Modeling of thermal storage systems in MILP distributed energy resource models
Abstract
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 somemore »
- Authors:
-
- 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)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Electricity (OE)
- OSTI Identifier:
- 1163653
- Alternate Identifier(s):
- OSTI ID: 1247566
- Report Number(s):
- LBNL-6757E
Journal ID: ISSN 0306-2619
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 137; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 25 ENERGY STORAGE; 54 ENVIRONMENTAL SCIENCES; 99 GENERAL AND MISCELLANEOUS; Distributed energy resources; Investment planning; Renewables; Energy optimization; Thermal energy storage
Citation Formats
Steen, David, Stadler, Michael, Cardoso, Gonçalo, Groissböck, Markus, DeForest, Nicholas, and Marnay, Chris. Modeling of thermal storage systems in MILP distributed energy resource models. United States: N. p., 2014.
Web. doi:10.1016/j.apenergy.2014.07.036.
Steen, David, Stadler, Michael, Cardoso, Gonçalo, Groissböck, Markus, DeForest, Nicholas, & Marnay, Chris. Modeling of thermal storage systems in MILP distributed energy resource models. United States. https://doi.org/10.1016/j.apenergy.2014.07.036
Steen, David, Stadler, Michael, Cardoso, Gonçalo, Groissböck, Markus, DeForest, Nicholas, and Marnay, Chris. Mon .
"Modeling of thermal storage systems in MILP distributed energy resource models". United States. https://doi.org/10.1016/j.apenergy.2014.07.036. https://www.osti.gov/servlets/purl/1163653.
@article{osti_1163653,
title = {Modeling of thermal storage systems in MILP distributed energy resource models},
author = {Steen, David and Stadler, Michael and Cardoso, Gonçalo and Groissböck, Markus and DeForest, Nicholas and Marnay, Chris},
abstractNote = {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.},
doi = {10.1016/j.apenergy.2014.07.036},
journal = {Applied Energy},
number = C,
volume = 137,
place = {United States},
year = {Mon Aug 04 00:00:00 EDT 2014},
month = {Mon Aug 04 00:00:00 EDT 2014}
}
Web of Science
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