South Carolina 500 bus systems. Comparison with previous approaches and the Column-and-Column Constraint Generation (C&CG) algorithm underscores the proposed model's effectiveness in achieving a robust optimal network topology. © 1969-2012 IEEE.

关键词： mixed-integer linear programming

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