Work

Construction and Empirical Analysis of ESCO Risk Early Warning Model for Energy-Saving Retrofit Project of Existing Buildings Based on Cloud Matter Element Theory in China

Year: 2025

Type: article

Abstract: The energy-saving retrofit (ESR) of existing buildings under the energy performance contracting (EPC) mode depends on the effective risk early warnings of energy service companies (ESCOs); therefore, this paper constructs an ESCO risk early warning model for energy-saving retrofit projects of existing buildings based on cloud matter element theory (CMET). The ESCO risk early warning indicator system is established according to the essential characteristics of ESR projects of existing buildings. The subjective weighting method (G1 method) and the objective weighting method (entropy weight method) are introduced to determine the comprehensive weights of ESCO risk early warning indicators. The ESCO risk warning level of ESR projects of existing buildings is evaluated based on the cloud matter element model concerning the randomness and ambiguity of the ESCO risk early warning indicators. Finally, the risk early warning model is applied to the ESCO risk management practice of an existing building ESR project in Tianjin. By comparing the actual project and the risk early warning model constructed in this paper, it is concluded that the model has high levels of feasibility, reasonableness, and efficiency. This model has scientific guidance value for ESCO enterprise risk control.

Source: Energies

DOI: 10.3390/en18061390

Authors: Handing Guo, Siman Jia, Mingyu Wang, Yinxian Zhang

Institutions: Sanjiang University, Tianjin Chengjian University

Language: English

Topic: Extenics and Innovation Methods

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $3,137