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

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.
 [1] ;  [1] ;  [2] ;  [3] ;  [4]
  1. Colorado School of Mines, Golden, CO (United States). Dept. of Mechanical Engineering
  2. Georgia Inst. of Technology, Atlanta, GA (United States). School of Chemical and Biomolecular Engineering
  3. Univ. of Texas, Austin, TX (United States). Dept. of Mechanical Engineering
  4. Argonne National Lab. (ANL), Argonne, IL (United States). Mathematics and Computer Science Division
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Optimization and Engineering
Additional Journal Information:
Journal Volume: 18; Journal Issue: 3; Journal ID: ISSN 1389-4420
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
25 ENERGY STORAGE; 14 SOLAR ENERGY; Hybrid energy systems; Optimization; Mixed-integer programming
OSTI Identifier: