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Single Period Dynamic Economic Dispatch in Integrated Energy Systems using JuMP Optimization

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Single Period Dynamic Economic Dispatch in Integrated Energy...

Emerging Power Technologies (ICEPT), International Conference on

作者： Muhammad Nouman Muhammad Bilal Raza Muhammad Saqlain Khalid Moattar Robab Muhammad Mansoor Ashraf Muhammad Waseem Electrical Engineering Department University of Engineering and Technology Taxila Pakistan International Renewable and Energy Systems Integration Research Group (IRESI) School of Business Maynooth University Co. Kildare Ireland

ISBN: (数字)9798331536657

ISBN: (纸本)9798331536664

This study introduces an innovative method for addressing Single Period Dynamic Economic Dispatch (DED) in Integrated Energy Systems (IES) utilizing the Julia for mathematical programming (JuMP) optimization framework. The primary focus of this research is to minimize the operating costs of IES while integrating a variety of generation sources, such as biogas, wind, solar, hydropower, and natural gas. Using real-world data from San Diego Gas and Electric (SDG&E), the model tackles the dual objectives of enhancing economic effi-ciency and advancing environmental sustainability. The proposed optimization model aims to reduce the total variable costs of power generation by efficiently managing the generation mix. It accounts for dynamic constraints, including resource availability, generation capacity limits, and system demand, providing a versatile and adaptable framework suitable for future energy systems. By integrating renewable energy sources, the study emphasizes the potential to decrease reliance on fossil fuels and reduce carbon emissions, contributing to global sustainability goals. The outcomes of the simulation carried out in JuMP substantiate the efficacy of the proposed approach providing a benchmark for future research on sustainable and cost-efficient energy systems.

关键词： Costs Power system dynamics Real-time systems Dynamic programming Power system reliability Reliability Sustainable development Optimization mathematical programming programming environments

Data-driven Optimization and Transfer Learning for Cellular Network Antenna Configurations

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arXiv 2025年

作者： Benzaghta, Mohamed Geraci, Giovanni López-Pérez, David Valcarce, Alvaro Univ. Pompeu Fabra Barcelona Spain Telefónica Research Barcelona Spain Univ. Politècnica de València Spain Nokia Bell Labs Massy France

We propose a data-driven approach for large-scale cellular network optimization, using a production cellular network in London as a case study and employing Sionna ray tracing for site-specific channel propagation modeling. We optimize base station antenna tilts and half-power beamwidths, resulting in more than double the 10%-worst user rates compared to a 3GPP baseline. In scenarios involving aerial users, we identify configurations that increase their median rates fivefold without compromising ground user performance. We further demonstrate the efficacy of model generalization through transfer learning, leveraging available data from a scenario source to predict the optimal solution for a scenario target within a similar number of iterations, without requiring a new initial dataset, and with a negligible performance loss. © 2025, CC BY.

关键词： mathematical programming

Holographic Beamforming Design for RHS-Assisted MU-MISO Systems with One-Bit DACs

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Holographic Beamforming Design for RHS-Assisted MU-MISO Syst...

IEEE Conference on Wireless Communications and Networking

作者： Yaqi Wang Jianping Zheng School of Telecommunications Engineering Xidian University Xi'an Shaanxi China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Reconfigurable holographic surfaces (RHSs) can generate the desired directional beam by controlling the radiation amplitude of reference wave, and thus is an effective alternative to conventional analogue beamforming architecture. In this paper, we investigate the RHS-aided downlink multiuser multiple-input-single-output system with one-bit digital-to-analogue converters. Specifically, we aim to minimize the mean-square error by alternately optimizing the one-bit precoding vector and the holographic beamforming matrix. The alternating direction method of multipliers algorithm is employed to optimize the one-bit nonlinear precoding vector, and the projected gradient decent method, the mathematical programming with equilibrium constraints-alternating direction method, and the Riemannian conjugate gradient method are utilized to design the holographic beamforming matrix with continuous amplitude, binary amplitude, and Lorentzian-constrained phase, respectively. Finally, the effectiveness of the proposed method is demonstrated by computer simulations.

