Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/233486
Title: Architecture and Algorithms for Privacy Preserving Thermal Inertial Load Management by a Load Serving Entity
Authors: Abhishek Halder;Xinbo Geng;P. R. Kumar;Le Xie
Year: 2017
Publisher: IEEE
Abstract: Motivated by the growing importance of demand response in modern power system's operations, we propose an architecture and supporting algorithms for privacy preserving thermal inertial load management as a service provided by the load serving entity (LSE). We focus on an LSE managing a population of its customers' air conditioners, and propose a contractual model where the LSE guarantees quality of service to each customer in terms of keeping their indoor temperature trajectories within respective bands around the desired individual comfort temperatures. We show how the LSE can price the contracts differentiated by the flexibility embodied by the width of the specified bands. We address architectural questions of (i) how the LSE can strategize its energy procurement based on price and ambient temperature forecasts, (ii) how an LSE can close the real-time control loop at the aggregate level while providing individual comfort guarantees to loads, without ever measuring the states of an air conditioner for privacy reasons. Control algorithms to enable our proposed architecture are given, and their efficacy is demonstrated on real data.
URI: http://localhost/handle/Hannan/233486
volume: 32
issue: 4
More Information: 3275,
3286
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7742416.pdf4.65 MBAdobe PDF
Title: Architecture and Algorithms for Privacy Preserving Thermal Inertial Load Management by a Load Serving Entity
Authors: Abhishek Halder;Xinbo Geng;P. R. Kumar;Le Xie
Year: 2017
Publisher: IEEE
Abstract: Motivated by the growing importance of demand response in modern power system's operations, we propose an architecture and supporting algorithms for privacy preserving thermal inertial load management as a service provided by the load serving entity (LSE). We focus on an LSE managing a population of its customers' air conditioners, and propose a contractual model where the LSE guarantees quality of service to each customer in terms of keeping their indoor temperature trajectories within respective bands around the desired individual comfort temperatures. We show how the LSE can price the contracts differentiated by the flexibility embodied by the width of the specified bands. We address architectural questions of (i) how the LSE can strategize its energy procurement based on price and ambient temperature forecasts, (ii) how an LSE can close the real-time control loop at the aggregate level while providing individual comfort guarantees to loads, without ever measuring the states of an air conditioner for privacy reasons. Control algorithms to enable our proposed architecture are given, and their efficacy is demonstrated on real data.
URI: http://localhost/handle/Hannan/233486
volume: 32
issue: 4
More Information: 3275,
3286
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7742416.pdf4.65 MBAdobe PDF
Title: Architecture and Algorithms for Privacy Preserving Thermal Inertial Load Management by a Load Serving Entity
Authors: Abhishek Halder;Xinbo Geng;P. R. Kumar;Le Xie
Year: 2017
Publisher: IEEE
Abstract: Motivated by the growing importance of demand response in modern power system's operations, we propose an architecture and supporting algorithms for privacy preserving thermal inertial load management as a service provided by the load serving entity (LSE). We focus on an LSE managing a population of its customers' air conditioners, and propose a contractual model where the LSE guarantees quality of service to each customer in terms of keeping their indoor temperature trajectories within respective bands around the desired individual comfort temperatures. We show how the LSE can price the contracts differentiated by the flexibility embodied by the width of the specified bands. We address architectural questions of (i) how the LSE can strategize its energy procurement based on price and ambient temperature forecasts, (ii) how an LSE can close the real-time control loop at the aggregate level while providing individual comfort guarantees to loads, without ever measuring the states of an air conditioner for privacy reasons. Control algorithms to enable our proposed architecture are given, and their efficacy is demonstrated on real data.
URI: http://localhost/handle/Hannan/233486
volume: 32
issue: 4
More Information: 3275,
3286
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7742416.pdf4.65 MBAdobe PDF