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2024 International Conference on Intelligent Robots and Systems

作者： Jaitly, Akshay Farzan, Siavash Worcester Polytech Inst Robot Engn Dept Worcester MA 01609 USA Calif Polytech State Univ San Luis Obispo Elect Engn Dept San Luis Obispo CA 93407 USA

ISBN: (纸本)9798350377712;9798350377705

Optimization methods for long-horizon, dynamically feasible motion planning in robotics tackle challenging non-convex and discontinuous optimization problems. Traditional methods often falter due to the nonlinear characteristics of these problems. We introduce a technique that utilizes learned representations of the system, known as Polytopic Action Sets, to efficiently compute long-horizon trajectories. By employing a suitable sequence of Polytopic Action Sets, we transform the long-horizon dynamically feasible motion planning problem into a linear Program. This reformulation enables us to address motion planning as a mixed integer linear Program (MILP). We demonstrate the effectiveness of a Polytopic Action-Set and Motion Planning (PAAMP) approach by identifying swing-up motions for a torque-constrained pendulum as fast as 0.75 milliseconds. This approach is well-suited for solving complex motion planning and long-horizon Constraint Satisfaction Problems (CSPs) in dynamic and underactuated systems such as legged and aerial robots.

关键词： mixed-integer linear programming

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Stochastic Optimization Model for Energy Management of a Hybrid Microgrid using mixed integer linear programming 21st

Stochastic Optimization Model for Energy Management of a Hyb...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Franke, G. Schneider, M. Weitzel, T. Rinderknecht, S. Tech Univ Darmstadt Inst Mechatron Syst Mech Engn Darmstadt Germany Tech Univ Darmstadt Inst Prod & Supply Chain Management Darmstadt Germany

In the context of increasing decentralization of the energy supply system, the concepts of microgrids are well suited to realise a reduction of CO2-emissions and create opportunities for new business models. For this the operation of the microgrid has a significant impact. In real systems, however, the consideration of uncertainties in generation and consumption data is essential for the operating strategy. Therefore, in this paper we propose an optimization model based on mixed-integer linear programming for the hybrid microgrid of a residential building district and include stochastic optimization in a computationally efficient way. For this, a two-stage approach is used. In a first step, we do a day-ahead optimization to determine a schedule for the combined heat and power plant and the power exchanged with the grid. In a second step, based on the results of the day-ahead optimization and the observed values for the uncertain parameters the intraday optimization is carried out. Using a numerical example, we demonstrate the advantages of this stochastic optimization over conventional optimization based on point forecasts. The data used originates from a real project district in Darmstadt, Germany. Copyright (C) 2020 The Authors.

关键词： Residential micro grid battery energy storage system optimal operating strategy mixed-integer linear programming stochastic optimization

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Peak Load Shaving in Virtual Power Plants Utilizing mixed integer linear programming 7

Peak Load Shaving in Virtual Power Plants Utilizing Mixed In...

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7th IEEE Student Conference on Electric Machines and Systems, SCEMS 2024

作者： Zhu, Haoze He, Yaoming Xu, Dali Guan, Kesi Zhao, Xunan State Grid Liaoning Electric Power Co. Ltd Anshan Power Supply Company Anshan China

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366945

This paper proposes a virtual power plant (VPP) peak load shaving control strategy that takes into account both safety and economic factors, aiming to reduce operational costs for the power system. By employing mixed integer linear programming (MILP), the strategy minimizes energy and demand charges, effectively shaving peak load demands. It optimizes embedded energy resources (EERs), including distributed energy storage (DES) and renewable energy sources (RES), to decrease load during peak times. Additionally, demand response (DR) is utilized during peak periods to limit the use of consumers' electric water heaters (EWH), heat pumps (HP), and baseboard heater (BBH). The results demonstrate that the proposed control strategy can shave up to three daily load peaks, meeting the requirements for safety and reliability while enhancing the economic benefits for power companies and consumers. © 2024 IEEE.

关键词： mixed-integer linear programming

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A New Planning Model for Optimal Feeder Routing of Radial Distribution System Using mixed integer linear programming Technique 25

A New Planning Model for Optimal Feeder Routing of Radial Di...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Shazly, Shazly Ahmed Mahmoud, Hassan Mohamed Albags, Mohamed Shibl Elzawawy, Ahmed Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Benha13511 Egypt Nahda University Faculty of Engineering Department of Electrical Engineering Beni Suef62511 Egypt

ISBN: (纸本)9798350379648

Several studies have been focused on developing the distribution system planning techniques, varying from classical to nontraditional soft computing techniques, to solve the distribution system planning problem. This paper presents a new planning model for accurate mathematical planning to get optimum feeder routing of radial distribution systems using a mixed integer linear programming (MILP) technique. The model treats the loads at different load buses as injected power. The model also considers the ohmic power loss of various branches as a variable for optimization. All cost items (capital cost, energy loss cost, cost of bays, and line interruption cost) are considered. Also, bus voltage and line capacity limits are considered in addition to the different line sizes. Model verification has been made using two test examples. Lingo software is used to verify the proposed planning model. The developed model can be extended to deal with the general distribution planning problem in which both feeding substations and feeders can be optimized. In addition, it is very important for getting the optimal feeder routing of the system. © 2024 IEEE.

关键词： mixed-integer linear programming

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Fast Topology Identification of AC / DC Hybrid Distribution Network Based on mixed integer linear programming 2

Fast Topology Identification of AC / DC Hybrid Distribution ...

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2nd International Conference on Cyber-Energy Systems and Intelligent Energy, ICCSIE 2024

作者： Hu, Shiyao Feng, Xichun Kang, Xiaofan Ju, Yuntao Jiang, Jing Economic and Technical Research Institute State Grid Hebei Electric Power Co. Ltd Shijiazhuang China School of Electrical and Control Engineering North China University of Technology Beijing China State Grid Economic and Technological Research Institute Co. Ltd Beijing China

ISBN: (纸本)9798350373318

Topology identification is crucial for advanced analysis such as state estimation in hybrid AC/DC distribution networks. Traditional topology identification methods based on data statistics lack accuracy, and optimization-based methods exhibit low efficiency. To address these issues, a topology identification method based on mixed-integer linear programming is proposed. Initially, the normalized Lagrange multiplier is utilized to identify suspicious measurements, forming a set of suspicious measurements to reduce the number of integer variables to be determined. Subsequently, a linearization method for network constraints in hybrid AC/DC distribution networks is introduced to transform the topology identification problem into a mixed-integer linear programming model. The simulation results demonstrate that by constructing a set of suspicious measurements and linearizing network constraints, the efficiency of solving the problem is significantly improved while ensuring the accuracy of identification. © 2024 IEEE.

关键词： mixed-integer linear programming

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A mixed integer linear programming based optimal operational and sizing approach for a Hybrid Local Microgrid

A Mixed Integer Linear Programming based optimal operational...

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Hossain, Mohammad Shafayet Iftekhar Bin Ashraf, Mohammad Ahmed, Saif University of Lorraine Department of Energy France North South University Department of Electrical and Computer Engineering Bangladesh

ISBN: (纸本)9798331529765

Optimal sizing of microgrids is achieving higher importance in the current era of energy transition driven by renewable sources. Due to the intermittence of the renewable sources i.e. PV, wind assisted by energy storages i.e. battery the optimal sizing of the microgrids alonf with cost minimization is a great challenge. This study presents a methodological framework for determining the optimal configuration of a hybrid microgrid, integrating various energy resources such as photovoltaic (PV) generation, battery storage, a genset, and grid interconnection. Employing Pyomo optimization tool with a mixed-integer linear programming algorithm, the research focuses on sizing components within a 20 kW PV microgrid. Through meticulous examination of load demand and installed PV capacity, the algorithm strategically optimizes the sizing of PV panels, batteries, gensets, and grid interactions to minimize both capital expenditure (CAPEX) and operational expenditure (OPEX). The microgrid's performance is analyzed under three pricing schemes: net metering, selling excess energy to the grid (selling price less than buying price), and giving it away (zero price). Additionally, in off-grid mode, the total CO2 emissions are minimized. The proposed methodology offers a systematic approach for designing economically viable and efficient hybrid microgrids, essential for sustainable energy systems. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimal Sensor Placement and Battery Pack Configuration in Electrochemical Energy Storage Systems: A mixed-integer Non-linear programming Approach 3

Optimal Sensor Placement and Battery Pack Configuration in E...

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3rd International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024

作者： Wei, Shibo Jiang, Liping Zhang, Xiaojun Zhang, Jingwen Tian Di Technology Co. Ltd. CCTEG Beijing Technology Research Branch Beijing100013 China Xiaoshan District Fire Rescue Brigade Hangzhou311201 China West Lake Scenic Area Fire Rescue Brigade Hangzhou311607 China Chinese Institute of Coal Science CCTEG Beijing100013 China

ISBN: (纸本)9798331528386

The integration of electrochemical energy storage (EES) systems in diverse applications from portable devices to grid storage is crucial for the transition to sustainable energy sources. Efficient battery management is vital for optimizing performance and ensuring safety, with a focus on the strategic placement of sensors and battery pack configuration. This paper introduces a mixed-integer nonlinear programming (MINLP) model that optimizes these aspects by considering three-dimensional spatial configurations and diverse battery types. The model aims to minimize costs while ensuring comprehensive coverage and stringent safety standards. It extends beyond traditional methods by incorporating adaptive strategies that enhance predictive capabilities and operational efficiency. By applying this model in detailed case studies, the paper demonstrates significant improvements in cost efficiency and system reliability, offering a robust framework for enhancing battery management systems in various technological and operational settings. This approach not only addresses current challenges but also adapts to dynamic conditions, highlighting its potential to significantly impact the future of energy storage solutions. © 2024 IEEE.

