This dissertation develops an interdisciplinary approach to integrating renewable energy resources into energy markets, using tools from optimization theory, power systems, and economics. It advances prior work with the development of a set of tools for securing distributed and fully-decentralized optimization problems, including both algorithmic guards against attacks by malicious nodes, and system architectures which can enable decentralized security checks. Leveraging the emerging technologies of blockchains and smart contracts, it develops a new paradigm of blockchain-secured distributed optimization, demonstrated with simulation of a microgrid which is able to securely operate without oversight from a utility or central operator. As the goal of interdisciplinary research is to show mastery of each field and extend current knowledge by exploring their intersection, the chapters of this dissertation are designed to support that goal: • Chapter 1 provides background on the technical challenges of integrating high amounts of renewable energy into the electricity system, and discusses technologies and policies which can address those challenges. • Chapter 2 introduces the idea of applying optimization tools to energy systems by studying a small-scale energy harvesting system in which batteries and capacitors are used to meet a defined load, and constraints force the use of nonlinear optimization techniques. • Chapter 3 explores how large-scale energy storage systems can be designed and sited to maximize profits from participating in wholesale energy markets, using a linear program which demonstrates how convex optimization tools can be united with energy market data to create scalable tools for modeling large networks. • Chapter 4 expands the study of market-based models by examining the strategic operation of generation resources on a congested network. We use game theory to model participants’ behavior, power flow models to reflect the underlying constraints of the physical network, and robust convex optimization to explore how uncertainty is integrated into decision-making. • Chapter 5 discusses how decentralized optimization models can facilitate scalable optimization tools, and explores the security risks which these optimization models introduce. Tools for detection and mitigation of attacks are explored and tested on a simple problem. Potential architectures for securing decentralized optimization are explored, including blockchains and smart contracts. • Chapter 6 extends this approach by developing a blockchain-secured fully-decentralized optimization for a microgrid dispatch problem, coordinating distributed energy resources. By demonstrating the usefulness of this blockchain-secured optimization model, this culminating chapter shows how difficult optimization models can be scalably solved in a manner which respects privacy while guaranteeing security. • The Appendices present tutorial material on the tools used throughout the paper, and are supplemented by the code in the author’s github repository: https://github.com/emunsing/tutorials.

As power and gas markets are becoming more and more mature and globally competitive, the importance of reaching maximum potential economic efficiency is fundamental in all the sectors of the value chain, from investments selection to asset optimization, trading and sales. Optimization techniques can be used in many different fields of the energy industry, in order to reduce production and financial costs, increase sales revenues and mitigate all kinds of risks potentially affecting the economic margin. For this reason the industry has now focused its attention on the general concept of optimization and to the different techniques (mainly mathematical techniques) to reach it. Optimization Methods for Gas and Power Markets presents both theoretical elements and practical examples for solving energy optimization issues in gas and power markets. Starting with the theoretical framework and the basic business and economics of power and gas optimization, it quickly moves on to review the mathematical optimization problems inherent to the industry, and their solutions – all supported with examples from the energy sector. Coverage ranges from very long-term (and capital intensive) optimization problems such as investment valuation/diversification to asset (gas and power) optimization/hedging problems, and pure trading decisions. This book first presents the readers with various examples of optimization problems arising in power and gas markets, then deals with general optimization problems and describes the mathematical tools useful for their solution. The remainder of the book is dedicated to presenting a number of key business cases which apply the proposed techniques to concrete market problems. Topics include static asset optimization, real option evaluation, dynamic optimization of structured products like swing, virtual storage or virtual power plant contracts and optimal trading in intra-day power markets. As the book progresses, so too does the level of mathematical complexity, providing readers with an appreciation of the growing sophistication of even common problems in current market practice. Optimization Methods for Gas and Power Markets provides a valuable quantitative guide to the technicalities of optimization methodologies in gas and power markets; it is essential reading for practitioners in the energy industry and financial sector who work in trading, quantitative analysis and energy risk modeling.

