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Stochastic Optimal Device Sizing Model for Zero Energy Buildings: A Parallel Computing Solution
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DOI：10.1109/TIA.2022.3159313.png)
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Abstract
En 中文
Byconsuming35% of the final global energy, buildings are among major contributors to greenhouse gas emissions and global warming. If the economic justification challenge is addressed, zero energy buildings (ZEB), which are defined as buildings that generate as much renewable-based energy as they consume annually, can be a promising solution for energy efficiency improvement in the building sector. In this article, we propose a stochastic ZEB device sizing model considering uncertain parameters (i.e., building's electrical and thermal demands, solar irradiation, and outdoor temperature) and their correlation. The proposed model finds the optimal size of the thermal and electrical devices considering their nonlinear behaviors and temperature-dependent dynamics. Furthermore, two parallel computing-based solution algorithms (i.e., parallelism in the algebraic level using Schur complement decomposition and parallelism in the problem (scenario) level by progressive hedging) are proposed to solve the stochastic model. Using the real historical data, numerical studies on the Woodward library building, located on the University of British Columbia campus, illustrate the efficacy of the solution algorithms to handle large-scale nonlinear programming models with more than 32.8 million variables, which is the largest one reported in the literature so far.
Keywords:
Cogeneration
Buildings
Stochastic processes
Heat pumps
Production
Heating systems
Numerical models
Optimal device sizing
parallel computing
progressive hedging
stochastic nonlinear programming
zero energy buildings
Journal
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4.5
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3.5W