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International Technical Conference o Circuits/Systems, Computers and Communications (ITC-CSCC)

作者： Yuki Sakamoto Takumi Namba Kiyotsugu Takaba Ritsumeikan University Kusatsu Japan

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

The use of EV batteries as secondary energy sources has recently been attracting great attention due to their large capacities. This paper is concerned with energy management of a workplace making use of the employees' EVs. We formulate such an energy management as a mixed-integer linear programming (MILP) problem by taking account of the arrival/departure status of the EVs and the benefits of the EV owners. Through a numerical simulation, we compare the effectiveness of the centralized algorithm and the distributed algorithm (Camisa et al. 2022) for finding a near-optimal solution to the MILP. The following points turn out from the simulation. If the number of EVs is small, the centralized algorithm can obtain a better solution to the MILP problem faster than the distributed algorithm without admitting the EV owners' decision-making. In contrast, in the case of a large number of EVs, the distributed algorithm can solve the problem faster than the centralized one taking account of the EV owners' decision-making at the price of the quality of its solution.

关键词： Computers Employment Decision making Numerical simulation linear programming mixed integer linear programming Batteries

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Makespan optimization using Timed Petri Nets and mixed integer linear programming Problem

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IFAC-PapersOnLine 2020年第4期53卷 129-135页

作者： E. Di Marino R. Su F. Basile University of Salerno DIEM Italy Nanyang Technological University School of Electrical & Electronic Engineering Singapore

In this paper, a method for generating a mixed integer linear programming problem from deterministic timed Petri nets to optimize the makespan of manufacturing systems is proposed. After exposing several challenges involved in such a model transformation, a novel method is exploited to overcome them. The adopted solution may create a synergy between the highly expressive timed Petri net modelling framework and the computational attractive mathematical programming tool set.

关键词： Discrete Event Systems Timed Petri Nets mixed integer linear programming

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QAOA-Assisted Benders' Decomposition for mixed-integer linear programming

QAOA-Assisted Benders' Decomposition for Mixed-integer Linea...

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IEEE International Conference on Communications (ICC)

作者： Zhongqi Zhao Lei Fan Yuanxiong Guo Yu Wang Zhu Han Lajos Hanzo Department of Electrical and Computer Engineering University of Houston Houston TX USA Department of Engineering Technology University of Houston Houston TX USA Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX USA Department of Computer and Information Sciences Temple University Philadelphia PA USA School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Benders' decomposition (BD) algorithm constitutes a powerful mathematical programming method of solving mixed-integer linear programming (MILP) problems with a specific block structure. Nevertheless, BD still needs to solve an NP-hard quasi-integer programming master problem (MAP), which motivates us to harness the popular variational quantum algorithm (VQA) to assist BD. More specifically, we choose the popular quantum approximate optimization algorithm (QAOA) of the VQA family. We transfer the BD's MAP into a digital quantum circuit associated with a physically tangible problem-specific ansatz; and then solve it with the aid of a state-of-the-art digital quantum computer. Next, we evaluate the computational results and discuss the feasibility of the proposed algorithm. The hybrid approach advocated, which utilizes both classical and digital quantum computers, is capable of tackling many practical MILP problems in communication and networking, as demonstrated by a pair of case studies.

关键词： Performance evaluation Quantum computing Quantum algorithm programming Approximation algorithms mixed integer linear programming Quantum circuit

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On the Equivalence Between mixed-integer linear and linear programming Problems in MPC for Photovoltaic Plants with Energy Storage

On the Equivalence Between Mixed-Integer Linear and Linear P...

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IEEE ANDESCON

作者： Rodrigo Graves Angel L. Cedeño Cùsar Silva Juan C. Agüero Departamento de Electronica Universidad Tecnica Federico Santa Maria Valparaiso Chile

ISBN: (数字)9798350355284

ISBN: (纸本)9798350355291

This paper investigates the equivalence between a class of mixed-integer linear and linear programming prob-lems. By utilizing the addition of slack variables theorem, we demonstrate that certain optimization problems arising in Model Predictive Control strategies, which involve logical constraints, can be solved as linear programming problems. Consequently, the equivalent linear programming problem can be solved using the standard and numerically efficient method named the Sim-plex method, as opposed to mixed-integer linear programming problems for which the best solution method is not clear. As a case study, we address the control problem of photovoltaic plants with energy storage systems. We design a model-based predictive control scheme based on our proposed equivalent linear programming problem to maximize economic benefits derived from energy delivered by both photovoltaic panels and energy storage systems to the grid in a deregulated electricity market, achieved by managing the charge and discharge of the energy storage. Additionally, the proposed scheme allows for the consideration of rate-based variable efficiency in the energy stor-age system model, offering a more comprehensive implementation compared to the previous approach in the literature, where only an ideal battery was considered. Furthermore, simulations reveal that the proposed control methodology reduces the execution time of model-predictive control iterations compared to another approach based on mixed-integer linear programming schemes with similar considerations, thereby enhancing the scalability of the solution.

