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 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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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. |
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| 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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| 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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