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Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

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posted on 2021-01-01, 02:49 authored by Chinmay ShahChinmay Shah, Richard Wies, Jennifer King
The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, which limits the size of the problem that can be solved, and also creates a high communication overhead since all the data is transferred to the central controller. These limitations are addressed by a proposed consensus-ADMM (alternating direction method of multiplier) based distributed optimization algorithm, which decomposes the optimization problem into sub-problems. The distribution feeder is partitioned into low coupling sub-networks/regions, which solves the sub-problem locally and exchanges information with the neighboring regions to reach consensus to solve for the global update. The information exchange and synchronization between sub-networks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a virtual aggregator for synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for 0.5-MW laboratory microgrid for one hour ahead and day-ahead for IEEE 123-bus and EPRI J1 test feeder, and results are compared with a centralized solution.


U.S. Department of Energy with the Battelle Memorial Institute under Contract DEAC05-76RL01830 and under a subcontract Contract No. 474633 from Pacific Northwest National Laboratories to the University of Alaska Fairbanks.


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University of Alaska Fairbanks

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  • United States of America