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检索条件"主题词=mixed-integer linear programming"

共 2269 条记录，以下是671-680 订阅

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User Cost Differences under Five Capacity Adequacy Mechanisms Based on Equilibrium Analysis 8

User Cost Differences under Five Capacity Adequacy Mechanism...

引用

8th International Conference on Smart Grid and Smart Cities, ICSGSC 2024

作者： Ma, Ning Yang, Lei Feng, Yuanhao Yang, Xingang Du, Yang Zhou, Yun European Representative Office State Grid Corporation China Berlin Germany Electric Power Company State Grid Shanghai Municipal Shanghai China Shanghai Jiao Tong University Dept. of Electrical Engineering Shanghai China Power Research Institute State Grid Shanghai Electric Shanghai China

ISBN: (纸本)9798350377408

Capacity adequacy mechanisms are crucial pathways to ensure reliable power supply in electricity grids and are coupled with the spot electricity market. However, current studies on the impact of capacity adequacy mechanisms on the electricity market do not simultaneously consider the strategies of power generators regarding bidding, investment, and capacity sales, as well as the strategic behaviors among multiple stakeholders. To address this, we propose game-theoretic equilibrium models for multiple power generators under five typical capacity adequacy mechanisms: scarcity pricing, strategic reserve, capacity subsidy, capacity market, and reliability options. Firstly, we establish a two-layer game model for each capacity adequacy mechanism: the upper layer is the strategic optimization model for power generators, and the lower layer is the day-ahead market clearing model. Secondly, by using the optimality conditions of the lower model and a series of precise linearization methods, the two-layer models are transformed into several mixed-integer linear programming problems, and the game equilibrium is iteratively solved using a dynamic game framework. Case studies show that, compared to scarcity pricing mechanisms, reliability options can suppress the market power abuse by power generators during high-load periods and lead to a market equilibrium with lower user costs, while the other three mechanisms can only maintain or increase user costs. © 2024 IEEE.

关键词： mixed-integer linear programming

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Bi-Level Optimization for Energy Management of Networked Microgrid 4

Bi-Level Optimization for Energy Management of Networked Mic...

引用

4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Bhowmick, Arpan Badar, Altaf Q. H. Nit Warangal Dept. Electrical Engineering Warangal India

ISBN: (纸本)9798350383997

A Microgrid (MG) is formed by a collection of interconnected loads and distributed energy resources, operating collectively and under control as a distinct entity in relation to the grid. A Networked Microgrid (NMG) comprises of interconnected MGs, facilitating sharing of resources, load balancing, and coordinated operation. NMG may connect to the external power grid for energy import/ export and enhancing overall efficiency. This paper proposes an energy management scheme in an NMG. The proposed scheme consists of two levels. At lower-level, Microgrid Energy Management Systems (MG-EMS) calculate the surplus and shortage of power, generation of Dispatchable Generation (DG), charging and discharging of Electric Vehicle (EV), Battery Energy Storage System (BESS) of individual MGs. At upper-level, Central Energy Management System (CEMS) decides the amount of energy traded between the MGs and between MG and the utility grid with the help of information given by MG-EMS. The NMG considered in this research has three MGs and each MG has EV as a part of it. mixed-integer linear programming (MILP) has been deployed to address this problem. Microsoft Visual Studio is used to implement MILP. © 2024 IEEE.

关键词： mixed-integer linear programming

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Minimize the Rest Differences in Round Robin Tournaments under an Initial Schedule 6

Minimize the Rest Differences in Round Robin Tournaments und...

引用

6th International Conference on Control and Robotics, ICCR 2024

作者： Shang, Zhiyuan Xue, Fei Wang, Wushuang Shigeno, Maiko University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798331518158

Fairness is a crucial element in sports tournaments, with numerous indicators devised to ensure balanced competitions. To minimize rest differences, which means the rest time difference between two opponents, previous research has proposed a mixed-integer programming Model for Rest Difference Problem(MIP-RDP), basing on this foundation, the paper proposes a mixed-integer programming Model with Initial Schedule(MIP-RDPIS) to improve computational efficiency. Additionally, we employ a meta-heuristic algorithm called discrete Jaya to investigate the effects of various initial schedules on the algorithm's performance. Our computational results indicate that for a small number of teams, the MIP-RDPIS closely approximates the model without initial schedules. The heuristic algorithm, which incorporates round swap and matchday swap, demonstrates superior performance on larger-scale problems. We conclude that by leveraging existing initial schedules and avoiding extensive alterations within a single round, we can approach optimal solutions more effectively. For large-scale problems, our method offers improved match scheduling solutions compared to existing approaches. © 2024 IEEE.

