A Probabilistic Approach to Committing Solar Energy in Day-ahead Electricity Markets-Reference-Cited by-同舟云学术

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A Probabilistic Approach to Committing Solar Energy in Day-ahead Electricity Markets

Published:2021-03 Issue: Volume:29 Page:100477
ISSN:2210-5379
Container-title:Sustainable Computing: Informatics and Systems
language:en
Short-container-title:Sustainable Computing: Informatics and Systems

Author:

Bashir Noman,Irwin David,Shenoy Prashant

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science

Reference37 articles.

1. J. Blatchford, Participating Intermittent Resource Program (PIRP), CAISO.

2. Real-Time vs. Day-Ahead Pricing,2018

3. Solar-TK: A Data-driven Toolkit for Solar PV Performance Modeling and Forecasting;Bashir;MASS,2019

4. On Mitigating Wind Energy Variability with Storage;Arya;COMSNETS,2013

5. Overview of New England's Wholesale Electricity Markets and Market Oversight,2014

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1. A Comparative Study of Data Mining Methods for Solar Radiation and Temperature Forecasting Models;JUCS - Journal of Universal Computer Science;2024-06-28

2. Electricity price forecast on day-ahead market for mid- and short terms: capturing spikes in data sequences using recurrent neural network techniques;Electrical Engineering;2024-04-11

3. Predicting Day-Ahead Electricity Market Prices through the Integration of Macroeconomic Factors and Machine Learning Techniques;International Journal of Computational Intelligence Systems;2024-01-15

4. Optimization-driven uncertainty forecasting: Application to day-ahead commitment with renewable energy resources;Applied Energy;2022-11

5. A Strategy for System Risk Mitigation Using FACTS Devices in a Wind Incorporated Competitive Power System;Sustainability;2022-07-01

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