关键词： mixed-integer linear programming

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An integrated mixed integer linear programming model for resilient and sustainable natural gas supply chain

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ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY 2022年第1期17卷 Article: 2118901页

作者： Emenike, Scholastica N. Ioannou, Anastasia Falcone, Gioia Univ Glasgow James Watt Sch Engn Glasgow G12 8QQ Lanark Scotland

Disruptions in the natural gas supply chain result in reduced throughput and associated emissions and losses, causing significant economic, environmental, and social impacts. Therefore, it is crucial to design supply chains that are resilient and sustainable to prevent or reduce the effects of disruptions. This paper proposes a novel mixed-integer linear programming model, which optimizes the natural gas supply chain in terms of resilience and sustainability, by examining the impact of an additional workflow design (contingency pipeline) located between the shutdown inlet and outlet nodes in the transmission echelon. The model is applied to a "real world" case, using data collected from gas companies operating in Nigeria. Both steady and transient states of the system are examined in this study through a set of scenarios. The best final solution was found to yield 93.6% performance increase when compared to target throughput and 63% performance increase with the introduction of the contingency when compared with the baseline scenario.

关键词： Natural gas Supply chain Optimization mixed-integer linear programming Resilience Sustainability

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Stochastic Optimization Model for Energy Management of a Hybrid Microgrid using mixed integer linear programming

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IFAC-PapersOnLine 2020年第2期53卷 12948-12955页

作者： G. Franke M. Schneider T. Weitzel S. Rinderknecht Technische Universität Darmstadt Institute for Mechatronic Systems in Mechanical Engineering Germany Technische Universität Darmstadt Institute of Production and Supply Chain Management Germany

In the context of increasing decentralization of the energy supply system, the concepts of microgrids are well suited to realise a reduction of CO 2 -emissions and create opportunities for new business models. For this the operation of the microgrid has a significant impact. In real systems, however, the consideration of uncertainties in generation and consumption data is essential for the operating strategy. Therefore, in this paper we propose an optimization model based on mixed-integer linear programming for the hybrid microgrid of a residential building district and include stochastic optimization in a computationally efficient way. For this, a two-stage approach is used. In a first step, we do a day-ahead optimization to determine a schedule for the combined heat and power plant and the power exchanged with the grid. In a second step, based on the results of the day-ahead optimization and the observed values for the uncertain parameters the intraday optimization is carried out. Using a numerical example, we demonstrate the advantages of this stochastic optimization over conventional optimization based on point forecasts. The data used originates from a real project district in Darmstadt, Germany.

关键词： Residential micro grid battery energy storage system optimal operating strategy mixed-integer linear programming stochastic optimization

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Optimal Operational Adjustment of a Community-Based Off-Grid Polygeneration Plant using a Fuzzy mixed integer linear programming Model

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ENERGIES 2019年第4期12卷 636-636页

作者： Ubando, Aristotle T. Marfori, Isidro Antonio V., III Aviso, Kathleen B. Tan, Raymond R. De La Salle Univ Mech Engn Dept 2401 Taft Ave Manila 0922 Philippines De La Salle Univ Chem Engn Dept 2401 Taft Ave Manila 0922 Philippines

Community-based off-grid polygeneration plants based on micro-hydropower are a practical solution to provide clean energy and other essential utilities for rural areas with access to suitable rivers. Such plants can deliver co-products such as purified water and ice for refrigeration, which can improve standards of living in such remote locations. Although polygeneration gives advantages with respect to system efficiency, the interdependencies of the integrated process units may come as a potential disadvantage, due to susceptibility to cascading failures when one of the system components is partially or completely inoperable. In the case of a micro-hydropower-based polygeneration plant, a drought may reduce electricity output, which can, in turn, reduce the level of utilities available for use by the community. The study proposes a fuzzy mixed-integer linear programming model for the optimal operational adjustment of an off-grid micro-hydropower-based polygeneration plant seeking to maximize the satisfaction levels of the community utility demands, which are represented as fuzzy constraints. Three case studies are considered to demonstrate the developed model. The use of a diesel generator for back-up power is considered as an option to mitigate inoperability during extreme drought conditions.

关键词： off-grid polygeneration micro-hydropower plant fuzzy optimization mixed-integer linear programming dual-turbine multi-objective

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