关键词： Array signal processing Surface waves Precoding OFDM Mean square error methods Downlink Vectors Matrix converters Optimization mathematical programming

Tail Assignment-Driven Aircraft Routing Model

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Transportation Research Procedia 2023年 71卷 172-179页

作者： Rubén Jiménez Moreno Francisco López Ramos Manuel Fuentes González Luis Cadarso Morga Rey Juan Carlos University Madrid Spain Cisneria Engineering S.L Spain Tecnológico de Monterrey School of Engineering and Sciences Mexico

The airline industry is characterized by complex, large-scale combinatorial optimization problems that must be tackled in a sequential manner. The planning process is divided into different problems, with decisions being made months or days before the day of operations. For example, fleet assignment and aircraft routing are typically planned months ahead of time, while the tail assignment is decided on a closer time horizon. Due to changes in operational status, flight cancellations, and re-timings, new constraints are imposed on the schedule, leading to updates to the aircraft rotations and tail assignments. This is why it is important to have a flexible tool that can handle the transition from planning to operations. The objective of the research presented in the paper is to bridge the gap between aircraft routing and tail assignment problems, in order to prevent flight cancellations and other issues caused by maintenance-tail incompatibilities. The proposed solution is a mixed-integer linear problem, based on a directed acyclic graph, where nodes are tasks and arcs are connections between them. The paper also presents a solving approach based on the clustering of tails with similar characteristics to improve the performance of the model. The computational experiments in the paper are based on a two-day planning horizon and are drawn from a European airline network. The results show that the integrated problem can keep aircraft routing feasibility, minimize changes in rotations and satisfy specific maintenance requirements.

关键词： Airline Planning mathematical programming Aircraft Routing Tail Assignment Clustering

Cheapest Ensuring Demanded Fire Security of a Region

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Cheapest Ensuring Demanded Fire Security of a Region

International Carpathian Control Conference (ICCC)

作者： Jaroslav Janáček Marek Kvet Faculty of Management Science and Informatics University of Žilina Žilina Slovakia

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

This research article is aimed at completion of the mathematical programming problem, which includes constraints of demand satisfaction of every community by minimum of the firefighters’ units or by minimal associated holding costs. A considered region consists of a set of communities, factories and institutions, which differ in risk of fire outbreak and in amount of possible aftermath. Security is ensured by fire brigades deployed in the serviced region. The deployment of firefighters’ units must fulfill certain conditions, which follow seven levels of risk. The concrete risk level relates to the demand that a given number of firemen units must be located in a given radius and, possibly that another number of units must be located in a given bigger radius. As one firemen unit can be shared by several communities, a question arises, what is the cheapest composition and deployment of the firemen units, which are able to satisfy all the security demands. Computational study is focused on finding relations between necessary computational time and complexity of the system of the security levels.

关键词： Integer programming Costs Production facilities Complexity theory Security mathematical programming

Detailed Thermal Environment Classification of High Geothermal Tunnel Based on Thermal Comfort Indices

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SSRN

SSRN 2024年

作者： Jia, Chaojun Xie, Yanghao Dai, Liang Shi, Chenghua Lei, Mingfeng Zheng, Yanni School of Civil Engineering Central South University Changsha410083 China

High-temperature and high-humidity conditions in geothermal tunnels have adverse effects on the well-being of construction workers. This study aims to establish critical environmental thresholds for construction workers in such conditions. The real-time monitoring of workers encompassed continuous assessment of vital parameters, including dry bulb temperature, relative humidity, wet bulb globe temperature (WBGT), skin temperature, and heart rate. Utilizing actual measurements, this research examines how elevated tunnel environment affects human physiological indicators. The hygrothermal environment within high geothermal tunnels is stratified into five categories: comfort zone, general comfort zone, safety zone, heat tolerable zone, and danger zone. We determine thresholds for environmental parameters in each class using mathematical programming. Furthermore, thresholds for discomfort index (DI), heat index (HI), and relative strain index (RSI) heat stress indicators across different classes are derived. The findings indicate that in this high geothermal tunnel construction setting, thresholds for the comfort zone are 26°C for dry bulb temperature, 30% for relative humidity, and 20°C for WBGT index. Safety thresholds are 37°C, 64%, and 32°C, while danger thresholds are 43°C, 81%, and 40°C, respectively. Regarding safety thresholds for heat stress indices (DI, HI, and RSI), they are determined as 24.89°C, 26.9°C, and 0.28°C, respectively. The danger thresholds are 27.76°C, 36.23°C, and 0.39°C, respectively. This investigation provides essential insights to safeguard the health of construction personnel working in high geothermal tunnel conditions. © 2024, The Authors. All rights reserved.

