A Blockchain-Enabled Trading Framework for Distributed Photovoltaic Power Using Federated Learning

Table 1

An overview of related work.

Type	Source	Contribution	Limitation
Power predicting	[6]	An approach grounded in historical electricity data	Additional recent historical data
	[7]	The combination of multiple variables	Greater demand for data
	[8]	Dynamic artificial neural network	Greater demand for data
	[9]	The correlation between different weather variables and PV power	Greater demand for data
	[10]	FL	Insecurity and single-point failure
Blockchain in electricity trading	[11]	The introduction of settlement mechanism	Neglect of transaction subjects
	[12]	Blockchain for risk management	Neglect of transaction subjects
	[13]	New consensus protocol	Neglect of blockchain performance
	[14]	Auction mechanism for microgrids	Incapability of automated transactions
	[15]	Smart contract for implementation of rules	Without considering future generation capacity
	[16]	Proposal of a joint energy-reserve prosumer-centric market	Without considering future generation capacity