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ASME 15th International Conference on Energy Sustainability (ES)

作者： Upadhya, Sahana Wagner, Michael J. Univ Wisconsin Dept Mech Engn Energy Syst Optimizat Lab Madison WI 53706 USA

ISBN: (纸本)9780791884881

Recently, there has been an increased level of integration of renewable energy systems in existing power grids. Lack of integrated dispatch models has led to waste in power produced. This paper proposes a mixed-integer linear optimization model for hybrid renewable-generator-plus-battery systems, with the objective of maximizing long-term profit. Prior studies have revealed that both high and low state of charge (SOC) of the battery is detrimental to its lifetime and results in reduced battery capacity over time. In addition, increased number of cycles of charge and discharge also causes capacity reduction. This paper models these two factors with a constraint relating capacity loss to the SOC and number of cycles completed by the battery. Finally, the loss in capacity is penalized in the objective function of the optimization model, thereby indirectly penalizing high and low SOCs and frequent cycling. To overcome the computational difficulties of achieving global optimality, a rolling time horizon optimization approach is used. By incorporating battery degradation in the real-time model, the model is capable of maximizing the profits from the power dispatch to the grid while also maximizing the life of the battery. This paper exercises the model by assessing sample generator time series profiles with a range of battery capacities. The results demonstrate that the battery lifetime is extended in comparison to conventional models that ignore battery degradation in dispatch decisions. Finally, we analyze the relationship between operational parameters of the battery and the capacity fade.

关键词： energy storage energy systems analysis optimization and control simulation

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A new Simulation-Based Approach in the Design of Manufacturing Systems and Real-Time Decision 17th

A new Simulation-Based Approach in the Design of Manufacturi...

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17th IFAC Symposium on Information control Problems in Manufacturing (INCOM)

作者： Santos, Romao Toscano, Cesar de Sousa, Jorge Pinho INESC TEC Porto Portugal Univ Porto Fac Engn INESC TEC Porto Portugal

The principles and tools made available by the Industry 4.0, smart factories, or the Internet of Things (IoT), along with the adoption of more comprehensive simulation models, can significantly help the industry to face the current, huge external and internal challenges. This paper presents a new simulation-based approach to support decision making in the design and operational management of manufacturing systems. This approach is used to evaluate different layouts and resources allocation, and help managing operations, by integrating a simulation software with real-time data collected from the production assets through an IoT platform. The developed methodology uses a digital representation of the real production system (that may be viewed as a form of a digital twin) to assess different production scenarios. A set of key performance indicators (e.g. productivity) provided by the simulation can be used by the Manufacturing Execution System (MES) to generate production schedules. The developed approach was implemented and assessed in a real case study, showing its robustness and application potential. Its extension to other industrial contexts and sectors seems, therefore, quite promising. Copyright (C) 2021 The Authors.

关键词： Decision Support Systems Discrete Event Simulation Flexible and Reconfigurable Manufacturing Systems Line Design and Balancing optimization and control Performance Evaluation Real-time control

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A Dispatch optimization Model for Hybrid Renewable and Battery Systems Incorporating a Battery Degradation Model

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JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME 2022年第7期144卷 070907-070907页

作者： Upadhya, Sahana Wagner, Michael J. Univ Wisconsin Dept Mech Engn Energy Syst Optimizat Lab Madison WI 53706 USA

