Energy optimization of the smart stand-alone buildings considering renewable energy resources

Xiaodan  Liang; Dan  Wang; Yalong  Liu

doi:10.6180/jase.202505_28(5).0003

Energy optimization of the smart stand-alone buildings considering renewable energy resources

Xiaodan Liang¹, Dan Wang², and Yalong Liu¹This email address is being protected from spambots. You need JavaScript enabled to view it.

¹School of Digital Construction, Shanghai Urban Construction Vocational College, Yangpu 200438, Shanghai, China

²Shanghai Jianke Architectural Design Institute CO., Ltd. Xuhui 200032, Shanghai, China

Received: March 9, 2024
Accepted: May 17, 2024
Publication Date: July 10, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202505_28(5).0003

The utilization of fossil fuels for energy generation leads to the release of harmful emissions, posing a threat to the environment. Therefore, the promotion of energy conservation through the adoption of new energy systems and the utilization of renewable energy resources (RERs) has become a significant focus across various sectors of the energy industry. This study evaluates the economic viability of intelligent residential buildings by optimizing the integration of controllable appliances within an independent electrical residential network. The proposed methodology emphasizes achieving an efficient coordination between controllable appliances and RERs, with the coordination being modeled through the load shifting model (LSM) of the demand side management (DSM) strategy. The power generation from RERs is analyzed using stochastic modeling techniques to address uncertainties. The technical and economic modeling of the stand-alone electrical residential network is formulated as a multi-criteria problem. To solve this problem, the augmented ε-constraint method and fuzzy logic techniques are employed. Finally, numerical simulations are conducted across various case studies to validate and demonstrate the effectiveness of the proposed approach.

Keywords: Smart residential buildings; controllable appliances; stand-alone electrical residential network; load shifting model (LSM); multi-criteria problem

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