Equilibrium Forward Risk Premiums in Electricity Markets
The Journal of Energy Markets(2013)
Virginia Polytech Inst & State Univ
Abstract
This paper develops an equilibrium electricity forward pricing model which explicitly accounts for constrained capacity. The model is able to reproduce the price spikes observed in wholesale electricity markets using reasonable parameter values. The equilibrium forward premium, defined as the forward price minus the expected spot price, decreases in spot price variance when the expected spot price is less than the retail price, but increases in spot price variance when the expected spot price is greater than the retail price. The forward premium is an increasing function of the ratio of the expected spot price to the retail price.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2005
被引用211 | 浏览
2008
被引用133 | 浏览
2008
被引用114 | 浏览
2008
被引用145 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest