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Closed loop model predictive control of a hybrid battery-hydrogen energy storage system using mixed-integer linear programming

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ENERGY CONVERSION AND MANAGEMENT-X 2024年 22卷

作者： Holtwerth, Alexander Xhonneux, Andre Mueller, Dirk Forschungszentrum Julich Inst Energy & Climate Res Energy Syst Engn IEK 10 Wilhelm Johnen Str D-52428 Julich Germany Rhein Westfal TH Aachen Inst Energy Efficient Bldg & Indoor Climate E ON Energy Res Ctr Mathieustr 10 D-52074 Aachen Germany

The derivation of an efficient operational strategy for storing intermittent renewable energies using a hybrid battery-hydrogen energy storage system is a difficult task. One approach for deriving an efficient operational strategy is using mathematical optimization in the context of model predictive control. However, mathematical optimization derives an operational strategy based on a non-exact mathematical system representation for a specified prediction horizon to optimize a specified target. Thus, the resulting operational strategies can vary depending on the optimization settings. This work focuses on evaluating potential improvements in the operational strategy for a hybrid batteryhydrogen energy storage system using mathematical optimization. To investigate the operation, a simulation model of a hybrid energy storage system and a tailor-made mixed integer linear programming optimization model of this specific system are utilized in the context of a model predictive control framework. The resulting operational strategies for different settings of the model predictive control framework are compared to a rulebased controller to show the potential benefits of model predictive control compared to a conventional approach. Furthermore, an in-depth analysis of different factors that impact the effectiveness of the model predictive controller is done. Therefore, a sensitivity analysis of the effect of different electricity demands and resource sizes on the performance relative to a rule-based controller is conducted. The model predictive controller reduced the energy consumption by at least 3.9 % and up to 17.9% compared to a rule-based controller. Finally, Pareto fronts for multi-objective optimizations with different prediction and control horizons are derived and compared to the results of a rule-based controller. A cost reduction of up to 47 % is achieved by a model predictive controller with a prediction horizon of 7 days and perfect foresight.

关键词： Model predictive control Optimization mixed integer linear programming Hybrid battery-hydrogen energy storage system

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Experiences with mixed integer linear programming-Based Approaches in Short-Term Hydro Scheduling

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IEEE Power Engineering Review 2001年第9期21卷 63-63页

作者： G. Chang M. Aganagic J. Waight J. Medina T. Burton S. Reeves M. Christoforidis National Chung Cheng University Taiwan Oracle Utility Verticle Siemens Power Systems Control ECNZ Southern Generation Group Power Plant Department Swiss Rail (SBB)

This paper describes experiences with mixed integer linear programming (MILP)-based approaches on the short-term hydro scheduling (STHS) function. The STHS is used to determine the optimal or near-optimal schedules for the dispatchable hydro units in a hydro-dominant system for a user-definable study period at each time step while respecting all system and hydraulic constraints. The problem can be modeled in detail for a hydro system that contains both conventional and pumped-storage units. Discrete and dynamic constraints such as unit startup/shutdown and minimum-up/minimum-down time limits are also included in the model for hydro unit commitment (HUC). The STHS problem is solved with a state-ofthe-art package that includes an algebraic modeling language and an MILP solver. The usefulness of the proposed solution algorithm is illustrated by testing the problem with actual hydraulic system data. Numerical experiences show that the solution technique is computationally efficient, simple, and suitable for decision support of short-term hydro operations planning. In addition, the proposed approaches can be easily extended for scheduling applications in deregulated environments.

关键词： Power generation economics Environmental economics Fuel economy Power generation Search methods mixed integer linear programming Processor scheduling Convergence Intelligent sensors Power system control

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Cost Optimization of Combined Building Heating/Cooling Equipment via mixed-integer linear programming

Cost Optimization of Combined Building Heating/Cooling Equip...

