Power-to-gas (P2G) application in managing network constraints
Power-to-Gas, Page: 161-179
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Book Chapter Description
In line with zero-carbon targets, countries rely on renewable generation as a clean resource to attain a sustainable solution to the energy trilemma. The coincidence of high production of renewable resources and power transmission congestion can impose restrictions on the output of renewable sources. The described situation imposes a significant penalty on the electricity system operators due to the need for constraint payments (CP) to be conducted to renewable resources. The imposed CP to renewables, which is ultimately recovered from final energy consumers, can jeopardize the optimality of system operation. This chapter presents a hybrid bridging-operational framework that uses the vector-bridging system and electrical energy storage to address the issue and enhance operational efficiency. The proposed model is a multi-vector scheduling framework for electricity and gas in a day-ahead energy market.
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