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Most approaches for designing self-assembled materials focus on the thermodynamic stability of a target structure or crystal polymorph. Yet in practice, the outcome of a self-assembly process is often controlled by kinetic pathways. Here we…

Soft Condensed Matter · Physics 2025-05-08 Sambarta Chatterjee , William M. Jacobs

Though considerable effort has been devoted to exploiting generation-side and demand-side operational flexibility in order to cope with uncertain renewable generations, grid-side operational flexibility has not been fully investigated. In…

Optimization and Control · Mathematics 2018-06-08 Jia Li , Feng Liu , Zuyi Li , Chengcheng Shao , Xinyuan Liu

In this paper, to address backhaul capacity bottleneck and concurrently optimize energy consumption and delay, we formulate a novel weighted-sum multi-objective optimization problem where popular content caching placement and integrated…

Optimization and Control · Mathematics 2022-01-21 Wen Shang , Vasilis Friderikos

The goal of multi-objective optimization is to understand optimal trade-offs between competing objective functions by finding the Pareto front, i.e., the set of all Pareto optimal solutions, where no objective can be improved without…

Multi-objective optimization is a widely studied problem in diverse fields, such as engineering and finance, that seeks to identify a set of non-dominated solutions that provide optimal trade-offs among competing objectives. However, the…

Neural and Evolutionary Computing · Computer Science 2024-01-15 Arash Heidari , Sebastian Rojas Gonzalez , Tom Dhaene , Ivo Couckuyt

We study the trade-offs between strategyproofness and other desiderata, such as efficiency or fairness, that often arise in the design of random ordinal mechanisms. We use approximate strategyproofness to define manipulability, a measure to…

Computer Science and Game Theory · Computer Science 2017-01-11 Timo Mennle , Sven Seuken

Motivated by the increasing need to hedge against load and generation uncertainty in the operation of power grids, we propose flexibility maximization during operation. We consider flexibility explicitly as the amount of uncertainty that…

Optimization and Control · Mathematics 2025-01-27 Aron Zingler , Stephane Fliscounakis , Patrick Panciatici , Alexander Mitsos

The goal of multi-objective optimisation is to identify the Pareto front surface which is the set obtained by connecting the best trade-off points. Typically this surface is computed by evaluating the objectives at different points and then…

Machine Learning · Statistics 2024-06-24 Ben Tu , Nikolas Kantas , Robert M. Lee , Behrang Shafei

As the share of variable renewable energy sources increases in the electricity mix, new solutions are needed to build a flexible and reliable grid. Energy arbitrage with battery storage systems supports renewable energy integration into the…

Optimization and Control · Mathematics 2025-12-17 Alban Puech , Gorazd Dimitrov , Claudia D'Ambrosio

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid strategies like demand response and peak shaving. In…

Machine Learning · Computer Science 2024-11-26 Dafang Zhao , Xihao Piao , Zheng Chen , Zhengmao Li , Ittetsu Taniguchi

Flexible load at the demand-side has been regarded as an effective measure to cope with volatile distributed renewable generations. To unlock the demand-side flexibility, this paper proposes a peer-to-peer energy sharing mechanism that…

Optimization and Control · Mathematics 2021-09-09 Yue Chen , Wei Wei , Mingxuan Li , Laijun Chen , João P. S. Catalão

Microgrids with energy storage systems and distributed renewable energy sources play a crucial role in reducing the consumption from traditional power sources and the emission of $CO_2$. Connecting multi microgrid to a distribution power…

Neural and Evolutionary Computing · Computer Science 2021-03-12 Jiangjiao Xu , Ke Li , Mohammad Abusara

In multi-task learning, multiple tasks are solved jointly, sharing inductive bias between them. Multi-task learning is inherently a multi-objective problem because different tasks may conflict, necessitating a trade-off. A common compromise…

Machine Learning · Computer Science 2019-01-14 Ozan Sener , Vladlen Koltun

In this paper, we propose a control framework for a battery energy storage system to provide simultaneously multiple services to the electrical grid. The objective is to maximise the battery exploitation from these services in the presence…

Signal Processing · Electrical Eng. & Systems 2018-10-15 Emil Namor , Fabrizio Sossan , Rachid Cherkaoui , Mario Paolone

Offshore wind farms have emerged as a popular renewable energy source that can generate substantial electric power with a low environmental impact. However, integrating these farms into the grid poses significant complexities. To address…

Systems and Control · Electrical Eng. & Systems 2024-09-23 Himanshu Sharma , Wei Wang , Bowen Huang , Thiagarajan Ramachandran , Veronica Adetola

Solutions to multi-objective optimization problems can generally not be compared or ordered, due to the lack of orderability of the single objectives. Furthermore, decision-makers are often made to believe that scaled objectives can be…

Optimization and Control · Mathematics 2022-05-31 Sebastian Hönel , Welf Löwe

Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point…

Systems and Control · Computer Science 2016-12-05 Alireza Majzoobi , Amin Khodaei

A market consisting of a generator with thermal and renewable generation capability, a set of non-preemptive loads (i.e., loads which cannot be interrupted once started), and an independent system operator (ISO) is considered. Loads are…

Systems and Control · Electrical Eng. & Systems 2021-12-14 Nathan Dahlin , Rahul Jain

To date, the multi-objective optimization literature has mainly focused on conflicting objectives, studying the Pareto front, or requiring users to balance tradeoffs. Yet, in machine learning practice, there are many scenarios where such…

Machine Learning · Computer Science 2025-03-05 Yonathan Efroni , Ben Kretzu , Daniel Jiang , Jalaj Bhandari , Zheqing , Zhu , Karen Ullrich

The idea of changing our energy system from a hierarchical design into a set of nearly independent microgrids becomes feasible with the availability of small renewable energy generators. The smart microgrid concept comes with several…

Emerging Technologies · Computer Science 2018-07-03 Anita Sobe , Wilfried Elmenreich