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American Control Conference

作者： Michael J. Risbeck Christos T. Maravelias James B. Rawlings Robert D. Turney University of Wisconsin-Madison Johnson Controls Milwaukee WI

ISBN: (纸本)9781479917730

In this paper, we propose a mixed-integer linear program to economically optimize equipment usage in a central heating/cooling plant subject to time-of-use and demand charges for utilities. The optimization makes both discrete on/off and continuous load decisions for equipment while determining utilization of thermal energy storage systems. This formulation allows simultaneous optimization of heating and cooling subsystems, which interact directly when heat-recovery chillers are present. Nonlinear equipment models are approximated as piecewise-linear to balance modeling accuracy with the computational constraints imposed by online implementation and to ensure global optimality for the computed solutions. The chief benefits of this formulation are its ability to tightly control on/off switching of equipment, its consideration of cost contributions from auxiliary equipment such as pumps, and its applicability to large systems with multiple heating and cooling units in which a combinatorial problem must be solved to pick the optimal mix of equipment. These features result in improved performance over heuristic scheduling rules or other formulations that do not consider discrete decision variables. We show optimization results for a system with four conventional chillers, two heat-recovery chillers, and one hot water boiler. With a timestep of 1 h and a horizon of 48 h, the optimization problem can be solved to optimality within 5 minutes, indicating suitability for online implementation.

关键词： EQUIPMENT CHILLER mixed integer linear programming Demand Charges Auxiliary equipment optimality Pumps

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mixed-integer linear programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty

Mixed-Integer Linear Programming (MILP) Approach for Solving...

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Power Engineering Application (ICPEA), IEEE International Conference in

作者： Nur Fauziyah Nanang Hariyanto School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with mixed integer linear programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.

关键词： Costs Uncertainty Coal Maintenance engineering mixed integer linear programming Thermal analysis Sulfur

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mixed-integer linear programming Model and Constraints Reduction Methods for Security-Constrained Unit Commitment

Mixed-Integer Linear Programming Model and Constraints Reduc...

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Sustainable Power and Energy Conference (iSPEC)

作者： Zhi Li Li Li Yanping Wang Guannan Bao Hanghang Liu Dapeng Liao Ruipeng Guo State Grid Jinan Power Supply Company Jinan Shandong China State Grid Shandong Electric Power Company Jinan Shandong China College of Electrical Engineering Zhejiang University Hangzhou Zhejiang China State Grid Dongying Power Supply Company Dongying Shandong China

ISBN: (数字)9781728191645

ISBN: (纸本)9781728191652

Security-constrained unit commitment (SCUC) is one of the most important daily tasks that must be accomplished in electric power market. To solve the SCUC problem efficiently, this paper proposes a mixed-integer linear programming (MILP) model and related constraints reduction methods. The proposed model includes both pre-and post-contingency security constraints, which are linearized by the DC power flow equation and the line outage distribution factor (LODF), respectively. The proposed constraints reduction methods reduce the security constraints of parallel branches by identifying the representative branches in each group of parallel branches, and eliminate the redundant post-contingency security constraints by analyzing the maximum possible values of post-contingency power flow. The correctness and effectiveness of the proposed model and methods are verified on 39 bus New England system and IEEE-118 test system.

关键词： Computational modeling Software mixed integer linear programming Mathematical model Security Task analysis Load flow

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Optimal Load Control and Scheduling through Distributed mixed-integer linear programming

Optimal Load Control and Scheduling through Distributed Mixe...

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Mediterranean Conference on Control and Automation (MED)

作者： Vassilios Yfantis William Motsch Nico Bach Achim Wagner Martin Ruskowski Department of Mechanical and Process Engineering Chair of Machine Tools and Control Systems Technische Universit&#x00E4 t Kaiserslautern Kaiserslautern Germany Technologie-Initiative SmartFactory KL e.V. Kaiserslautern Germany German Research Center for Artificial Intelligence (DFKI) Kaiserslautern Germany

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

This paper presents a mixed-integer linear programming-based optimization model for simultaneous optimal load control and scheduling of distributed systems coupled through their energy consumptions. The subsystems are able to adjust their energy consumption during the execution of a task and aim at minimizing their completion time and energy cost. The overall problem is solved in a distributed fashion, where each subsystem optimizes its individual operation without sharing sensitive information. To this end, dual decomposition is employed and a new algorithm to update the dual variables is presented. It relies on a transformation of the gradient of the quadratically approximated dual function and the subsequent solution of a regression problem. The proposed algorithm makes efficient use of information collected in previous iterations. The solution obtained from the distributed optimization of the subsystems is compared to both a decentral and a system-wide solution, showing that the distributed solution lies close to the global optimum of the process.

关键词： Energy consumption Costs Automation Approximation algorithms mixed integer linear programming Task analysis Optimization

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Simultaneous signal selection for silicon debug through mixed-integer linear programming

Simultaneous signal selection for silicon debug through Mixe...