关键词： mixed-integer linear programming

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Economic Optimizer for Building Energy Rating 26

Economic Optimizer for Building Energy Rating

引用

2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024

作者： Legal, Daniel Fuentes, Carlos Chavez, Hector Perez, Roberto Riquelme, Esteban Universidad de Santiago Center for Sustainable Energy Systems Santiago Chile

ISBN: (纸本)9798350378115

The construction sector is responsible for emitting 30% of worldwide greenhouse emissions. Sustainable construction addresses this problem by designing infrastructures under the energy-efficient concept. This paper presents an energyefficient optimal methodology for designing the thermal envelope and energy support technologies of the infrastructure, according to the energy qualification established in 21.305 law. The methodology consists of carrying out a mathematical formulation of the optimization problem for an energy solution implementing a Home Energy Rating (CEV) as an input parameter, which allows obtaining specific results for all the elements that participate in the property's requirement. Specifically, simulations were carried out of a house located in the north and south of Chile considering different parameters such as floor, walls, windows, etc. Simulating in each area and restricting the energy rating where the sensitivity of the problem to the different parameters is observed. Finally it is possible to conclude about the minimum energy requirements. © 2024 IEEE.

关键词： mixed-integer linear programming

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linear Reinforcement Learning for Energy Storage Systems Optimal Dispatch

Linear Reinforcement Learning for Energy Storage Systems Opt...

引用

2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Gao, Shuyi Hou, Shengren Duque, Edgar Mauricio Salazar Palensky, Peter Vergara, Pedro P. Delft University of Technology Intelligent Electrical Power Grids Delft Netherlands Eindhoven University of Technology Energy Systems Systems Group Eindhoven Netherlands

ISBN: (纸本)9789531842976

Reinforcement Learning (RL) has emerged as a promising solution for defining the optimal dispatch of Energy Storage Systems (ESS) in distributed energy systems. However, a notable gap exists in the literature: a lack of comprehensive and fair comparisons between different RL algorithms, particularly between linear and nonlinear approaches. This study critically evaluates the trade-offs between computational efficiency and operational accuracy among various linear RL (LRL) strategies and compares them against the nonlinear Deep-Q-Network (DQN) algorithm. Through a comprehensive analysis, this study benchmarks the model-based mixed-integer linear programming (MILP) results to assess and compare these algorithms' convergence, training efficiency, and optimization accuracy. Results indicate that while LRL approaches the operational cost accuracy of DQN, it faces significant trade-offs in computational efficiency and struggles with generalization across larger and varied datasets. The results illuminate critical areas for further development in LRL methodologies, particularly in enhancing their adaptability and generalization capabilities. © 2024 IEEE.

关键词： mixed-integer linear programming

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Randomized Rounding for the Preventive Healthcare Facility Location Problem

Randomized Rounding for the Preventive Healthcare Facility L...

引用

IISE Annual Conference and Expo 2024

作者： Lee, Taewoo Shim, Sangho Zhao, Qian Swanson School of Engineering University of Pittsburgh PittsburghPA15261 United States School of Engineering Mathematics and Science PA15108 United States

ISBN: (纸本)9781713877851

In the preventive healthcare facility location problems (PHFLPs), explicitly modeling realistic aspects of the location decisions such as potential participants’ latent utility functions related to various attributes of each candidate facility leads to a large-scale mixed-integer non-linear program (MINLP). In this paper, we develop a randomized rounding approach to efficiently solve computationally challenging PHFLPs formulated as an MINLP and rapidly identify optimal or near-optimal solutions. We use the previous results by Krohn, Müller and Haase [OR Spectrum (2021) 43, 59-87] and their publicly available data as a case study to demonstrate the efficiency and practical usefulness of the proposed computational approach. Our approach solves PHFLP instances with up to 400 demand nodes and 15 candidate locations within a few seconds and the real-world case of 9,679 demand nodes and 56 candidate locations within 10 minutes, significantly faster than the previous approaches. © IISE Annual Conference and Expo *** rights reserved.