A recent increase in the integration of renewable energy systems in existing power grids along with a lack of integrated dispatch models has led to waste in power produced. This paper presents a mixed-integer nonlinear optimization model for hybrid renewable-generator-plus-battery systems, with the objective of maximizing long-term profit. Prior studies have revealed that both high and low state of charge (SOC) of the battery is detrimental to its lifetime and results in reduced battery capacity over time. In addition, increased number of cycles of charge and discharge also causes capacity reduction. This paper models these two factors with a constraint relating capacity loss to the SOC and number of cycles completed by the battery. Loss in capacity is penalized in the objective function of the optimization model, thereby disincentivizing high and low SOCs and frequent cycling. A rolling time horizon optimization approach is used to overcome the computational difficulties of achieving global optimality within a long-term time horizon. By incorporating battery degradation, the model is capable of maximizing the profits from the power dispatch to the grid while also maximizing the life of the battery. This paper exercises the model within a case study using a sample photovoltaic system generation time series that considers multiple battery capacities. The results indicate that the optimal battery lifetime is extended in comparison to conventional models that ignore battery degradation in dispatch decisions. Finally, we analyze the relationship between battery operational decisions and the resultant capacity fade.

关键词： energy storage energy systems analysis optimization and control simulation

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Dynamics of Locally Coupled Agents with Next Nearest Neighbor Interaction

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DIFFERENTIAL EQUATIONS AND DYNAMICAL SYSTEMS 2021年第3期29卷 487-509页

作者： Herbrych, J. Chazirakis, A. G. Christakis, N. Veerman, J. J. P. Univ Crete Dept Phys Crete Ctr Quantum Complex & Nanotechnol Iraklion Greece Univ Tennessee Dept Phys & Astron Knoxville TN 37996 USA Oak Ridge Natl Lab Mat Sci & Technol Div Oak Ridge TN USA Univ Crete Dept Math & Appl Math Iraklion Greece Portland State Univ Fariborz Maseeh Dept Math & Stat Portland OR USA

We consider large but finite systems of identical agents on the line with up to next nearest neighbor asymmetric coupling. Each agent is modelled by a linear second order differential equation, linearly coupled to up to four of its neighbors. The only restriction we impose is that the equations are decentralized. In this generality we give the conditions for stability of these systems. For stable systems, we find the response to a change of course by the leader. This response is at least linear in the size of the flock. Depending on the system parameters, two types of solutions have been found: damped oscillations and reflectionless waves. The latter is a novel result and a feature of systems with at least next nearest neighbor interactions. Analytical predictions are tested in numerical simulations.

关键词： Dynamical systems Chaotic Dynamics optimization and control Multi-agent systems

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Measurement-based Validation of Energy-Space Modelling in Multi-Energy Systems 52

Measurement-based Validation of Energy-Space Modelling in Mu...

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52nd North American Power Symposium (NAPS)

作者： Bharadwaj, Pallavi Agrawal, Janak Jaddivada, Rupamathi Zhang, Min Ilic, Marija MIT Lab Informat & Decis Syst Cambridge MA 02139 USA ENNEW DIGITAL TECHNOL CO LTD Beijing Peoples R China

ISBN: (纸本)9781728181929

In this paper we derive a unifying multi-energy system model to represent dynamics of interactions between its gas, water and electricity network components. We conceptualize each component as a two-directional energy conversion processing unit which receives at its inputs power at certain rate from the neighboring system components, and sends out power at certain rate to the rest of the system. This characterizes input-output relations of components and their dynamic interactions in terms of unifying energy and power variables. We show how generalized flow and effort variables, typically measured at component ports, can be used to validate the newly derived unifying model in terms of its real power and rate of change of reactive power. Based on actual data obtained for a commercial multi-energy HVAC installation we validate the newly derived model at nearly 99% accuracy.

关键词： Multi-energy system energy-space modelling reduced-order model HVAC system optimization and control

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Deep Reinforcement Learning for Robotic control with Multi-Fidelity Models

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IFAC-PapersOnLine 2022年第37期55卷 193-198页