Optimization in Renewable Energy Systems: Recent Perspectives covers all major areas where optimization techniques have been applied to reduce uncertainty or improve results in renewable energy systems (RES). Production of power with RES is highly variable and unpredictable, leading to the need for optimization-based planning and operation in order to maximize economies while sustaining performance. This self-contained book begins with an introduction to optimization, then covers a wide range of applications in both large and small scale operations, including optimum operation of electric power systems with large penetration of RES, power forecasting, transmission system planning, and DG sizing and siting for distribution and end-user premises. This book is an excellent choice for energy engineers, researchers, system operators, system regulators, and graduate students. - Provides chapters written by experts in the field - Goes beyond forecasting to apply optimization techniques to a wide variety of renewable energy system issues, from large scale to relatively small scale systems - Provides accompanying computer code for related chapters

This book opens up new ways to develop mathematical models and optimization methods for interdependent energy infrastructures, ranging from the electricity network, natural gas network, district heating network, and electrified transportation network. The authors provide methods to help analyze, design, and operate the integrated energy system more efficiently and reliably, and constitute a foundational basis for decision support tools for the next-generation energy network. Chapters present new operation models of the coupled energy infrastructure and the application of new methodologies including convex optimization, robust optimization, and equilibrium constrained optimization. Four appendices provide students and researchers with helpful tutorials on advanced optimization methods: Basics of Linear and Conic Programs; Formulation Tricks in Integer Programming; Basics of Robust Optimization; Equilibrium Problems. This book provides theoretical foundation and technical applications for energy system integration, and the the interdisciplinary research presented will be useful to readers in many fields including electrical engineering, civil engineering, and industrial engineering.

This textbook provides a detailed analysis of operation and planning problems faced by virtual power plants participating in different electricity markets. The chapters address in-depth, topics such as: optimization, market power, expansion, and modelling uncertainty in operation and planning problems of virtual power plants. The book provides an up-to-date description of decision-making tools to address challenging questions faced by virtual power plants such as: How can virtual power plants optimize their participation in electricity markets? How can a virtual power plant exercise market power? How can virtual power plants be optimally expanded? How can uncertainty be efficiently modelled in the operation and planning problems of virtual power plants? The book is written in a tutorial style and modular format, and includes many illustrative examples to facilitate comprehension. It is intended for a diverse audience including advanced undergraduate and graduate students in the fields of electric energy systems, operations research, and economics. Practitioners in the energy sector will also benefit from the concepts and techniques presented in this book. In particular, this book: Provides students with the GAMS codes to solve the examples in the book; Provides a basis for the formulation of decision-making problems under uncertainty; Contains a blend of theoretical concepts and practical applications that are developed as working algorithms.

Annotation Today's need-to-know optimization techniques, at your fingertips The use of optimization methods is familiar territory to academicians and researchers. Yet, in today's world of deregulated electricity markets, it's just as important for electric power professionals to have a solid grasp of these increasingly relied upon techniques. Making those techniques readily accessible is the hallmark of Optimization Principles: Practical Applications to the Operation and Markets of the Electric Power Industry. With deregulation, market rules and economic principles dictate that commodities be priced at the marginal value of their production. As a result, it's necessary to work with ever-more-sophisticated algorithms using optimization techniques-either for the optimal dispatch of the system itself, or for pricing commodities and the settlement of markets. Succeeding in this new environment takes a good understanding of methods that involve linear and nonlinear optimization, including optimal power flow, locational marginal prices for energy, and the auction of hedging instruments. In its comprehensive, skill-building overview of optimization techniques, Optimization Principles puts you on the same footing with algorithm-savvy software developers. Starting with a helpful look at matrix algebra fundamentals, this just-in-time reference covers: * Deregulated electricity markets: terminology and acronyms * Solution of equations, inequalities, and linear programs * Unconstrained and constrained nonlinear optimization * Applications to practical problems addressing system dispatch, market design, and material procurement * And related topics As an aid to the uninitiated, appendices provide a brief description of basic principles of electricity, and the development of network equations. Optimization Principles allows you to learn optimization methods at your own pace using Microsoft Excel or MATLAB software, and it includes an FTP web site with downloadable Excel spreadsheets and problems. After mastering these practical applications, you can then refer to chapters that highlight the theoretical background of the algorithms and resulting solutions. The book also includes a Web site with downloadable files of all example problems and solved problems. Ideal for engineers, other electric power professionals, and advanced engineering students, Optimization Principles demystifies the electric power industry under deregulation-and delivers a complete, learn-as-you-go tutorial of optimization techniques that no other resource can match.

