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Existing design methodologies for off-grid wind–solar–hydrogen integrated energy systems (WSH-IES) are typically case-specific and lack portability. This study aims to establish a unified design framework to enhance cross-scenario applicability while retaining case-specific adaptability. The proposed framework employs the superstructure concept, dividing the off-grid WSH-IES into three subsystems: energy production, conversion, and storage subsystems. The framework integrates equipment selection and capacity sizing into a unified optimization process described by a mixed-integer programming model. Additionally, the modular constraint template ensures generalizability across scenarios by linking the local resource protocol to the techno-economic parameters of the equipment, allowing the model to be adapted to various situations. The model was applied to two case studies. Economic analysis indicates that the pure electricity architecture is dominated by energy storage (battery costs account for 96.8%), while the hybrid architecture redistributes expenditures between batteries (67.8%) and electrolyzers (28.4%). It utilizes hydrogen as a complementary medium for long-duration energy storage, achieving cost risk diversification and enhanced resilience. Under current techno-economic conditions, real-time bidirectional electricity–hydrogen conversion offers no economic benefits. This framework quantifies cost drivers and design trade-offs for off-grid WSH-IES, providing an open modeling platform for academic research and planning applications.
Details
Hydrogen storage;
Integer programming;
Mathematical models;
Hydrogen;
Clean technology;
Energy storage;
Optimization techniques;
Systems design;
Heuristic;
Superstructures;
Case studies;
Mathematical programming;
Design optimization;
Economic conditions;
Electricity;
Sustainable development;
Energy costs;
Logic;
Integrated energy systems;
Maintenance costs;
Optimization;
Flexibility;
Endowment;
Variables;
Linear programming;
Algorithms;
Mixed integer;
Subsystems;
Real time;
Economic analysis
; Zuo Xin 1 ; Bu Zhijun 3 ; Li, Jian 3 ; Tan Chaodong 1
1 Department of Automation, China University of Petroleum, Beijing 102249, China; [email protected] (L.L.); [email protected] (X.Z.); [email protected] (C.T.)
2 Department of Automation, China University of Petroleum, Beijing 102249, China; [email protected] (L.L.); [email protected] (X.Z.); [email protected] (C.T.), Hainan Institute of China University of Petroleum (Beijing), Sanya 572000, China
3 China Petroleum Pipeline Engineering Co., Ltd., Langfang 065000, China; [email protected] (Z.B.); [email protected] (J.L.)