关键词： Photovoltaic systems Economics Transforms linear programming Electricity supply industry Batteries mixed integer linear programming Optimization Standards Predictive control

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Stochastic optimization of comfort-centered model of electrical water heater using mixed integer linear programming

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2020年 42卷

作者： Najafi, Foad Fripp, Matthias Univ Hawaii Manoa Dept Elect Engn 2540 Dole St Honolulu HI 96822 USA

This paper introduces a new strategy for controlling electric water heaters (EWH) using mixed-integer linear programming (MILP). It has two major contributions: 1) To balance between cost savings and the discomfort (cold water) that Demand Response (DR) could bring, the discomfort is modeled as undelivered energy in the objective of the problem rather than a thermal constraint. This improves both sides of the cost-saving Vs. User-comfort trade-ff. 2) in EWH control, many previous works only rely on electricity prices for scheduling. However, this work is among the very few works that also consider consumption for scheduling. Further, by treating the hot water withdrawal pattern as a random variable, the algorithm finds the best setpoints for EWH via stochastic optimization over a range of possible hot water withdrawal patterns, rather than requiring perfect foresight of withdrawal. The result of these changes is an algorithm that can let the temperature fall below minimum when probability of energy usage is low without affecting user comfort while other methods always keep the temperature above minimum. The effectiveness of this approach on improving both sides of the cost Vs. discomfort trade-off and the effectiveness of stochastic approach is confirmed by comparison with two other methods.

关键词： Thermal comfort Demand response Electric water heater scheduling Stochastic optimization mixed integer linear programming Smart grids

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A mixed-integer linear programming Formulation for Human Multi-Robot Task Allocation 30

A Mixed-Integer Linear Programming Formulation for Human Mul...

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30th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

作者： Lippi, Martina Marino, Alessandro Roma Tre Univ Rome Italy Univ Cassino & Southern Lazio Cassino Italy

ISBN: (纸本)9781665404921

In this work, we address a task allocation problem for human multi-robot settings. Given a set of tasks to perform, we formulate a general mixed-integer linear programming (MILP) problem aiming at minimizing the overall execution time while optimizing the quality of the executed tasks as well as human and robotic workload. Different skills of the agents, both human and robotic, are taken into account and human operators are enabled to either directly execute tasks or play supervisory roles;moreover, multiple manipulators can tightly collaborate if required to carry out a task. Finally, as realistic in human contexts, human parameters are assumed to vary over time, e.g., due to increasing human level of fatigue. Therefore, online monitoring is required and re-allocation is performed if needed. Simulations in a realistic scenario with two manipulators and a human operator performing an assembly task validate the effectiveness of the approach.

关键词： Collaboration Switches Manipulators Fatigue Real-time systems mixed integer linear programming Resource management

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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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Predicting Mode Confusion Through mixed integer linear programming 58

Predicting Mode Confusion Through Mixed Integer Linear Progr...

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58th IEEE Conference on Decision and Control (CDC)

作者： Sivaramakrishnan, Vignesh Thapliyal, Omanshu Vinod, Abraham Oishi, Meeko Hwang, Inseok Univ New Mexico Elect & Comp Engn Albq NM 87131 USA Purdue Univ Aeronaut & Astronaut W Lafayette IN 47907 USA Univ Texas Austin Oden Inst Computat Engn & Sci Austin TX 78712 USA Univ New Mexico Albuquerque NM 87131 USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113982

Mode confusion, in which the human and the automation have a mismatch in intent, is a contributing factor in many aircraft incidents and accidents. Despite extensive work studying and documenting instances of mode confusion, methodological tools to predict and prevent mode confusion are still lacking. We propose a method to identify mismatches between the pilot and automation intents, in which the pilot intent is inferred from the pilot manual, and the automation intent is an abstraction of the underlying hybrid dynamical system representation of the aircraft and flight management system. We employ a mixed-integer linear programming framework to identify all trajectories from a known initial condition that will result in mismatches in discrete event abstractions which encode both pilot and aircraft intents. We then propose heuristics that use traces from failed trajectories to correct the mode confusion through modifications to the automation intent, via parameterization of guards. We demonstrate our method on the canonical kill-the-capture scenario for longitudinal aircraft dynamics.

关键词： Aircraft Atmospheric modeling Automation Hidden Markov models Discrete-event systems Trajectory mixed integer linear programming

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A mixed integer linear programming Method for Generating Backbone Grid 3

A Mixed Integer Linear Programming Method for Generating Bac...

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3rd IEEE International Electrical and Energy Conference (CIEEC)

作者： ZhiYuan, Sun Liu, Mosi Sun, Yan Guangxi Power Grid Co Ltd Elect Power Res Inst Nanning Peoples R China Guangxi Power Grid Co Ltd Power Dispatching & Control Ctr Nanning Peoples R China

ISBN: (纸本)9781728116754

The intelligence algorithm used in the backbone grid search is unrobust and has uncertain results. To tackle the drawback, this paper proposes a mixed integer linear programming (MILP) model for generating the power system backbone grid. Based on the graph theory, this model considers the connectivity of the backbone grid as linear constraints with integer variables. Constrains of line power in the model are elicited by the derivation from Kirchhoff's current law. Since the expressions in this model are analytical and linear, with the help of developed MILP algorithm, the proposed model can fully solve the problem of absence of robustness in existing method. The simulations of IEEE 39-bus system and IEEE 118-bus system show that the proposed model is effective and reliable, which provides a new idea for the development in this research.

关键词： mixed integer linear programming backbone grid Steiner tree connectivity

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PV system sizing with storage management: A comparative study based on mixed integer linear programming 6

PV system sizing with storage management: A comparative stud...

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6th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Hascuri, Mohamed Rami, Mustapha Ait Derrhi, Mostala ENSA Tangier BP 1818 Tanger Principal Tangier Tangier Morocco ENSI Tangier Villa 131Rue Ibn Atia Tangier 90000 Morocco

ISBN: (纸本)9781728105215

This paper provides a systematic approach in order to analyze and treat the sizing of Photovoltaic systems (PV), such approach is based on mixed integer linear programming (MILP) formulation. In this spirit, two optimized models are provided. Moreover, a comparative study is performed for the sizingg problem between Branch and Bound and Branch and Cut algorithms. The simulation results show the efficiency of the proposed approach.

关键词： Photovoltaic Energy Storage System mixed integer linear programming Optimization

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