Modeling of thermal storage systems in MILP distributed energy resource models

Steen, David; Stadler, Michael; Cardoso, Gonçalo; Groissböck, Markus; DeForest, Nicholas; Marnay, Chris

doi:10.1016/j.apenergy.2014.07.036

Title: Modeling of thermal storage systems in MILP distributed energy resource models

Journal Article · Mon Aug 04 00:00:00 EDT 2014 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2014.07.036· OSTI ID:1163653

Steen, David ^[1]; Stadler, Michael ^[2]; Cardoso, Gonçalo ^[3]; Groissböck, Markus ^[2]; DeForest, Nicholas ^[4]; Marnay, Chris ^[4]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chalmers Univ. of Technology, Goteborg (Sweden)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovative Technologies(CET), Hofamt Priel (Austria)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of Lisbon (Portugal)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO₂ emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Ultimately,results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Electricity (OE)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1163653

Alternate ID(s):: OSTI ID: 1247566

Report Number(s):: LBNL-6757E

Journal Information:: Applied Energy, Vol. 137, Issue C; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 111 works

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A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage Urbanucci, Luca; D’Ettorre, Francesco; Testi, Daniele Energies, Vol. 12, Issue 5 https://doi.org/10.3390/en12050875	journal	March 2019
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