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Bi-objective mixed integer linear programming for managing building clusters with a shared electrical energy storage

Rui Dai(ruidai***at***mail.usf.edu)
Hadi Charkhgard(hcharkhgard***at***usf.edu)

Abstract: Emerging smart grid infrastructures are allowing buildings to connect to components in other buildings and utilize them in different ways. Clearly, these interconnected building clusters provide new opportunities for building operators to collaborate and help reduce their operational costs over a planning horizon. Nevertheless, since each building can be treated as an independent decision maker here, related fairness concerns have to be addressed in these collaborative environments. We address these issues on building clusters when a single electrical energy storage is shared between two buildings with deterministic demand. We introduce three energy storage sharing strategies, and develop a bi-objective mathematical formulation for each strategy. Several techniques such as piecewise McCormick relaxation are employed for linearizing non-linear terms in the proposed formulations. An extensive computational study demonstrates the efficacy of our proposed linearization techniques, and compares all three strategies in terms of fairness and freedom.

Keywords: smart buildings, shared energy storage, piecewise McCormick relaxation, bi-objective mixed integer linear programming

Category 1: Other Topics (Multi-Criteria Optimization )

Category 2: Integer Programming ((Mixed) Integer Linear Programming )

Citation:

Download: [PDF]

Entry Submitted: 02/10/2017
Entry Accepted: 02/10/2017
Entry Last Modified: 02/10/2017

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