Online Optimization And Decision Making Problems Under Uncertainty In The Power Systems
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Online Optimization And Decision Making Problems Under Uncertainty In The Power Systems
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Author : Yutong Wu
language : en
Publisher:
Release Date : 2023
Online Optimization And Decision Making Problems Under Uncertainty In The Power Systems written by Yutong Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Online optimization addresses problems whose input is incomplete. To solve online optimization problems, the decision maker needs to invent algorithms or mechanisms under uncertainty and achieve a performance comparable to when the information is completely given. The power system, non-surprisingly, is an area rich in online problems. In particular, the expanding use of renewable energy, including wind and solar, has imposed great uncertainty and new challenges on the power grid. Recent large-scale power blackouts also raise discussions about improving stability and fairness in the scheduling of electricity generation. To address these emerging issues, novel online optimization tools catered for the power grid must be considered. In this Ph.D. dissertation, we aim to use online optimization techniques to solve decision-making problems in power systems, when different kinds of uncertainty are present. We choose three emerging online problems in the power systems that can greatly benefit from the proposed optimization frameworks, either in promoting equity among electricity consumers or enhancing the resilience of the existing power infrastructure. Moreover, the invented online algorithms and mechanisms have utilities beyond the power systems and can be used for general online problems in other application areas. The first problem is related to the inequity in the net metering billing scheme that is currently adopted in the electricity market. The growing number of energy prosumers (e.g., solar panel owners), whose gross power consumption is hidden from the public, has been shifting the grid costs to traditional energy consumers, causing great unfairness. We study a penalty mechanism that incentivizes prosumers to report their true consumption, which results in a fairer pricing scheme than net metering. We model the problem as a repeated game with one or multiple players and provide the minimum penalty rates such that players voluntarily report their private value of electricity consumption. The second problem is to address the uncertainty in energy procurement where utility companies need to secure contracts with generators to fulfill the demand. The contracts arrive one by one during a time period and the utility company must decide irrevocably whether to accept the current contract or not. This is an application of the well-known prophet inequality problem. In the literature, the distribution of the value of the contract is known to the utility companies, which is hardly the case in practice. In this work, we consider the setting where the utility company can make a handful of queries to a distribution oracle and has to design algorithms to select the contract such that the value obtained is maximized. We give competitive ratios when two to five queries can be made. When only one query is allowed, we propose an alternative algorithm whose competitive ratio is strictly better than the one obtained from the single-threshold algorithm in the past literature. Finally, for the last problem, we study the classic unit commitment (UC) problem, the scheduling and dispatch of power generators subject to operating constraints so that the total cost is minimized. The UC problem is a special case of the more general location-allocation problems that have been widely adopted in application areas including disaster preparedness and supply chain management. We design a two-stage data-driven robust optimization framework to address general location-allocation problems with two types of uncertainties: the binary network uncertainty and the continuous unknown demand. Moreover, we add fairness constraints to the formulation such that the ratio of the allocated resources to demand is consistent across all regions. We provide tractable reformulations of the original problem and conduct numerical studies for an IEEE test system and the 2010 Yushu earthquake data set. Our simulation results show that the addition of network uncertainties and fairness constraints effectively improves equity and reduces costs
Decision Making Under Uncertainty
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Author : Mykel J. Kochenderfer
language : en
Publisher: MIT Press
Release Date : 2015-07-24
Decision Making Under Uncertainty written by Mykel J. Kochenderfer and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-24 with Computers categories.
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Optimization And Decision Making Under Uncertainty
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Author : Anthony Kim
language : en
Publisher:
Release Date : 2018
Optimization And Decision Making Under Uncertainty written by Anthony Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
We consider several online and repeated decision problems with uncertainty features in resource allocation, energy storage management and internet advertising using worst-case and stochastic models. In the first part, we use worst-case models to design and analyze online algorithms that make irrevocable decisions without any future information. In the online resource allocation problem, a seller allocates items that can be produced at non-decreasing marginal costs per unit to buyers arriving in an online fashion. The objective is to maximize the social welfare which is the sum of the buyers' values less the total production cost. We then consider the energy storage management problem motivated by applications of energy storage networks in smart grids. Given renewable power supplies that generate power unpredictably, a grid operator wants to route power from these online power supplies to offline consumer demands using storage units subject to decay factors. The objective is to maximize the total utility of satisfied demands less the total production cost of routed power. In the second part, we consider the problems of budget management and contract design in internet advertising using stochastic models where a publisher allocates ad impressions given distributional information of advertisers' private valuations. In the budget management problem, the publisher manages advertisers' budgets on their behalf and adjusts allocations and payments such that the advertisers' cumulative expenditures are at most their budgets. Our goal is to study various budget management mechanisms on the bases of the publisher's profit, advertisers' utilities, incentive compatibility properties and uniqueness and stability of an equilibrium notion. For the contract design problem for selling online display advertisements, the publisher wants to sell ad impressions by bundling them via contracts before selling via auctions. The publisher wants to design a sequence of contracts that yields the maximum revenue, where advertisers are assigned priorities and buy bundles of impressions that are not yet purchased by those with higher priorities. Our contributions are both theoretical and empirical. We develop new algorithms and mechanisms with near optimality guarantees and provide characterizations of optimal solutions. We also provide empirical studies based on real datasets to validate our theoretical findings and derive further insights.
Hybrid Offline Online Methods For Optimization Under Uncertainty
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Author : A. De Filippo
language : en
Publisher: IOS Press
Release Date : 2022-04-12
Hybrid Offline Online Methods For Optimization Under Uncertainty written by A. De Filippo and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-12 with Computers categories.