Integrated circuit densities and operating speeds continue to rise at an exponential rate. Chips, however, cannot get larger and faster without a sharp decrease in power consumption beyond the current levels. Minimization of power consumption in VLSI chips has thus become an important design objective. In fact, with the explosive growth in demand for portable electronics and the usual push toward more complex functionality and higher performance, power consumption has in many cases become the limiting factor in satisfying the market demand. A new generation of power-conscious CAD tools are coming onto the market to help designers estimate, optimize and verify power consumption levels at most stages of the IC design process. These tools are especially prevalent at the register-transfer level and below. There is a great need for similar tools and capabilities at the behavioral and system levels of the design process. Many researchers and CAD tool developers are working on high-level power modeling and estimation, as well as power-constrained high-level synthesis and optimization. Techniques and tools alone are, however, insufficient to optimize VLSI circuit power dissipation - a consistent and convergent design methodology is also required. Power Optimization and Synthesis at Behavioral and System Levels Using Formal Methods was written to address some of the key problems in power analysis and optimization early in the design process. In particular, this book focuses on power macro-modeling based on regression analysis and power minimization through behavioral transformations, scheduling, resource assignment and hardware/software partitioning and mapping. What differentiates this book from other published work on the subject is the mathematical basis and formalism behind the algorithms and the optimality of these algorithms subject to the stated assumptions. From the Foreword: `This book makes an important contribution to the field of system design technologies by presenting a set of algorithms with guaranteed optimality properties, that can be readily applied to system-level design. This contribution is timely, because it fills the need of new methods for a new design tool generation, which supports the design of electronic systems with even more demanding requirements'. Giovanni De Micheli, Professor, Stanford University

Regulation of the Power Sector is a unified, consistent and comprehensive treatment of the theories and practicalities of regulation in modern power-supply systems. The need for generation to occur at the time of use occasioned by the impracticality of large-scale electricity storage coupled with constant and often unpredictable changes in demand make electricity-supply systems large, dynamic and complex and their regulation a daunting task. Arranged in four parts, this book addresses both traditional regulatory frameworks and also liberalized and re-regulated environments. First, an introduction gives a full characterization of power supply including engineering, economic and regulatory viewpoints. The second part presents the fundamentals of regulation and the third looks at the regulation of particular components of the power sector in detail. Advanced topics and subjects still open or subject to dispute form the content of Part IV. In a sector where regulatory design is the key driver of both the industry efficiency and the returns on investment, Regulation of the Power Sector is directed at regulators, policy decision makers, business managers and researchers. It is a pragmatic text, well-tested by the authors’ quarter-century of experience of power systems from around the world. Power system professionals and students at all levels will derive much benefit from the authors’ wealth of blended theory and real-world-derived know-how.

This addition to the ISOR series introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques. In a nutshell, complementarity models generalize: a. optimization problems via their Karush-Kuhn-Tucker conditions b. on-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions) c. conomic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria) d. roblems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES). As such, complementarity models are a very general and flexible modeling format. A natural question is why concentrate on energy markets for this complementarity approach? s it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems. The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold. Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning. Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers.

Classical and Recent Aspects of Power System Optimization presents conventional and meta-heuristic optimization methods and algorithms for power system studies. The classic aspects of optimization in power systems, such as optimal power flow, economic dispatch, unit commitment and power quality optimization are covered, as are issues relating to distributed generation sizing, allocation problems, scheduling of renewable resources, energy storage, power reserve based problems, efficient use of smart grid capabilities, and protection studies in modern power systems. The book brings together innovative research outcomes, programs, algorithms and approaches that consolidate the present state and future challenges for power. Analyzes and compares several aspects of optimization for power systems which has never been addressed in one reference Details real-life industry application examples for each chapter (e.g. energy storage and power reserve problems) Provides practical training on theoretical developments and application of advanced methods for optimum electrical energy for realistic engineering problems