A two-stage procedure for the optimal sizing and placement of grid-level energy storage

• Published in: Computers & chemical engineering Vol. 114; pp. 265 - 272
• Main Authors: Adeodu, Oluwasanmi, Chmielewski, Donald J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 09.06.2018
• Subjects: Economic MPC; Energy storage; Smart grid; System design; System design; Smart grid; Economic MPC; Energy storage
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2017.10.033

•Introduce economic model predictive control (EMPC) as a viable economic dispatch policy for transmission networks with energy storage.•Illustrate that the numeric basis of EMPC makes it ill-suited for the optimal energy storage sizing and placement problem.•Develop an economic linear optimal control (ELOC) based algorithm for the energy storage and placement problem, which will yield a global solution, but must relax point-wise in-time constraints to statistical constraints.•Propose a novel 2-step algorithm that begins with the ELOC-based approach to determine the placement of energy storage units, followed by an EMPC-based gradient search to determine optimal sizes. The economic benefit realized from energy storage units on the electric grid is linked to the control policy selected to govern grid operations. Thus, the optimal sizing and placement (OSP) of such units is also dependent on the operating policy of the power network. In this work, we first introduce economic model predictive control (EMPC) as a viable economic dispatch policy for transmission networks with energy storage. However, the numeric basis of EMPC makes it ill-suited for the OSP problem. In contrast, the method of economic linear optimal control (ELOC) can be easily adapted to the OSP problem. However, the relaxation of point-wise-in-time constraints, inherent to ELOC, will introduce a systematic underestimation of operating costs. Thus, we introduce a 2-step OSP algorithm that begins with the ELOC-based approach to determine the placement of energy storage units. Then, an EMPC-based gradient search is used to determine optimal sizes.