Balancing the solution-quality/time trade-off and optimizing problems which feature offline and online phases can deliver significant improvements in efficiency and budget control. Offline/online integration yields benefits by achieving high quality solutions while reducing online computation time. This book considers multi-stage optimization problems under uncertainty and proposes various methods that have broad applicability. Due to the complexity of the task, the most popular approaches depend on the temporal granularity of the decisions to be made and are, in general, sampling-based methods and heuristics. Long-term strategic decisions that may have a major impact are typically solved using these more accurate, but expensive, sampling-based approaches. Short-term operational decisions often need to be made over multiple steps within a short time frame and are commonly addressed via polynomial-time heuristics, with the more advanced sampling-based methods only being applicable if their computational cost can be carefully managed. Despite being strongly interconnected, these 2 phases are typically solved in isolation. In the first part of the book, general methods based on a tighter integration between the two phases are proposed and their applicability explored, and these may lead to significant improvements. The second part of the book focuses on how to manage the cost/quality trade-off of online stochastic anticipatory algorithms, taking advantage of some offline information. All the methods proposed here provide multiple options to balance the quality/time trade-off in optimization problems that involve offline and online phases, and are suitable for a variety of practical application scenarios.
Online Optimization Of Large Scale Systems
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Author : Martin Grötschel
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Online Optimization Of Large Scale Systems written by Martin Grötschel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Mathematics categories.
In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.
Decision Making Under Uncertainty In Electricity Markets
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Author : Antonio J. Conejo
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-08
Decision Making Under Uncertainty In Electricity Markets written by Antonio J. Conejo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-08 with Business & Economics categories.
Decision Making Under Uncertainty in Electricity Markets provides models and procedures to be used by electricity market agents to make informed decisions under uncertainty. These procedures rely on well established stochastic programming models, which make them efficient and robust. Particularly, these techniques allow electricity producers to derive offering strategies for the pool and contracting decisions in the futures market. Retailers use these techniques to derive selling prices to clients and energy procurement strategies through the pool, the futures market and bilateral contracting. Using the proposed models, consumers can derive the best energy procurement strategies using the available trading floors. The market operator can use the techniques proposed in this book to clear simultaneously energy and reserve markets promoting efficiency and equity. The techniques described in this book are of interest for professionals working on energy markets, and for graduate students in power engineering, applied mathematics, applied economics, and operations research.
The 37th Annual Conference On Power System And Automation In Chinese Universities Cus Epsa
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Author : Pingliang Zeng
language : en
Publisher: Springer Nature
Release Date : 2023-04-24
The 37th Annual Conference On Power System And Automation In Chinese Universities Cus Epsa written by Pingliang Zeng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-24 with Technology & Engineering categories.
This book includes original, peer-reviewed research papers from the 37th Annual Conference of Power System and Automation in Chinese Universities (CUS-EPSA), held in Hangzhou, China on October 23-25, 2022. These papers cover topics as Evolution and development path of the power system, Resilience assessment, analysis and planning of power system, Power system planning and reliability, Modelling and simulation of novel power system, Power electronic for power system stability analysis, Power system relay protection and automation and so on. The papers included in this proceedings share the latest research results and practical application examples on the methodologies and algorithms in these areas, which makes the book a valuable reference for researchers, engineers, and university students.
Handbook Of Smart Cities
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Author : Juan Carlos Augusto
language : en
Publisher: Springer
Release Date : 2021-07-17
Handbook Of Smart Cities written by Juan Carlos Augusto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-17 with Computers categories.
This Handbook presents a comprehensive and rigorous overview of the state-of-the-art on Smart Cities. It provides the reader with an authoritative, exhaustive one-stop reference on how the field has evolved and where the current and future challenges lie. From the foundations to the many overlapping dimensions (human, energy, technology, data, institutions, ethics etc.), each chapter is written by international experts and amply illustrated with figures and tables with an emphasis on current research. The Handbook is an invaluable desk reference for researchers in a wide variety of fields, not only smart cities specialists but also by scientists and policy-makers in related disciplines that are deeply influenced by the emergence of intelligent cities. It should also serve as a key resource for graduate students and young researchers entering the area, and for instructors who teach courses on these subjects. The handbook is also of interest to industry and business innovators.
Stochastic Optimization Methods In Finance And Energy
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Author : Marida Bertocchi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-15
Stochastic Optimization Methods In Finance And Energy written by Marida Bertocchi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-15 with Business & Economics categories.
This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and practitioners, who cooperated in recent years to facilitate the growing penetration of stochastic programming techniques in real-world applications, inducing a significant advance over a large spectrum of complex decision problems. After the recent widespread liberalization of the energy sector in Europe and the unprecedented growth of energy prices in international commodity markets, we have witnessed a significant convergence of strategic decision problems in the energy and financial sectors. This has often resulted in common open issues and has induced a remarkable effort by the industrial and scientific communities to facilitate the adoption of advanced analytical and decision tools. The main concerns of the financial community over the last decade have suddenly penetrated the energy sector inducing a remarkable scientific and practical effort to address previously unforeseeable management problems. Stochastic Optimization Methods in Finance and Energy: New Financial Products and Energy Markets Strategies aims to include in a unified framework for the first time an extensive set of contributions related to real-world applied problems in finance and energy, leading to a common methodological approach and in many cases having similar underlying economic and financial implications. Part 1 of the book presents 6 chapters related to financial applications; Part 2 presents 7 chapters on energy applications; and Part 3 presents 5 chapters devoted to specific theoretical and computational issues.
Power System Simulation Control And Optimization
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Author : José Antonio Domínguez-Navarro
language : en
Publisher: MDPI
Release Date : 2021-06-21
Power System Simulation Control And Optimization written by José Antonio Domínguez-Navarro and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-21 with Technology & Engineering categories.
This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence.