[PDF] Stochastic Virtual Bidding In The Two Settlement Electricity Market eBook

Author : Dongliang Xiao
Publisher :
Page : 0 pages
File Size : 42,11 MB
Release : 2019
Category : Electricity
ISBN : 9781392534564

GET BOOK

The short-term electricity markets in the United States have a two-settlement structure, which includes a day-ahead (DA) and a real-time (RT) markets. Virtual bidding is a financial tool available for the participants to earn profits by utilizing the price difference between the DA and RT markets. To better utilize this financial tool to help with the electricity market operation, it is necessary to develop decision-making models for virtual bidders to generate optimal virtual bidding strategies while considering the uncertainties related to the electricity prices and the participants' physical assets. In this dissertation, stochastic optimization-based decision-making models were developed for generating optimal virtual bidding strategies for different types of market participants, and a hybrid electricity price scenario generation method was proposed to improve the virtual bidders' profits.Firstly, bilevel stochastic optimization models were developed for generating the virtual bidding strategies used by two types of physical participants, i.e., a wind power producer and an electricity retailer, respectively. The proposed models considered the participants' risk preferences, the impacts of other participants' bidding strategies on the market clearing processes, and that the physical participants would use virtual bidding at multiple buses, which were not limited to the locations of their generating units or demands, to improve their market power. Case studies were carried out to validate the proposed models for a strategic wind power producer and a retailer, respectively, and the simulation results showed that virtual bidding improved their expected profits. Next, a hybrid electricity price scenario generation method using a seasonal autoregressive integrated moving average (SARIMA) model and historical data was proposed. In the proposed method, the spikes contained in the historical data of the electricity prices were firstly identified by using an outlier detection method; then, the historical data were decomposed into base and spike components; next, the base and spike component scenarios were generated by using the SARIMA- and historical data-based methods, respectively; finally, the electricity price scenarios were obtained by combining the base and spike component scenarios. Case studies were carried out for a virtual bidder in the Pennsylvanian-New Jersey-Maryland (PJM) electricity market to validate the proposed method.

Author : Oliver Grothe
Publisher : Springer Nature
Page : 619 pages
File Size : 50,74 MB
Release : 2023-09-30
Category : Business & Economics
ISBN : 3031249070

GET BOOK

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2022), which was held at Karlsruhe Institute of Technology, Germany, on September 6-9, 2022. KIT’s Institute for Operations Research (IOR) hosted the conference together with the Institute for Industrial Production (IIP), the Institute for Automation and Applied Informatics (IAI), and the Institute for Material Handling and Logistics (IFL). The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.

Author :
Publisher :
Page : 0 pages
File Size : 26,98 MB
Release : 2023
Category :
ISBN :

GET BOOK

This work presents a novel method for generating electricity price scenarios from statistical properties of past electricity prices using a hybrid statistical and reduced-form stochastic model. Previous work in applying stochastic differential equations (SDE) to model electricity prices has focused on daily average prices. To extend stochastic price generation methods to hourly or sub-hourly pricing, we address several weaknesses in the state-of-the-art: (1) we replace the mean-reversion component of the SDE with an ARIMA process that is better able to characterize the daily and weekly trends; (2) we extend the price-spike, or jump process to account for conditional probabilities of price spikes occurring in consecutive time steps by replacing the traditional Poisson process for modeling jumps with a generalized point process model inspired by brain neuron models; and (3) we replace the traditional method of estimating spike intensity with empirical variance with a Markov process based on observed price spike intensity transitions. The method is demonstrated with electricity prices from the US ERCOT market and a use-case example is provided for bidding an energy storage unit into the day-ahead and real-time energy markets of ERCOT using stochastic optimization methods. Results show that the the synthetic price model out performs a (naive) persistence forecast model by resulting in 24% to 47% more in profits over 168 simulated days.

Author : John E. Parsons
Publisher :
Page : 57 pages
File Size : 41,54 MB
Release : 2015
Category :
ISBN :

GET BOOK

Virtual bidding is a type of transaction introduced into wholesale electricity markets to improve competition and pricing. This paper analyzes the theory behind virtual bidding and describes circumstances under which it does not work as advertised. The case for virtual bidding is predicated on an oversimplified model of the multi-settlement market design. The complexity of the unit commitment and optimal power flow problems forces the actual market algorithms to make compromises with the theoretical model. These compromises create situations in which virtual bidders can profit without improving system performance. Indeed, in these situations, virtual bidding can add real costs to system operation. The paper illustrates this with a specific case study of virtual bidding in California, and with a matching numerical illustration. The paper explains the general nature of the problem with experiences in other regions and other situations. The fault with virtual bidding identified in this paper needs to be incorporated into any assessment of the costs and benefits of virtual bidding.

Author : Fred Espen Benth
Publisher : World Scientific
Page : 352 pages
File Size : 49,93 MB
Release : 2008
Category : Business & Economics
ISBN : 981281230X

GET BOOK

The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives.This book provides a concise and rigorous treatment on the stochastic modeling of energy markets. Ornstein?Uhlenbeck processes are described as the basic modeling tool for spot price dynamics, where innovations are driven by time-inhomogeneous jump processes. Temperature futures are studied based on a continuous higher-order autoregressive model for the temperature dynamics. The theory presented here pays special attention to the seasonality of volatility and the Samuelson effect. Empirical studies using data from electricity, temperature and gas markets are given to link theory to practice.

Author : Fred Espen Benth
Publisher : World Scientific
Page : 352 pages
File Size : 12,95 MB
Release : 2008-04-14
Category : Business & Economics
ISBN : 9814471313

GET BOOK

The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives.This book provides a concise and rigorous treatment on the stochastic modeling of energy markets. Ornstein-Uhlenbeck processes are described as the basic modeling tool for spot price dynamics, where innovations are driven by time-inhomogeneous jump processes. Temperature futures are studied based on a continuous higher-order autoregressive model for the temperature dynamics. The theory presented here pays special attention to the seasonality of volatility and the Samuelson effect. Empirical studies using data from electricity, temperature and gas markets are given to link theory to practice.

Author : Stefan Schöne
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 41,46 MB
Release : 2009-01-06
Category : Business & Economics
ISBN : 3540853650

GET BOOK

Electricity is an essential commodity traded at power exchanges. Its price is very volatile within a day and over the year. This raises questions about the efficiency of the trading rules. The author develops a non-cooperative auction model analyzing the bidding behavior of producers at power exchanges. Producers are limited by the production capacity of their power plants. Production costs are affiliated. This allows for independence or positive correlation. The author analyzes and compares a uniform-price, a discriminatory, and a generalized second-price auction. Optimal bids, cost efficiency, profits, and consumer prices are examined. A simple probability density function of affiliated production costs is given and used for examples. Numerical results are presented. The results of the analysis can help improving the bidding strategies of producers, selecting the best auction type at power exchanges or detecting price manipulations.

Author : Antonio J. Conejo
Publisher : Springer Science & Business Media
Page : 549 pages
File Size : 41,21 MB
Release : 2010-09-08
Category : Business & Economics
ISBN : 1441974210

GET BOOK

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.

Author : Ning Zhang
Publisher : CRC Press
Page : 372 pages
File Size : 29,16 MB
Release : 2019-02-21
Category : Technology & Engineering
ISBN : 042984770X

GET BOOK

The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration.The first part presents mathematical theories of stochastic mathematics; the second presents modeling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.