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2014 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Integrating Renewables in Electricity Markets

Operational Problems

verfasst von: Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno

Verlag: Springer US

Buchreihe : International Series in Operations Research & Management Science

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This addition to the ISOR series addresses the analytics of the operations of electric energy systems with increasing penetration of stochastic renewable production facilities, such as wind- and solar-based generation units.

As stochastic renewable production units become ubiquitous throughout electric energy systems, an increasing level of flexible backup provided by non-stochastic units and other system agents is needed if supply security and quality are to be maintained.

Within the context above, this book provides up-to-date analytical tools to address challenging operational problems such as:

• The modeling and forecasting of stochastic renewable power production.
• The characterization of the impact of renewable production on market outcomes.
• The clearing of electricity markets with high penetration of stochastic renewable units.
• The development of mechanisms to counteract the variability and unpredictability of stochastic renewable units so that supply security is not at risk.
• The trading of the electric energy produced by stochastic renewable producers.
• The association of a number of electricity production facilities, stochastic and others, to increase their competitive edge in the electricity market.
• The development of procedures to enable demand response and to facilitate the integration of stochastic renewable units.

This book is written in a modular and tutorial manner and includes many illustrative examples to facilitate its comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, applied mathematics and economics. Practitioners in the electric energy sector will benefit as well from the concepts and techniques explained in this book.

