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American Control Conference (ACC)

作者： Nasim Baharisangari Narendhiran Saravanane Zhe Xu School for Engineering of Matter Transport and Energy Arizona State University Tempe AZ

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We propose a distributed differentially private receding horizon control (RHC) approach for multi-agent systems (MAS) with metric temporal logic (MTL) specifications. In the MAS considered in this paper, each agent privatizes its sensitive information from other agents using a differential privacy mechanism. In other words, each agent adds privacy noise (e.g., Gaussian noise) to its output to maintain its privacy. We define two types of MTL specifications for the MAS: agent-level specifications and system-level specifications. Agents should collaborate to satisfy the system-level MTL specifications while each agent must satisfy its own agentlevel MTL specifications at the same time. In the proposed distributed RHC approach, each agent communicates with its neighboring agents to acquire their estimate of the system-level trajectory and updates its estimate of the system-level trajectory. Then, each agent synthesizes its own control inputs such that the system-level specifications are satisfied with a probabilistic guarantee while the agent-level specifications are also satisfied with a deterministic guarantee. In the proposed optimization formulation of RHC, we directly incorporate Kalman filter equations to calculate the system-level trajectory estimates. We use mixed-integer linear programming (MILP) to encode the MTL specifications as optimization constraints. Finally, we implement the proposed distributed RHC approach in two scenarios.

关键词： Privacy System dynamics Probabilistic logic Robustness Mathematical models Trajectory mixed integer linear programming

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Learning Heuristics Approaches in mixed integer linear Programing

Learning Heuristics Approaches in Mixed Integer Linear Progr...

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International Conference on Computers, Communications, and Systems (ICCCS)

作者： Zhilei Wang Wentao Song Yang Lei Yu Wang Naijie Gu School of Computer Science and Technology University of Science and Technology of China Hefei China School of Data Science University of Science and Technology of China Hefei China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

mixed integer linear programming (MILP) technology is a versatile method used for formulating and solving combinatorial optimization problems. During the solving process, primal heuristics help to quickly find good feasible solutions, which can aid branch-and-bound (B&B) algorithms in reducing the primal-dual gap and pruning the B&B search tree. The heuristics employed by existing open-source solvers follow empirical rules summarized from real-world instances, enabling the solvers to achieve generally good performance but sometimes performing poorly on specific instances. In response, this paper proposes a method that uses hierarchical sequence models to learn the patterns of given instances and assigns a heuristic configuration for them. Compared to the default settings of the solver, the proposed method enables heuristic module to perform better, finding feasible solutions more quickly and reducing the primal-dual gap. Experimental results indicate that the proposed method can improve the solver's average performance on given instances by 27%.

关键词： Communication systems Heuristic algorithms Reinforcement learning Manuals mixed integer linear programming Task analysis Optimization

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A Hybrid Discrete Jaya Algorithm Based on Gene Expression programming for Heterogeneous Multi-Satellites Cooperative Observation

A Hybrid Discrete Jaya Algorithm Based on Gene Expression Pr...

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Artificial Intelligence and Automation Control (AIAC), International Conference on

作者： Junxiang Yang Lei He College of Systems Engineering National University of Defense Technology Changsha China

ISBN: (数字)9798331529147

ISBN: (纸本)9798331529154

In disaster observation, disasters with different characteristics have different degrees of demand for the selection of observation satellites, which directly affects the imaging quality, specifically involving the matching problem between mission types and satellite types. In this paper, for this Heterogeneous multi-Agile Earth Observation Satellites Scheduling Problem (HAEOSSP), a mixed integer linear programming model is established, and the time-dependent transition time and task matching are taken into account. To solve HAEOSSP, a Hybrid Discrete Jaya algorithm based on Gene Expression programming (HD-Jaya-GEP) method is designed to evolve task assignment rule. Coded with GEP, the Jaya algorithm is discretized by a neighborhood-based strategy, while the single-satellite task scheduling is solved by a mature meta-heuristic algorithm. Finally, simulation experiments are performed to evaluate the generalization of HD-Jaya-GEP, which validates the effectiveness and capability.

关键词： Earth Satellites Disasters Metaheuristics Imaging programming Scheduling mixed integer linear programming Gene expression Standards

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Multiobjective Optimization Model for Regime Adjustment in Crude Oil Production

Multiobjective Optimization Model for Regime Adjustment in C...

