A Stochastic Bi-Level Optimal Allocation Approach of Intelligent Buildings Considering Energy Storage Sharing Services

To decrease the investment cost of energy storage for urbanization purposes, a stochastic bi-level optimal allocation approach of intelligent buildings (IBs) considering energy storage sharing (ESS) services is proposed. First, based on the thermal inertia (TI) of buildings and the lifecycle of ener...

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Published in:IEEE transactions on consumer electronics Vol. 70; no. 3; pp. 5142 - 5153
Main Authors: Zhang, Haopeng, Li, Zening, Xue, Yixun, Chang, Xinyue, Su, Jia, Wang, Peng, Guo, Qinglai, Sun, Hongbin
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0098-3063, 1558-4127
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Abstract To decrease the investment cost of energy storage for urbanization purposes, a stochastic bi-level optimal allocation approach of intelligent buildings (IBs) considering energy storage sharing (ESS) services is proposed. First, based on the thermal inertia (TI) of buildings and the lifecycle of energy storage devices, a detailed thermal dynamic model of IBs equipped with air conditioning (AC) systems and the ESS station model are established respectively. Then, a stochastic bi-level optimal allocation model of IBs considering ESS services is established to consider the uncertainties of electricity prices. Given the different interests of the ESS station and IBs, the upper-level model aims to reduce the planning costs of the ESS station, and the lower-level model aims to reduce the annual operating costs of IBs. Finally, the nonlinear bi-level model is converted into a single-level mixed-integer linear programming problem using the Karush-Kuhn-Tucher (KKT) condition. The results show that while meeting the temperature comfort demands of IBs users, the proposed stochastic bi-level optimal allocation approach can guarantee the interests of different agents under the uncertainties of electricity prices and achieve a win-win situation for the ESS station and IBs.
AbstractList To decrease the investment cost of energy storage for urbanization purposes, a stochastic bi-level optimal allocation approach of intelligent buildings (IBs) considering energy storage sharing (ESS) services is proposed. First, based on the thermal inertia (TI) of buildings and the lifecycle of energy storage devices, a detailed thermal dynamic model of IBs equipped with air conditioning (AC) systems and the ESS station model are established respectively. Then, a stochastic bi-level optimal allocation model of IBs considering ESS services is established to consider the uncertainties of electricity prices. Given the different interests of the ESS station and IBs, the upper-level model aims to reduce the planning costs of the ESS station, and the lower-level model aims to reduce the annual operating costs of IBs. Finally, the nonlinear bi-level model is converted into a single-level mixed-integer linear programming problem using the Karush-Kuhn-Tucher (KKT) condition. The results show that while meeting the temperature comfort demands of IBs users, the proposed stochastic bi-level optimal allocation approach can guarantee the interests of different agents under the uncertainties of electricity prices and achieve a win-win situation for the ESS station and IBs.
Author Zhang, Haopeng
Chang, Xinyue
Li, Zening
Wang, Peng
Guo, Qinglai
Xue, Yixun
Sun, Hongbin
Su, Jia
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Snippet To decrease the investment cost of energy storage for urbanization purposes, a stochastic bi-level optimal allocation approach of intelligent buildings (IBs)...
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SubjectTerms Air conditioning
Cost allocation
Dynamic models
Electricity pricing
Energy costs
Energy storage
energy storage sharing
Integer programming
intelligent building
Linear programming
Mixed integer
Operating costs
Optimization
Resource management
Smart buildings
stochastic bi-level optimization
Stochastic processes
thermal inertia
Uncertainty
Title A Stochastic Bi-Level Optimal Allocation Approach of Intelligent Buildings Considering Energy Storage Sharing Services
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Volume 70
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