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.

Around the world, liberalization and privatization in the electricity industry have lead to increased competition among utilities. At the same time, utilities are now exposed more than ever to risk and uncertainties, which they cannot pass on to their customers through price increases as in a regulated environment. Especially electricity-generating companies have to face volatile wholesale prices, fuel price uncertainty, limited long-term hedging possibilities and huge, to a large extent, sunk investments. In this context, Uncertainty in the Electric Power Industry: Methods and Models for Decision Support aims at an integrative view on the decision problems that power companies have to tackle. It systematically examines the uncertainties power companies are facing and develops models to describe them - including an innovative approach combining fundamental and finance models for price modeling. The optimization of generation and trading portfolios under uncertainty is discussed with particular focus on CHP and is linked to risk management. Here the concept of integral earnings at risk is developed to provide a theoretically sound combination of value at risk and profit at risk approaches, adapted to real market structures and market liquidity. Also methods for supporting long-term investment decisions are presented: technology assessment based on experience curves and operation simulation for fuel cells and a real options approach with endogenous electricity prices.

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.

Bridges the knowledge gap between engineering and economics in a complex and evolving deregulated electricity industry, enabling readers to understand, operate, plan and design a modern power system With an accessible and progressive style written in straight-forward language, this book covers everything an engineer or economist needs to know to understand, operate within, plan and design an effective liberalized electricity industry, thus serving as both a useful teaching text and a valuable reference. The book focuses on principles and theory which are independent of any one market design. It outlines where the theory is not implemented in practice, perhaps due to other over-riding concerns. The book covers the basic modelling of electricity markets, including the impact of uncertainty (an integral part of generation investment decisions and transmission cost-benefit analysis). It draws out the parallels to the Nordpool market (an important point of reference for Europe). Written from the perspective of the policy-maker, the first part provides the introductory background knowledge required. This includes an understanding of basic economics concepts such as supply and demand, monopoly, market power and marginal cost. The second part of the book asks how a set of generation, load, and transmission resources should be efficiently operated, and the third part focuses on the generation investment decision. Part 4 addresses the question of the management of risk and Part 5 discusses the question of market power. Any power system must be operated at all times in a manner which can accommodate the next potential contingency. This demands responses by generators and loads on a very short timeframe. Part 6 of the book addresses the question of dispatch in the very short run, introducing the distinction between preventive and corrective actions and why preventive actions are sometimes required. The seventh part deals with pricing issues that arise under a regionally-priced market, such as the Australian NEM. This section introduces the notion of regions and interconnectors and how to formulate constraints for the correct pricing outcomes (the issue of "constraint orientation"). Part 8 addresses the fundamental and difficult issue of efficient transmission investment, and finally Part 9 covers issues that arise in the retail market. Bridges the gap between engineering and economics in electricity, covering both the economics and engineering knowledge needed to accurately understand, plan and develop the electricity market Comprehensive coverage of all the key topics in the economics of electricity markets Covers the latest research and policy issues as well as description of the fundamental concepts and principles that can be applied across all markets globally Numerous worked examples and end-of-chapter problems Companion website holding solutions to problems set out in the book, also the relevant simulation (GAMS) codes

Electric market dynamic problems, as observed in practice after deregulation, need to be studied to improve market design and maintain market reliability. This work studies electric market dynamics, generation companies (GENCOs) decision-making, and impact of GENCO decisions on market from a new viewpoint using control theory, decision analysis and decision theory. The first part of this work simulates electricity price and output dynamics in electric markets and studies impact of GENCO decision on markets. The problem is examined from the viewpoint of an Independent Contract Administrator (ICA) to examine market performances and activities of GENCOs in different situations: expectations of market participants, competition types, market risk levels, and market organizations. Electric markets are modeled as control systems and decision-making of GENCOs and interactions between them are modeled as control processes. Simulation results show that interactions between GENCOs, as well as market risk, competition types, and market organizations, have significant impacts on GENCOs' decisions and market properties. Results also show that properties of GENCOs and their decisions have important effects on market performance. Sometimes their legitimate actions may even cause market dynamic problems. Models developed can help ICA study market participants activities and simulate market performance, thus improve market design and maintain market reliability. The second part of this study is from GENCOs' viewpoint to develop optimal short-term decision-making strategies and models. GENCOs short-term decision-making in deregulated environment is identified as a three dimensional problem: to make optimal decisions for different time in different geographical markets in different service markets to maximize total gain. A new market-based generation scheduling scheme is proposed to solve the problem. Market rules, competitor's activities, uncertainty, bidding strategies, and technical constraints are all included in the scheme. Dynamic Programming is adopted to solve the problem. Results show that in new environment, GENCO's optimal generation schedules may be very different from schedules proposed in previous work. This short-term scheduling scheme can also be used to model GENCOs in market models for further market dynamic simulation. Finally, GENCO long-term decision-making is compared with short-term and the method to study long-term decision making for GENCO is proposed.

The challenges currently facing particIpants m competitive electricity markets are unique and staggering: unprecedented price volatility, a crippling lack of historical market data on which to test new modeling approaches, and a continuously changing regulatory structure. Meeting these challenges will require the knowledge and experience of both the engineering and finance communities. Yet the two communities continue to largely ignore each other. The finance community believes that engineering models are too detailed and complex to be practically applicable in the fast changing market environment. Engineers counter that the finance models are merely statistical regressions, lacking the necessary structure to capture the true dynamic properties of complex power systems. While both views have merit, neither group has by themselves been able to produce effective tools for meeting industry challenges. The goal of this book is to convey the fundamental differences between electricity and other traded commodities, and the impact these differences have on valuation, hedging and operational decisions made by market participants. The optimization problems associated with these decisions are formulated in the context of the market realities of today's power industry, including a lack of liquidity on forward and options markets, limited availability of historical data, and constantly changing regulatory structures.