作者： David Felipe Leguizamo Hsin-Jung Yang Xian Yeow Lee Soumik Sarkar

Deep reinforcement learning (DRL) can be used for the development of robotic controllers. Complicated kinematic relationships can be learned by a DRL agent, which will result in a control policy that takes actions based on an observed state. However, a DRL agent typically goes through much trial and error before beginning to take appropriate actions. Therefore, it is often useful to leverage simulated robotic manipulators before performing any training or testing on actual hardware. There are several options for such simulation, ranging from simple kinematic models to more complex models seeking to accurately simulate the effects of gravity, inertia, and friction. The latter models can provide excellent representations of a robotic plant, but typically with a noticeably increased computational expense. Reducing the expense of simulating the robotic plant (while still maintaining a reasonable degree of accuracy) can accelerate an already expensive DRL training loop. In this work, we present a methodology for using a lower-fidelity model (based on Denavit-Hartenberg parameters) to initialize the training of a DRL agent for control of a Sawyer robotic arm. We show that the trained DRL policy can then be fine-tuned in a higher-fidelity simulation provided by the robot's manufacturer. We demonstrate the accuracy of the fully trained policy by transferring it to the actual hardware, demonstrating the power of DRL to learn complicated robotic tasks entirely in simulation. Finally, we benchmark the time required to train a policy using each level of fidelity.

关键词： Robotic Systems Self-learning Models Real-time Artificial Intelligence Reinforcement learning control Engineering Applications of Artificial Intelligence optimization and control Multi-Fidelity Modeling

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New Approaches for Analyzing Systems with History-Dependent Efficiency

New Approaches for Analyzing Systems with History-Dependent ...

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作者： Lin, Michael University of Maryland College Park

学位级别：Ph.D.

In my dissertational work, I propose two novel models for analyzing systems in which the operational efficiency depends on the past history, e.g., systems with human-in-the-loop and energy harvesting sensors. First, I investigate a queuing system with a single server that serves multiple queues with different types of tasks. The server has a state that is affected by the current and past actions. The task completion probability of each kind of task is a function of the server state. A task scheduling policy is specified by a function that determines the probability of assigning a task to the server. The main results with multiple types of tasks include: (i) necessary and sufficient conditions for the existence of a randomized stationary policy that stabilizes the queues; and (ii) the existence of threshold type policies that can stabilize any stabilizable system. For a single type system, I also identify task scheduling policies under which the utilization rate is arbitrarily close to that of an optimal policy that minimizes the utilization rate. Here, the utilization rate is defined to be the long-term fraction of time the server is required to work. Second, I study a remote estimation problem over an activity packet drop link. The link undergoes packet drops and has an (activity) state that is influenced by past transmission requests. The packet-drop probability is governed by a given function of the link's state. A scheduler determines the probability of a transmission request regarding the link's state. The main results include: (i) necessary and sufficient conditions for the existence of a randomized stationary policy that stabilizes the estimation error in the second-moment sense; and (ii) the existence of deterministic policies that can stabilize any stabilizable system. The second result implies that it suffices to search for deterministic strategies for stabilizing the estimation error. The search can be further narrowed to threshold policies when the funct

关键词： Mathematics Information science Operations research optimization and control Queuing Theory Remote Estimation

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Comparison of path planning algorithms for an unmanned aerial vehicle deployment under threats

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IFAC-PapersOnLine 2019年第13期52卷 1978-1983页

作者： Danancier, Kevin Ruvio, Delphine Sung, Inkyung Nielsen, Peter Department of Industrial Engineering Polytech Engineering School of Aix-Marseille University France Operations Research Group Department of Materials and Production Aalborg University Denmark

Following the massive interests in unmanned aerial vehicles (UAVs), various optimization algorithms have been proposed for a path planning problem that allow the units to navigate in a region filled with threats such as a radar detection in air defence systems. Among the algorithms, we address Dijkstra's algorithm and a heuristic algorithm for the path planning of a UAV. The algorithms are compared under various configurations of a region to navigate with respect to the optimality and the computational complexity of the algorithms. © 2019, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Intelligent vehicle highway systems Air navigation Aircraft detection Antennas Computational complexity Heuristic algorithms Navigation Operations research optimization Scheduling Tracking radar Unmanned aerial vehicles (UAV) Air defence systems Dijkstra's algorithms Optimality optimization algorithms optimization and control Path planning problems Path planning algorithm Radar detection