关键词： mixed-integer linear programming

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Improved Spectral Clustering for Distributed Resources 11

Improved Spectral Clustering for Distributed Resources

引用

11th China International Conference on Electricity Distribution, CICED 2024

作者： Wang, Liwen Lv, Leiyan Ma, Xiang Ling, Kaiyuan Xu, Peng Liu, Jiantao China Electric Power Research Institute Co. Ltd Nanjing China Jinhua Power Supply Company State Grid Corporation of China Jinhua China

ISBN: (纸本)9798350368345

In addressing the issue of exponential increase in solution time with the growing number of simulations when using mixed-integer linear programming methods to solve stochastic models based on Monte Carlo simulation, this paper proposes employing spectral clustering to determine the best-quality classification scheme. By using the spectral clustering method on random samples generated by Monte Carlo simulation, the optimal classification scheme is identified to group similar stochastic scenarios together. Finally, by selecting the center of each class as a representative, the number of scenarios to be considered is reduced, facilitating the solution of problems such as whole-scenario modeling and lowering the difficulty of solving. Experimental results demonstrate that the spectral clustering method proposed in this paper exhibits the best performance among some commonly used methods. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimal Scheduling of Programmable Appliances for Demand Management in Energy Communities 10

Optimal Scheduling of Programmable Appliances for Demand Man...

引用

10th International Conference on Optimization and Applications, ICOA 2024

作者： Lazzeroni, Paolo Lorenti, Gianmarco Canova, Aldo Repetto, Maurizio Politecnico di Torino Dipartimento Energia 'Galileo Ferraris' Turin Italy

ISBN: (纸本)9798350387353

Increasing the share of Renewable Energy Sources (RES) in energy consumption is perceived today as essential to decarbonizing energy systems. In this context, the Renewable Energy Communities (RECs) have been recently introduced to create a more decentralized energy system, where each member may share RES-based energy production to increase local self-consumption. To maximize the benefits for each member, the RES-based energy generation should match the demand. Thus, demand management may contribute in this regard by introducing load-shifting for the electric appliances used by REC's members. In this view, different modeling approaches are proposed as mixed integer linear programming and mixed integer Quadratic programming. Solutions can be used to suggest possible changes to the end-users' current habits. Simulations are performed to compare energy, economic, and environmental Key Performance Indicators, including self-consumption, self-sufficiency, and CO2 emission savings. © 2024 IEEE.

关键词： mixed-integer linear programming

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Differentiable Distributionally Robust Optimization Layers 41

Differentiable Distributionally Robust Optimization Layers

引用

41st International Conference on Machine Learning, ICML 2024

作者： Ma, Xutao Ning, Chao Du, Wenli Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

In recent years, there has been a growing research interest in decision-focused learning, which embeds optimization problems as a layer in learning pipelines and demonstrates a superior performance than the prediction-focused approach. However, for distributionally robust optimization (DRO), a popular paradigm for decision-making under uncertainty, it is still unknown how to embed it as a layer, i.e., how to differentiate decisions with respect to an ambiguity set. In this paper, we develop such differentiable DRO layers for generic mixed-integer DRO problems with parameterized second-order conic ambiguity sets and discuss its extension to Wasserstein ambiguity sets. To differentiate the mixed-integer decisions, we propose a novel dual-view methodology by handling continuous and discrete parts of decisions via different principles. Specifically, we construct a differentiable energy-based surrogate to implement the dual-view methodology and use importance sampling to estimate its gradient. We further prove that such a surrogate enjoys the asymptotic convergency under regularization. As an application of the proposed differentiable DRO layers, we develop a novel decision-focused learning pipeline for contextual distributionally robust decision-making tasks and compare it with the prediction-focused approach in experiments. Copyright 2024 by the author(s)

关键词： mixed-integer linear programming

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Flexibility within market coupling in Southeast Europe 3

Flexibility within market coupling in Southeast Europe

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Koltsaklis, Nikolaos E. Sabanci University Faculty of Engineering and Natural Sciences Istanbul Turkey

ISBN: (纸本)9798350375923

This work addresses the problem of optimizing the energy market-clearing of an integrated power system in a coupled market. More specifically, a wide range of market products (simple hourly, block, and complex orders) are simulated in order to determine the optimal energy allocation. Apart from conventional power plants, a series of flexibility service providers are also modeled, including electricity storage systems and electric vehicles under various smart charging and discharging options. The overall methodological framework is based on mixed-integer programming techniques and is tested in the integrated Greek-Bulgarian-Romanian power system as planned for 2030. A series of scenarios have also been examined to investigate the impacts of parameters such as PV availability, electricity demand, EV penetration, and natural gas and CO2 emission prices. The results highlight the impacts of market coupling in a series of fundamentals such as resulting energy mix, cross-border electricity flows, and environmental impact in terms of CO2 emissions. It also underscores the role of flexible resources in alleviating the impacts of intermittency injected into the power systems through variable renewable energy sources. System operators, regulatory authorities, and potential investors can utilize the optimization framework developed to quantify the short-term dynamics of coupled electricity market operations and optimize the management of their resources and portfolios. © 2024 IEEE.

关键词： mixed-integer linear programming

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