关键词： mathematical programming

Optimal packing of attractor states in neural representations

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arXiv 2025年

作者： Vastola, John J. Department of Neurobiology Harvard Medical School BostonMA United States

Animals’ internal states reflect variables like their position in space, orientation, decisions, and motor actions—but how should these internal states be arranged? Internal states which frequently transition between one another should be close enough that transitions can happen quickly, but not so close that neural noise significantly impacts the stability of those states, and how reliably they can be encoded and decoded. In this paper, we study the problem of striking a balance between these two concerns, which we call an ‘optimal packing’ problem since it resembles mathematical problems like sphere packing. While this problem is generally extremely difficult, we show that symmetries in environmental transition statistics imply certain symmetries of the optimal neural representations, which allows us in some cases to exactly solve for the optimal state arrangement. We focus on two toy cases: uniform transition statistics, and cyclic transition statistics. Code is available at https://***/john-vastola/optimal-packing-neurreps23. © 2025, CC BY.

关键词： mathematical programming

Coordinating Drop-Off Locations and Pickup Routes: A Budget-Constrained Routing Perspective

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arXiv 2025年

作者： Albareda-Sambola, Maria Blanco, Víctor Hinojosa, Yolanda Universitat Politècnica de Catalunya Spain Universidad de Granada Spain Universidad de Sevilla Spain

We introduce in this paper a new variant of a location routing problem, to decide, the number and location of drop-off points to install based on the demands of a set of pick-up points, according to a given set-up budget for installing drop-off points. A single vehicle is in charge for all pick-up and drop-off operations, and the solution cost is associated with its route, which must also be decided. We provide a general and flexible mathematical optimization based approach for solving the problem that has some peculiarities to assure that the demand is adequately picked up, that some pickup points can be visited multiple times, that the capacity of the vehicle is respected, or that the vehicle is capable to implement the path or tour in the obtained solution. We report the results of a extense battery of experiments to validate our proposal on synthetic instances, and provide some insighs on the usefulness of our approach in practical applications. © 2025, CC BY.

关键词： mathematical programming

SOLAR: Scalable Distributed Spatial Joins through Learning-based Optimization

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arXiv 2025年

作者： Liu, Yongyi Mahmood, Ahmed R. Magdy, Amr Zhu, Minyao University of California Riverside RiversideCA United States Google LLC. Mountain ViewCA United States

The proliferation of location-based services has led to massive spatial data generation. Spatial join is a crucial database operation that identifies pairs of objects from two spatial datasets based on spatial relationships. Due to the intensive computational demands, spatial joins are often executed in a distributed manner across clusters. However, current systems fail to recognize similarities in the partitioning of spatial data, leading to redundant computations and increased overhead. Recently, incorporating machine learning optimizations into database operations has enhanced efficiency in traditional joins by predicting optimal strategies. However, applying these optimizations to spatial joins poses challenges due to the complex nature of spatial relationships and the variability of spatial data. This paper introduces SOLAR, scalable distributed spatial joins through learning-based optimization. SOLAR operates through offline and online phases. In the offline phase, it learns balanced spatial partitioning based on the similarities between datasets in query workloads seen so far. In the online phase, when a new join query is received, SOLAR evaluates the similarity between the datasets in the new query and the already-seen workloads using the trained learning model. Then, it decides to either reuse an existing partitioner, avoiding unnecessary computational overhead, or partition from scratch. Our extensive experimental evaluation on real-world datasets demonstrates that SOLAR achieves up to 3.6X speedup in overall join runtime and 2.71X speedup in partitioning time compared to state-of-the-art systems. © 2025, CC BY.

关键词： mathematical programming