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Publishing Language: Chinese | Open Access

Simulation experimental study on operation evaluation of rural distribution network with high proportion of solar and biogas renewable energy

Xue XUE1( )Jinming ZHANG1Haijun FU2Rui LIANG1
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
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Abstract

Objective

Under the background of national energy development transformation, universities shoulder the important mission of cultivating novel engineering talents for new power systems. To train electrical engineering professionals and keep pace with industry frontiers, and in consideration of the characteristics of rural distribution networks (DNs), a comprehensive and innovative experimental project is designed to evaluate the operational performance of rural DNs with a high penetration of distributed renewable energy.

Methods

Focused on photovoltaic (PV)–biogas coordinated operation in rural DNs, an optimal dispatch model is established for an IEEE-33-node DN incorporating high-penetration distributed PV generators and biogas power sources. The model adopts the minimization of comprehensive costs, including operation and maintenance expenses, electricity purchase and sale costs, and voltage penalty costs, as the objective function while applying multi-dimensional constraints, including network constraints based on distflow power flow, radial topology operation constraints, and voltage and current safety constraints, to achieve unified scheduling of controllable equipment, such as PV and biogas generation. A multi-dimensional performance evaluation system that covers safety, economy, and environmental benefits for DNs is developed: safety is ensured through voltage monitoring and analysis to maintain grid stability; economy is optimized by establishing a multi-dimensional cost control model, with economic benefits enhanced through PV–biogas coordinated scheduling; environmental benefits are precisely assessed using a quantified carbon emission (CE) factor strategy by comparing CEs from biogas generation, PV generation, and external electricity procurement.

Results

Simulation results demonstrate that optimized biogas generation is flexibly adjusted according to PV output to achieve peak shaving and valley filling within a day, increasing the local consumption rate of new energy to ≥96%. System voltage stability is substantially enhanced, with optimized voltage magnitudes at all nodes and no risk of exceeding limits. Network loss costs decrease from 4,703.08 to 1,966.68 yuan, indicating notable economic improvement. Daily CE reductions reach 167.09 tons, delivering notable environmental benefits.

Conclusions

A new model of high-proportion PV and biogas complementary integration into DNs is explored, providing a technically feasible and environmentally beneficial solution for constructing next-generation rural power systems. The effectiveness of the proposed model in terms of improving grid resilience, economic efficiency, and low-carbon performance is verified. As an innovative experiment project for undergraduate electrical engineering students, this study achieves remarkable outcomes in cultivating students’ innovative thinking, self-directed learning ability, practical skills, teamwork, and research methodology through their full participation in the complete research process from literature review and design to modeling and simulation. This study also enhances students’ ability to analyze and solve practical electrical engineering problems, delivering strong talent support for achieving the dual-carbon goals.

CLC number: TM732; TK01+9 Document code: A Article ID: 1002-4956(2026)03-0185-08

References

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Experimental Technology and Management
Pages 185-192

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Cite this article:
XUE X, ZHANG J, FU H, et al. Simulation experimental study on operation evaluation of rural distribution network with high proportion of solar and biogas renewable energy. Experimental Technology and Management, 2026, 43(3): 185-192. https://doi.org/10.16791/j.cnki.sjg.2026.03.024

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Received: 29 August 2025
Published: 20 March 2026
© 2026 Experimental Technology and Management. All rights reserved.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).