(373ai) A Blockchain Model for Residential Distributed Energy Resources Networks
The blockchain technology can fulfil these requirements by enabling the implementation of optimal energy management strategies through distributed databases. Since its introduction as the underlying technology of Bitcoin, the blockchain technology has emerged from its use as a verification mechanism for cryptocurrencies and heads to a broader field of applications. Blockchain-based systems are basically a combination of a distributed ledger, a decentralised consensus mechanism, and cryptographic security measures . More precisely, it allows the resolution of conflicts and dismantles information asymmetries by providing transparent and valid records of past transactions that cannot be altered retrospectively . With the help of specific algorithms and applications, multiple operations can be performed automatically on the blockchain, using this information together with information from the Internet or the real world (e.g. on whether, energy pricing, etc.). Furthermore, smart contracts can be implemented between the nodes of the microgrid.
This paper introduces a model for the implementation of a blockchain and smart contracts into the scheduling of a residential DER network. The blockchain is implemented in terms of energy rather than voltages , to allow for the decentralised operation of the microgrid without a centralised microgrid aggregator. Thus, the model will minimise only the operational cost. Furthermore, the DER network model is improved by the addition of more detailed transmission losses and costs within the microgrid and between the microgrid and the national grid. The resulted energy flows are stored and information on the availability/demand are exchanged between the network nodes. To appropriately compensate the DER operators in the microgrid for their services and to charge the consumers for withdrawals, nodal clearing prices are determined and implemented through smart contracts. The resulting MILP model minimises the overall investment and operating costs of the system.
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