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Calendar 2017 Poster Sessions : PowerNet Cloud Coordinator: Cost Minimization with Batteries in Distribution Grid
Abstract:
We consider the problem of controlling distributed storage in a distribution network with renewable distributed generation to minimize network operational cost while satisfying power quality constraints. Challenges involve incomplete information due to delays and the stochastic nature of loads and renewable generation, while maintaining power quality over a coupled network. We distribute control between a network and local controllers called the Cloud Coordinator (CC) and Home Hubs (HH) respectively. Each HH has access to its most recent data and runs frequently while the CC has delayed data due to smart meter infrastructure or communication network delay, hence runs less frequently. We describe three control schemes: Direct Storage Controller (DSC), Net Load Following Controller (NLFC), and Nodal Slack Controller (NSC). We use a radial network with real load data to compare the performance of these schemes based on arbitrage profit and maximum solar penetration relative to a perfect foresight controller. We find adding HH control improves robustness to information delay, while the NLFC improves power quality under distributed renewable generation and NSC improves arbitrage profits.
Bio:
Thomas Navidi is a Ph.D. Student in Electrical Engineering at Stanford University. He is a part of the PowerNet project for the cloud coordinator algorithms team. His research interests are to develop clever ways to control renewable energy to make it more appealing worldwide.
We consider the problem of controlling distributed storage in a distribution network with renewable distributed generation to minimize network operational cost while satisfying power quality constraints. Challenges involve incomplete information due to delays and the stochastic nature of loads and renewable generation, while maintaining power quality over a coupled network. We distribute control between a network and local controllers called the Cloud Coordinator (CC) and Home Hubs (HH) respectively. Each HH has access to its most recent data and runs frequently while the CC has delayed data due to smart meter infrastructure or communication network delay, hence runs less frequently. We describe three control schemes: Direct Storage Controller (DSC), Net Load Following Controller (NLFC), and Nodal Slack Controller (NSC). We use a radial network with real load data to compare the performance of these schemes based on arbitrage profit and maximum solar penetration relative to a perfect foresight controller. We find adding HH control improves robustness to information delay, while the NLFC improves power quality under distributed renewable generation and NSC improves arbitrage profits.
Bio:
Thomas Navidi is a Ph.D. Student in Electrical Engineering at Stanford University. He is a part of the PowerNet project for the cloud coordinator algorithms team. His research interests are to develop clever ways to control renewable energy to make it more appealing worldwide.