Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services

• Published in: IEEE transactions on smart grid Vol. 9; no. 5; pp. 4335 - 4345
• Main Authors: Hao, He, Wu, Di, Lian, Jianming, Yang, Tao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Arbitrage; Batteries; Buildings; Cost control; Demand response; Electrical loads; Energy; Energy management; Energy storage; Flexibility; flexibility evaluation; generalized battery model; grid and end user services; HVAC systems; Load modeling; optimal coordination; Power grids; Smart grid; Temperature control; Thermal resistance; Time of use; User services
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2017.2655083

Demand response and energy storage play a profound role in the smart grid. The focus of this paper is to evaluate benefits of coordinating flexible loads and energy storage to provide power grid and end user services. We present a generalized battery model (GBM) to describe the flexibility of building loads and energy storage. An optimization-based approach is proposed to characterize the parameters (power and energy limits) of the GBM for flexible building loads. We then develop optimal coordination algorithms to provide power grid and end user services such as energy arbitrage, frequency regulation, spinning reserve, as well as energy cost and demand charge reduction. Several case studies have been performed to demonstrate the efficacy of the GBM and coordination algorithms, and evaluate the benefits of using their flexibility for power grid and end user services. We show that optimal coordination yields significant cost savings and revenue. Moreover, the best option for power grid services is to provide energy arbitrage and frequency regulation. Furthermore, when coordinating flexible loads with energy storage to provide end user services, it is recommended to consider demand charge in addition to time-of-use price in order to flatten the aggregate power profile.