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International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： R. Agalya S. Saravanan School of Computing SASTRA University Thanjavur India

ISBN: (纸本)9781467367264

Post-silicon validation is the most vital parts of modern Integrated Circuits. The key challenge of silicon validation is that it has limited observability and controllability of internal signals. To improve those, a profitable set of signals should be selected. An automated procedure is proposed to select those signals which are used to facilitate early malfunctions of the design. Given the input vector set to the design an error transmission matrix is generated. From that, both relatively independent and dependent flip-flops are identified for grouping the signals through mixed-integer linear programming. This method precisely identifies the paths which improves observability and can speed up the process.

关键词： Observability Computer bugs Silicon Flip-flops Controllability mixed integer linear programming linear programming

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Master Surgical Scheduling of Multi-Surgeon Surgical Schedules Using a mixed-integer linear programming Model and Genetic Algorithms

Master Surgical Scheduling of Multi-Surgeon Surgical Schedul...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Wanyok Atisattapong Podcharapol Pongpatcharapun Department of Mathematics and Statistics Faculty of Science and Technology Thammasat University Pathum Thani Thailand

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

The purpose of this work is to develop a master surgical scheduling for a case study of a large-scale public hospital in Thailand using a mixed-integer linear programming model (MILP) and a genetic algorithm (GA). Due to the high volume of operations that must be handled every day, our main objective is to create a schedule that maximizes OR utilization, minimizes room overtime, and reduces idle time between surgical patients. The data from Thammasat University Hospital were analyzed and simulated to generate a timetable from daily to weekly schedule. Our results show that an exact solution can be obtained by MILP for a simple problem while a large CPU run time is incurred for the complex problems. GA provided the optimal solution for a complex large-scale problem. The schedule generated by the proposed GA is more flexible and the staff can improve it to obtain more practical timetable in real-life situations, such as increasing the number of surgeries, setting a time block for specific surgical specialties, and handling emergency cases.

关键词： Schedules Hospitals Computational modeling Surgery linear programming Scheduling mixed integer linear programming Personnel Robots Genetic algorithms

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A mixed-integer linear programming Approach to Optimize Return Strategies in Remanufacturing System

A Mixed-Integer Linear Programming Approach to Optimize Retu...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Houria Lahmar Mohammed Dahane Kinza Nadia Mouss Mohammed Haoues Faculty of Technology University of Batna II Batna Algeria LGIPM Université de Lorraine Metz France

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This study addresses a production planning problem in a remanufacturing system, where the objective is to determine the amount of used products of different qualities that need to be recovered in order to produce remanufactured products that meet customer demands, while minimizing total costs, which include used product return costs, remanufacturing costs, start-up costs and storage costs. To achieve this objective, a new mixed-integer linear programming (MILP) model is developed for this problem. This model is evaluated through computational experiments conducted under different scenarios, considering limited or unlimited quantities of used products and different period lengths. The results of this study illustrate the effectiveness and efficiency of the proposed model in minimizing costs and meeting customer demands of remanufactured products.

关键词： Costs Systematics Computational modeling Production planning Production Mathematical models mixed integer linear programming Information technology

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mixed-integer linear programming based Maintenance Scheduling of Generating Units

Mixed-Integer Linear Programming based Maintenance Schedulin...

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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Ali Esmaeel Nezhad Pedro H.J. Nardelli Farideh Ghanavati Subham Sahoo Gerardo J. Osó rio Department of Electrical Engineering School of Energy Systems LUT University Lappeenranta Finland Department of Industrial Engineering and Management University of Aveiro Aveiro Portugal Department of Energy Technology Aalborg University Aalborg Denmark R. Dr. Ant&#x00F3 nio University Portucalense Infante D. Henrique (UPT) Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

This paper presents a mixed-integer linear programming model for the maintenance scheduling of generating units in the power system. The proposed model is investigated for weekly scheduling for one year addressing the crew availability constraint. The maintenance scheduling problem is modeled as an optimization problem to determine the optimal timing for handling the technical constraints of the power generation sector. In addition, the technical constraints for optimal scheduling of the tasks, like sequential tasks and rest time of the crews have been addressed in the scheduling management framework. The weekly peak power and spinning reserve have been considered in line with the economic issues for power generation in the whole system. The historical market clearing price (MCP) and mid-term load forecasting have been considered in the developed model.

关键词： Simulation Optimal scheduling Maintenance engineering Power systems mixed integer linear programming Timing Spinning

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