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Matías Micheletto Javier Marenco Rómulo Alcoleas Carlos De Marziani Rodrigo Santos IIDEPyS GSJ CONICET-UNPSJB Comodoro Rivadavia Universidad Torcuato Di Tell Buenos Aires UNPSJB Comodoro Rivadavia DIEC UNS ICIC CONICET-UNS Bahía Blanca

ISBN: (数字)9798331540975

ISBN: (纸本)9798331540982

production battery in the oil industry is a set of equipment and facilities used in the initial stages of crude oil processing at an oilfield. At various stages of operation, it may be necessary to restrict or increase its processing capacity, meaning that the gross volume to be received must be adjusted. In remote areas where connectivity and infrastructure may be limited, it is necessary for an operator to approach the well in person to make manual adjustments directly to the pumping system. Proper planning of the well route for adjusting regimes directly impacts the operating costs of the oilfield. In this work in progress, a mixed integer linear programming model for this problem is proposed, by considering the production, operation, and modification restrictions of the pumping regime of each well. Preliminary results are presented, which show that the model can be used in practice.

关键词： Costs Oils Computational modeling Optimization models Production Planning mixed integer linear programming Batteries Petroleum industry

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Evaluating the impact of passenger electric vehicle adoption on high renewable resources electricity grid

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RESOURCES CONSERVATION & RECYCLING ADVANCES 2023年 20卷

作者： Sambasivam, Balasubramanian Sundararaman, Malolan Univ Texas Austin Operat Res & Ind Engn Austin TX USA Univ Texas Austin Ctr Transportat Res Austin TX 78759 USA Natl Inst Technol Dept Management Studies Trichy India

A considerable amount of electricity is additionally demanded for Electric Vehicle (EV) charging due to rapid EV penetration. This study explores the impact of time of charging for different levels of passenger EV penetration on the electricity system using a case study electricity system with high penetration of renewable energy resources. A simulation approach is proposed to determine the new demand profile due to EV charging. Next, a mixed integer linear programming model is formulated considering the operation schedules of conventional power plants to mimic the real-time status of the electricity system. Finally, the developed approach considers the different possible interventions of actual EVs available in the market and tries to determine their impact in a renewable energy-dominated electricity system. The results from the study show that it is emission-friendly to encourage night charging rather than day charging for the considered renewable energy-dominated case study electricity system.

关键词： Energy transitions Electricity load curves Electric vehicles mixed integer linear programming

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Strengthening Urban Power Grids: A Resilient Planning Approach to Improve Critical Load Survival in Extreme Events

Strengthening Urban Power Grids: A Resilient Planning Approa...

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IEEE International Conference on Energy Internet (ICEI)

作者： Guanxun Diao Jinping Liu Jiayu Liu Ying Wang Yin Xu Shanghai Municipal Electric Power Company State Grid China School of Electrical Engineering Beijing Jiaotong University Beijing China Shanghai Electric Power Research Institute State Grid Shanghai Municipal Electric Power Company China

ISBN: (数字)9798331523558

ISBN: (纸本)9798331523565

Extreme disasters can damage power infrastructure of urban power grids and lead to significant outages. Strengthening urban power grids by updating and building new lines, stations, and sources in planning stage can enhance the power grid resilience, thus improve critical load survival in extreme events. This paper proposes a planning approach to strength the urban power grid and improve resilience. First, the planning principles on the power supply to critical loads are proposed to ensure power service based on differentiated critical degree of loads. Second, the planning problem is formulated as a mixed integer linear program (MILP), maximizing the weighted number of critical loads with guaranteed power supply considering the length of power supply paths and minimizing planning budgets. The associated constraints on planning principles and budget limit are considered. Finally, the proposed method is validated on a practical multi-voltage level grid case. Simulation results indicate that the proposed method enables each critical load to receive multiple power supplies based on its importance which can help survive in extreme events.

关键词： Power supplies Disasters Simulation Power system dynamics Voltage Power grids Planning mixed integer linear programming Resilience Meteorology

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Analyzing the Operational Behavior of Standalone Grid-Scale Battery Energy Storage System (BESS): A Chhattisgarh State Case Study

Analyzing the Operational Behavior of Standalone Grid-Scale ...

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National Power Systems Conference (NPSC)

作者： Arvind Marandi Anoop Singh Sustainable Energy Engineering Department Indian Institute of Technology Kanpur India Department of Management Sciences Indian Institute of Technology Kanpur India

ISBN: (数字)9798331519568

ISBN: (纸本)9798331519575

The effective integration of renewable energy sources (RES) into the power grid is crucial for India's sustainable energy future. This paper presents a mixed-integer linear programming (MILP) model to optimize the unit commitment (UC) and economic dispatch (ED) of Chhattisgarh's power system, considering the projected demand for FY-26, upcoming generation capacity additions, and the assumed inclusion of two 200 MW/800 MWh BESS plants. The study analyzes the operational behavior of BESS under various scenarios, including high demand and high RE generation weeks. The results highlight the importance of BESS in peak shaving, load leveling, and managing the variability of RES, while also revealing limitations in addressing prolonged energy deficits. The findings contribute valuable insights for policymakers and stakeholders in the Indian power sector, emphasizing the need for strategic BESS integration to ensure grid stability and cost-effectiveness as RES penetration increases.