Inhaltsverzeichnis

Frontmatter
1. Introduction
Abstract
The subject matter of this book is inspired by the fact that today’s power systems are experiencing an increasing penetration of renewable energy sources that are nondispatchable—their output cannot or can only partly be modulated upon request—and stochastic—their production cannot be perfectly predicted in advance. Against this background, the operational practices that, for many decades, have governed the functioning of power systems are now to be challenged and revisited to accommodate the uncertain and variable nature of these energy sources. This first chapter motivates the operational problems dealt with in this book by providing a brief overview of the main challenges originated from the growing integration of stochastic and intermittent generation in current electric energy systems.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
2. Renewable Energy Sources—Modeling and Forecasting
Abstract
Short-term forecasts of renewable power generation are a necessary input to nearly all operational problems in electricity markets. For instance, both market and system operators may use them for the clearing of day-ahead and real-time electricity markets. In addition, market participants rely on forecasts for determining their optimal offering strategies in view of uncertainties brought in by renewable energy production. The various forms of renewable power predictions are introduced here based on real-world examples. Special emphasis is placed on probabilistic forecasts in their general form and to scenarios mimicking spatial and temporal dependencies, as well as potential dependencies among different types of renewable energy sources. The way forecasts are issued and subsequently evaluated is also covered.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
3. Clearing the Day-Ahead Market with a High Penetration of Stochastic Production
Abstract
This chapter motivates, develops, and explains a market-clearing algorithm for the day-ahead market, intended for electric energy markets with a significant number of stochastic producers. To adequately mimic the real-world decision-making process, a two-stage stochastic programming model with recourse is presented. Market outcomes include both production and consumption quantities, and energy-only clearing prices. These prices embody desirable properties such as revenue adequacy in expectation and cost recovery, also in expectation. Complementarily, and as alternative to the two-stage stochastic programming approach, this chapter also introduces a dispatch method for energy and reserve that copes with uncertain generation using adaptive robust optimization. A number of clarifying examples illustrate the theoretical interest and practical relevance of the proposed market-clearing algorithms.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
4. Balancing Markets
Abstract
This chapter explains the role of balancing markets in current power systems and introduces their functioning. It also provides several clearing algorithms, whose output is the optimal adjustments of production and consumption with respect to the day-ahead schedules, as well as the balancing energy prices. The development of such clearing algorithms emphasizes the differences between the implementation of a single-price and of a two-price settlements of imbalances. Furthermore, it shows how proactive demands and stepwise offers can be incorporated in the market clearing, and how balancing markets are cleared in a system with network constraints. These issues are further clarified through a number of simple examples. Finally, the main features of existing balancing markets in the USA and in Europe are briefly discussed.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
5. Managing Uncertainty with Flexibility
Abstract
As stochastic production units such as those based on wind or solar sources involve both high variability and high uncertainty, system flexibility is needed to accommodate such variability and uncertainty. System flexibility, which is analyzed in this chapter from the viewpoint of the Independent System Operator, involves preventive and corrective actions by conventional power plants, the demand, pumped-storage plants, as well as the availability of sufficient transmission capacity. This chapter analyzes the flexibility provided by these agents and illustrates its effects on system operations and costs through a number of examples.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
6. Impact of Stochastic Renewable Energy Generation on Market Quantities
Abstract
Electricity generation from stochastic renewable energy sources, such as wind and solar power, has a non-negligible impact on electricity markets. The origins of that impact relate to the economical aspects of stochastic renewable energy in electricity markets (the socalled merit-order effect), the variability and predictability of their power output, as well as the nonlinear and bounded nature of the electric power generation process itself. The way this impact materializes for the case of different market quantities (e.g., dayahead prices, system imbalance magnitude and direction, etc.) is further analyzed, while the underlying mechanisms are presented. Methodologies for the empirical analysis of that impact are finally described and applied to the case of the Nord Pool market in Scandinavia.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
7. Trading Stochastic Production in Electricity Pools
Abstract
Renewable electricity producers must trade in day-ahead electricity markets in the same manner as conventional producers. However, their power production may be highly unpredictable and nondispatchable. This is the case, for example, of wind and solar power producers, which thus need to use the balancing market to mend eventual deviations with respect to their day-ahead schedule. This chapter presents close formulae to determine the optimal offering strategy of stochastic producers in the day-ahead market. The analytical solution to these formulae is available under certain assumptions on the probabilistic structure characterizing power production and market prices. Stochastic programming is then introduced as a powerful mathematical framework to rid the solution to the trading problem for stochastic producers of these simplifying assumptions.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
8. Virtual Power Plants Virtual power plant
Abstract
The power systems of the future are expected to rely more and more on small-scale generation sources, flexible loads, and storage units at the distribution level as a way to increase the share of renewable energy in the electricity supply, while ensuring the security, reliability, and integrity of the electrical infrastructure. Owing to their reduced size, number, varied nature, and dispersed character, distributed energy sources are to be operated in aggregations or clusters, which have come to be called Virtual Power Plants (VPP). This chapter first introduces and motivates the concept of a VPP, then provides the basics on the mathematical modeling of its constituent parts, and finally explores, using a battery of illustrative examples, different approaches to efficiently running a VPP that includes weather-driven renewable energy sources.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
9. Facilitating Renewable Integration by Demand Response Demand response
Abstract
Demand response is seen as one of the resources with the greatest potential to support a large integration of renewables. Indeed, consumer flexibility can help address the shortcomings of renewable sources with respect to conventional ones, namely, their intermittent and stochastic nature. Within this framework, real-time dynamic pricing is expected to incentivize small consumers to participate in demand response. This chapter models the involvement of small consumers in demand response programs with real-time prices. In the first part of the chapter, the stochastic optimization problem of small consumers exposed to dynamic pricing is studied. Formulations of the problem based on stochastic programming and robust optimization are presented, and put in the framework of model predictive control (MPC). Then, the issue of forecasting the aggregate response of flexible consumers to time-varying prices is addressed. Finally, the last part of the chapter deals with the determination of optimal dynamic price signals, aimed at making the most out of the consumer flexibility.
Juan M. Morales, Antonio J. Conejo, Henrik Madsen, Pierre Pinson, Marco Zugno
Backmatter
Metadaten
Titel
Integrating Renewables in Electricity Markets
verfasst von
Juan M. Morales
Antonio J. Conejo
Henrik Madsen
Pierre Pinson
Marco Zugno
Copyright-Jahr
2014
Verlag
Springer US
Electronic ISBN
978-1-4614-9411-9
Print ISBN
978-1-4614-9410-2
DOI
https://doi.org/10.1007/978-1-4614-9411-9