Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market

Smart Grid;Electricity Market;Distributed Control;Multi-Agent System (MAS);Internet-of-Things (IoT);Bitcoin;Electrical Engineering;Electrical Engineering, College of Engineering and Computer Science

Luo, JingweiZheng, Yu ;

University of Michigan

关键词: Smart Grid;    Electricity Market;    Distributed Control;    Multi-Agent System (MAS);    Internet-of-Things (IoT);    Bitcoin;    Electrical Engineering;    Electrical Engineering, College of Engineering and Computer Science;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/136613/MS%20Thesis%20JingweiLuo%20-%2011F.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The power grid is undergoing a transformation from a monopolized control system to a more decentralized one. Distributed renewable energy generation, responsive loads, and distribution automation are posing a new challenge to the traditional centralized control method. To address these challenges, we propose two innovative centralized and decentralized solutions for the information infrastructure of the future electricity market. For the centralized approach, we investigate the applications of an open-source control system platform VOLTTRON in the areas of building control and electric vehicle charging. For the case study, we implement the VOLTTRON platform to solve the economic dispatch (ED) problem. The VOLTTRON platform is used as a central message bus and 16 single-board computers are used to simulate distributed generators and dispatchable loads. For the decentralized approach, we propose an innovative Bitcoin-style distributed transactional model ;;Bit-Energy” using radically different Internet-of-Things technologies (Blockchain and Ethereum’s smart contract). ;;Bit-Energy” enables transparent, auditable, and peer-to-peer energy transactions between active market participants. We implement a highly efficient buyer/seller matching algorithm. Case studies demonstrate the accuracy, robustness, effectiveness, and scalability of the proposed Bit-Energy platform under various operating conditions.