Skip to main content
main-content

Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Virtual Power Plants

Abstract
This chapter provides an overview of decision-making problems related to virtual power plants (VPPs). Section 1.1 defines the concept of VPP. Section 1.2 describes the basic organization of current electricity markets. Section 1.3 explains the strong relationship between VPPs and smart grids. Section 1.4 provides an overview of decision-making problems under uncertainty, including stochastic and robust optimization problems. Section 1.5 reviews the different approaches used in the technical literature to deal with operation and planiing problems for VPPs. Finally, Sect. 1.6 clarifies the scope of this book.
Luis Baringo, Morteza Rahimiyan

Chapter 2. Virtual Power Plant Model

Abstract
This chapter provides models for the most common components of virtual power plants (VPPs). Components described below include demands, conventional power plants, stochastic renewable generating units, and energy storage facilities. These components can be interconnected in an electric network, which is also modeled in this chapter. The joint modeling of all these components constitutes the basic model for a VPP, which will be used in the following chapters of this book.
Luis Baringo, Morteza Rahimiyan

Chapter 3. Optimal Scheduling of a Risk-Neutral Virtual Power Plant in Energy Markets

Abstract
This chapter addresses the scheduling problem of a virtual power plant (VPP) in different energy markets. This problem is solved to determine the optimal energy traded by the VPP in these markets, as well as the production and consumption of the energy resources that comprise the VPP with the aim of maximizing the profit of the VPP while complying with the technical constraints of these generation and consumption assets. Therefore, the scheduling problem is essential to achieve an efficient and secure operation of the VPP. Due to uncertainties in the market prices and the available production levels of stochastic renewable generating units, this is a decision-making problem under uncertainty. To accomplish these tasks, the scheduling problem is formulated through two practical options based on deterministic and stochastic approaches. The deterministic approach models the uncertainties involved in the scheduling problem by single-point forecasts, which are used as a single scenario. On the other hand, the stochastic approach models the uncertainties through a number of scenarios. A risk-neutral VPP that is indifferent to financial risks resulting from uncertainties is considered.
Luis Baringo, Morteza Rahimiyan

Chapter 4. Optimal Scheduling of a Risk-Averse Virtual Power Plant in Energy Markets

Abstract
This chapter describes the optimal scheduling problem of a virtual power plant (VPP) participating in energy markets. A risk-averse VPP is considered, i.e., some metrics are introduced on the problem to control the risk associated with the scheduling decisions. With this purpose, four different models are provided and described, namely a stochastic programming problem, a static robust model, a hybrid stochastic-robust problem, and an adaptive robust optimization approach.
Luis Baringo, Morteza Rahimiyan

Chapter 5. Optimal Scheduling of a Virtual Power Plant in Energy and Reserve Markets

Abstract
This chapter analyzes the scheduling problem of a virtual power plant (VPP) participating in energy and reserve electricity markets. On one hand, the VPP sells or buys energy in the energy market with the aim of maximizing its profit while to comply with the technical constraints of the different energy assets in the VPP. On the other hand, the VPP uses the flexibility of these energy resources to participate in the reserve electricity market, i.e., the VPP uses its flexibility to increase or decrease its total power production if requested by the system operator. This problem includes uncertainties in the market prices, the available production levels of stochastic renewable generating units, and the requests for reserve deployments. These uncertainties are modeled using both scenarios and confidence bounds, and the problem is formulated using different approaches based on stochastic programming and robust optimization.
Luis Baringo, Morteza Rahimiyan

Chapter 6. Price-Maker Virtual Power Plants

Abstract
This chapter provides equilibrium-based mathematical models that can be used for scheduling price-maker virtual power plants (VPPs) participating in energy and reserve electricity markets. These mathematical models allow price-maker VPPs to influence the prices in these markets to their own benefit, i.e., the proposed models allow VPPs to exercise market power. Uncertainties in market prices, production levels of stochastic renewable generating units, and reserve deployment requests are addressed in the problem using two different methods based on deterministic and stochastic programming approaches.
Luis Baringo, Morteza Rahimiyan

Chapter 7. Expansion Planning of Virtual Power Plants

Abstract
This chapter describes the expansion planning problem of a virtual power plant (VPP) trading energy in electricity markets. The VPP comprises generating units, including both conventional and stochastic renewable units, storage facilities, and flexible demands. With the aim of maximizing its profit, it has the possibility of building new conventional, stochastic renewable, and storage units. The resulting model is first formulated using a deterministic model that disregards uncertainties. This deterministic model is extended to account for uncertainties using a scenario-based two-stage stochastic programming model. Finally, the profit risk associated with the investment decisions is modeled using the conditional-value-at-risk.
Luis Baringo, Morteza Rahimiyan

Backmatter

Weitere Informationen