关键词： Analytical models Costs Power system stability Thermal force mixed integer linear programming Thermal analysis State of charge Optimization Thermal stability Load modeling

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A Dynamic Pyramidal Relaxation Method of AC OPF

A Dynamic Pyramidal Relaxation Method of AC OPF

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Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Yu-Yang Tang Liang Chen Hongbo Du Sheng-Jie Chen Caixia Kou Xiaomeng Ai Bo Zhou Academy of Mathematics and Systems Science Chinese Academy of Sciences Institute of Computational Mathematics and Scientific/Engineering Computing Beijing China College of Sciences Beijing University of Posts and Telecommunications Beijing China Academy of Mathematics and Systems Science Chinese Academy of Sciences Institute of Applied Mathematics Beijing China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Department of Industrial and Operations Engineering University of Michigan Ann Arbor United States

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

The Alternating Current Optimal Power Flow (AC OPF) is crucial for power system analysis, yet existing algorithms face challenges in meeting the diverse requirements of practical applications. This paper presents a Pyramidal Relaxation (PR) formulation of the Branch Flow Model (BFM) for AC OPF, where surface conical constraints are approximated through a union of tetrahedrons in a mixed integer linear programming (MILP) relaxation. To reduce problem size and to enhance computational efficiency, we proposed a Dynamic Pyramidal Relaxation (DPR) method, where the cuts (inner approximation and outer approximation) are adaptively added. In practice, the DPR method is embedded into a MILP commercial solver based on the branch-and-cut framework. Case studies in different test systems validate the effectiveness in terms of feasibility, accuracy, and efficiency of our proposed method.

关键词： Electrical engineering Computational modeling Power system dynamics Asia linear approximation Relaxation methods mixed integer linear programming

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Partial Context-Sensitive Pointer Integrity for Real-time Embedded Systems

Partial Context-Sensitive Pointer Integrity for Real-time Em...

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Real-Time Systems Symposium (RTSS)

作者： Yujie Wang Cailani Lemieux-Mack Thidapat Chantem Sanjoy Baruah Ning Zhang Bryan C. Ward Washington University in St. Louis Vanderbilt University Virginia Tech

ISBN: (数字)9798331540265

ISBN: (纸本)9798331540272

Safety- and mission-critical cyber-physical systems (CPSs) require temporal correctness to ensure safe physical behavior. This manifests as strict timing requirements, which cannot be missed at runtime. Counter-intuitively, this implies that real-time tasks can be delayed so long as they remain guaranteed to meet their deadlines. This paper explores how extra time in a schedule can be analytically recapitalized for the purpose of applying stronger security protection within individual tasks at compile time. This is achieved through the development of a partial context-sensitive pointer-integrity framework (ParCSPI). In this framework, more fine-grained policies can be enforced, with greater runtime overheads, where so doing does not violate real-time constraints. A whole-system optimization framework based upon a mixed-integer linear programming approach to fixed-priority response-time analysis is used to identify precisely which contexts can be checked within the available system-wide time while maximizing system-wide security. ParCSPI leverages Arm pointer authentication (PA) to encode context-based equivalence classes into the modifiers of the pointer signature and is implemented using a customized program analyzer and LLVM compiler passes. An evaluation of ParCSPI is presented that includes per-task and system-wide overhead and security tradeoffs, as well as a demonstration on a real-world CPS. Empirical results are presented showing that ParCSPI achieves up to 62% pointer-integrity protection with only 10% worst-case execution time (WCET) overhead, and can find optimal security trade-offs in complex real-time task sets as well as approximate them in reasonable time.

关键词： Schedules Runtime Program processors Prototypes Real-time systems Timing mixed integer linear programming Security Protection Optimization

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Constraint-Aware Resource Management for Cyber-Physical Systems

Constraint-Aware Resource Management for Cyber-Physical Syst...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Justin McGowen Ismet Dagli Neil T. Dantam Mehmet E. Belviranli Computer Science Department Colorado School of Mines

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Cyber-physical systems (CPS) such as robots and self-driving cars pose strict physical requirements to avoid failure. Scheduling choices impact these requirements. This presents a challenge: how do we find efficient schedules for CPS with heterogeneous processing units, such that the schedules are resource-bounded to meet the physical requirements? We propose the creation of a structured system, the Constrained Autonomous Workload Scheduler, which determines scheduling decisions with direct relations to the environment. By using a representation language (AuWL), Timed Petri nets, and mixed-integer linear programming, our scheme offers novel capabilities to represent and schedule many types of CPS workloads, real world constraints, and optimization criteria.

关键词： Schedules Processor scheduling Petri nets Cyber-physical systems mixed integer linear programming Autonomous automobiles Resource management

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