We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory we identify the optimal strategies of agents with market impact and exhibit the Nash equilibrium in closed form for a finite number of agents as well as in the asymptotic framework of mean field games. Our model reproduces the empirical features of intraday market prices, such as increasing price volatility at the approach of the delivery date and the correlation between price and renewable infeed forecasts, and relates these features with market characteristics like liquidity, number of agents, and imbalance penalty.
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.
As uncertainty and time granularity of short-term electricity markets increase, and intraday trading gains in importance, the complexity of deriving optimal trading decisions rises. This paper analyses the potential benefit of coordinating bids in three sequential electricity markets, facilitating a three-stage stochastic optimisation. The modelled markets comprise the typical European market setting of a balancing reserve, a day-ahead and an intraday market. Because of limited intraday market liquidity, the trading strategies also consider price impacts. The results show that coordinated bidding has the potential to increase profitability and that the size of gains depends on the price impact consideration. In a case study with a biomass and photovoltaic portfolio operating in Germany, we find that coordinated bidding increases the average revenue by around 18% over all analysed type days. With the continued increase of renewable generation, trading strategies that coordinate bids across markets are expected to further gain importance.
This book analyzes new electricity pricing models that consider uncertainties in the power market due to the changing behavior of market players and the implementation of renewable distributed generation and responsive loads. In-depth chapters examine the different types of market players including the generation, transmission, and distribution companies, virtual power plants, demand response aggregators, and energy hubs and microgrids. Expert authors propose optimal operational models for short-term performance and scheduling and present readers with solutions for pricing challenges in uncertain environments. This book is useful for engineers, researchers and students involved in integrating demand response programs into smart grids and for electricity market operation and planning. Proposes optimal operation models; Discusses the various players in today's electricity markets; Describes the effects of demand response programs in smart grids.
This book constitutes the conference proceedings of the 10th International Conference on Network Games, Control and Optimization, NETGCOOP 2020, held in Cargèse, Corsica, France, in September 2021*.The 12 full papers and 16 short papers were carefully reviewed and selected from 44 submissions. The papers are organized in the following topical sections: game theory and iterative algorithms applied to wireless communication; stochastic models for network performance analysis; game theory in mobile and wireless networks; scheduling and resource allocation problems in networks; advance in game theory; social network; electrical network. * The conference was postponed to 2021 due to the COVID-19 pandemic.
This book is aimed at university students in engineering, in particular graduated students in the electrical engineering area who want to learn more about topics such as the operation of electricity markets and the related policy decisions. The book starts with providing the fundamental theory of economics and regulation in relation to the electricity sector and then recalls the theory of nodal prices for the valuation of electrical energy at a power system buses. Numerical examples are used to clarify the implications of the theoretical models presented. Along with the theoretical aspects of valuating electricity, the book addresses the organisation of markets, including the real case example of the Italian power exchange, the options for capacity markets, the valuation of investments in transmission capacity and the congestion management, briefly recalling the current state of European markets integration. Environmental externalities are addressed while focusing on the current state of emission trading systems and the support for renewable energy. Finally, price formation and financial products supporting electricity trading are discussed.
This two-volume book offers a comprehensive treatment of the probabilistic approach to mean field game models and their applications. The book is self-contained in nature and includes original material and applications with explicit examples throughout, including numerical solutions. Volume I of the book is entirely devoted to the theory of mean field games without a common noise. The first half of the volume provides a self-contained introduction to mean field games, starting from concrete illustrations of games with a finite number of players, and ending with ready-for-use solvability results. Readers are provided with the tools necessary for the solution of forward-backward stochastic differential equations of the McKean-Vlasov type at the core of the probabilistic approach. The second half of this volume focuses on the main principles of analysis on the Wasserstein space. It includes Lions' approach to the Wasserstein differential calculus, and the applications of its results to the analysis of stochastic mean field control problems. Together, both Volume I and Volume II will greatly benefit mathematical graduate students and researchers interested in mean field games. The authors provide a detailed road map through the book allowing different access points for different readers and building up the level of technical detail. The accessible approach and overview will allow interested researchers in the applied sciences to obtain a clear overview of the state of the art in mean field games.
Offering a concise but complete survey of the common features of the microstructure of electricity markets, this book describes the state of the art in the different proposed electricity price models for pricing derivatives and in the numerical methods used to price and hedge the most prominent derivatives in electricity markets, namely power plants and swings. The mathematical content of the book has intentionally been made light in order to concentrate on the main subject matter, avoiding fastidious computations. Wherever possible, the models are illustrated by diagrams. The book should allow prospective researchers in the field of electricity derivatives to focus on the actual difficulties associated with the subject. It should also offer a brief but exhaustive overview of the latest techniques used by financial engineers in energy utilities and energy trading desks.
Understand the electricity market, its policies and how they drive prices, emissions, and security, with this comprehensive cross-disciplinary book. Author Chris Harris includes technical and quantitative arguments so you can confidently construct pricing models based on the various fluctuations that occur. Whether you?re a trader or an analyst, this book will enable you to make informed decisions about this volatile industry.
