Techno-economic model for long-term revenue prediction in distribution grids incorporating distributed energy resources

• Published in: Frontiers in energy research Vol. 11
• Main Authors: Lou, Qihe, Li, Yanbin
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 16.11.2023
• Subjects: dist flow model; distributed energy resources; distribution network; system dynamics; techno-economic model
• ISSN: 2296-598X; 2296-598X
• DOI: 10.3389/fenrg.2023.1261268

Distributed energy resources (DER) is a prevalent technology in distribution grids. However, it poses challenges for distribution network operators to make optimal decisions, estimate total investment returns, and forecast future grid operation performance to achieve investment development objectives. Conventional methods mostly rely on current data to conduct a static analysis of distribution network investment, and fail to account for the impact of dynamic variations in relevant factors on a long-term scale on distribution network operation and investment revenue. Therefore, this paper proposes a techno-economic approach to distribution networks considering distributed generation. First, the analysis method of the relationship between each investment subject and distribution network benefit is established by using the system dynamics model, and the indicator system for distribution network investment benefit analysis is constructed. Next, the distribution network operation technology model based on the dist flow approach is employed. This model takes into account various network constraints and facilitates the comprehensive analysis of distribution network operation under dynamic changes in multiple factors. Consequently, the technical index parameters are updated to reflect these changes. This updated information is then integrated into the system dynamics model to establish an interactive simulation of the techno-economic model. Through rigorous verification using practical examples, the proposed method is able to obtain the multiple benefits of different investment strategies and be able to select the better solution. This can provide reference value for future power grid planning.