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Intelligent control interfaces using extenics multidimensional theory applied on Vipro platforms for developing the IT industry 4.0 concept

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IFAC-PapersOnLine 2019年第13期52卷 922-927页

作者： Vladareanu, Luige Vladareanu, Victor Yu, Hongnian Mitroi, Daniel Ciocîrlan, Alexandra-Catalina Robotics and Mechatronics Department Romanian Academy Institute of Solid Mechanics Bucharest Romania Faculty of Science and Technology Bournemouth University PooleBH125BB United Kingdom

The paper presents new concepts and approaches to achieving intelligent control interfaces for solving contradictory problems using Extenics multidimensional theory applied on VIPRO Versatile Intelligent Portable Platforms. VIPRO platform enables developing the IT Industry 4.0 concept through the design, testing and experimentation of new intelligent control interfaces on a classical mechatronic control system without the need to modify its hardware structure, and, from optimal decisions and information fusion between the intelligent control interfaces, resulting in a high degree of versatility and portability to a global communications network. The Cyber-Physical Systems as like a VIPRO Platform's component, developed through advanced intelligent control interfaces integrate the dynamics of the physical processes with those of the software and networking, providing a powerful environment for modeling, design, and analysis techniques for an integrated whole IT Industry. The portability characteristics results allow test and improve the motion performance of the mechatronic system, and furthermore implement the intelligent control and decision interfaces on their own control system, applying Industry 4.0 components: cognitive computing including intelligence and signal processing, cyber-physical systems, internet of things and cloud computing, exemplified on an Extenics multidimensional control intelligent interfaces. © 2019, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Intelligent control Cognitive systems Computation theory Computer software portability control theory Cyber Physical System Decision support systems Embedded systems Industry 4.0 Real time control Robotics Signal processing Analysis techniques Contradictory problems Global communication Intelligent interface Mechatronic control systems Mechatronic systems Multi dimensional control optimization and control

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Social infrastructure of Silver Economy: Literature review and Research agenda

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IFAC-PapersOnLine 2019年第13期52卷 2680-2685页

作者： Rogelj, Valerija Bogataj, David Nova University Slovenia Institute INRISK Slovenia University of Padua Department of Management and Engineering Vicenza Italy

The term Silver Economy encompasses a vast range of concepts and areas of interest related to both the challenges and opportunities that the ageing population represents. Social Infrastructure is a subset of the infrastructure sector and typically includes assets that accommodate social services and support networks. Housing and utilities with the added value of 850 billion EUR per year represent the highest share of European Silver economy. Investments in housing and age-friendly built environment should be made with the criterion to accommodate declining functional capacities of ageing residents. Their functional capacities are decreasing and require the development of specialised housing stock for independent living in a community. The structure of housing stock and the development of supply networks and services for older adults, including nursing and social care, do not follow the dynamics of population ageing. Based on the literature review we present the dynamics of publications for the most frequently discussed types of dwellings in connection with ‘older adults' in the journals indexed by Web of Science (WoS). In this article, we present a literature review of specialized housing solutions and other dwellings for older adults and further research agenda to develop optimization and control theory models supporting optimal planning, operations and control of services for older adults based on ambient intelligence, some of them based also on the geographic information technology and model to measure and forecast the demand for specialized housing stock and services in ageing society for which even the documents of the European Commission state that has not been developed yet. Industrial engineering and production research has the potential to significantly improve the efficiency of supply networks for older adults and mitigate the rising expenditure for health care and long-term care in ageing societies. © 2019 IFAC © 2019, IFAC (International Federation of Au

关键词： Housing Economics Industrial research Investments Risk management Service industry Silver Geographic information technologies Housing stock Infrastructure sector LTC services Operations and control optimization and control Population ageing Social infrastructure

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