Pricing Information in Smart Grids: A Quality-Based Data Valuation Paradigm

Hydrogen‐powered smart grid resilience

“…Many studies have indicated that existing control technologies cannot meet the emergency dispatching requirements for massive amounts of distributed resources. Focusing on the major requirements of new power system construction and high‐quality development of hydrogen energy, we should master large‐scale electrolytic hydrogen production equipment and control technology that adapts to fluctuating power sources as soon as possible; strengthen the development of new high‐density hydrogen storage materials; explore new transfer technologies, such as large‐scale ammonia and alcohol production; break through the core technology of the fuel cell material‐component‐system link; strengthen the integration and co‐construction of integrated electricity–hydrogen systems with information, big data, artificial intelligence, and other technologies; build an industrial big data platform based on a combination of intelligent technology and resilient integrated electricity–hydrogen systems; and support industrial development [144]. Innovating and improving market mechanisms and building a new business development model.…”

End-to-end Distributed Video Coding

“…Thus, the second is to study how forecasting accuracy improvements affect operation costs, leading to the quantification of the economic value of data [10]. [11] utilized Shannon entropy and non-noise ratio as two metrics to measure the quality of photovoltaics-related data and then constructed a reflection from selected metrics to the load forecasting accuracy. On this basis, the economic value of data assets was quantified by simulating a stochastic unit commitment using forecasting results of various accuracy.…”