Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations

Scioletti, Michael S.; Newman, Alexandra M.; Goodman, Johanna K.; Zolan, Alexander J.; Leyffer, Sven

doi:10.1007/s11081-017-9355-4

Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations

Journal Article · Mon May 08 00:00:00 EDT 2017 · Optimization and Engineering

DOI:https://doi.org/10.1007/s11081-017-9355-4· OSTI ID:1393847

Scioletti, Michael S. ^[1]; Newman, Alexandra M. ^[1]; Goodman, Johanna K. ^[2]; Zolan, Alexander J. ^[3]; Leyffer, Sven ^[4]

Colorado School of Mines, Golden, CO (United States). Dept. of Mechanical Engineering
Georgia Inst. of Technology, Atlanta, GA (United States). School of Chemical and Biomolecular Engineering
Univ. of Texas, Austin, TX (United States). Dept. of Mechanical Engineering
Argonne National Lab. (ANL), Argonne, IL (United States). Mathematics and Computer Science Division

Renewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from larger grids. If sized correctly, hybrid systems reduce fuel consumption compared to diesel generator-only alternatives. We present an optimization model for establishing a hybrid power design and dispatch strategy for remote locations, such as a military forward operating base, that models the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, mixed-integer, nonlinear program contains a detailed battery model. Due to its complexities, we present linearizations, which include exact and convex under-estimation techniques, and a heuristic, which determines an initial feasible solution to serve as a “warm start” for the solver. We determine, in a few hours at most, solutions within 5% of optimality for a candidate set of technologies; these solutions closely resemble those from the nonlinear model. Lastly, our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1393847

Journal Information:: Optimization and Engineering, Journal Name: Optimization and Engineering Journal Issue: 3 Vol. 18; ISSN 1389-4420

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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