Study on the Economic and Technical Optimization of Hybrid Rural Microgrids Integrating Wind, Solar, Biogas, and Energy Storage with AC/DC Conversion

Hu Tan; Xiaoliang Wang; Tingting Xu; Ke Zhao; Lianchao Su; Wenyu Zhang; Zheng Xin

doi:10.4108/ew.5803

Authors

Hu Tan State Grid Shandong Electric Power Company
Xiaoliang Wang State Grid Shandong Electric Power Company
Tingting Xu State Grid Shandong Electric Power Company
Ke Zhao State Grid Shandong Electric Power Company
Lianchao Su State Grid Shandong Electric Power Company
Wenyu Zhang State Grid Shandong Electric Power Company
Zheng Xin Shandong Jianzhu University

DOI:

https://doi.org/10.4108/ew.5803

Keywords:

Electricity Market, Multi-Energy Complementary System, Rural Microgrid, Integration of Generation, Grid, Load and Storage, Economic and Technical Analysis

Abstract

Under the guidance of the 'dual carbon' goals and 'rural revitalization' strategy, the development of microgrids primarily based on wind, solar, and biogas energy is rapidly advancing in rural areas. A critical and challenging area of current research is how to optimally configure the capacity of these microgrids of varying sizes, taking into account the availability of resources in the system's environment and specific climatic conditions, to maximize economic benefits. Based on this, the article constructs a model of a hybrid AC/DC microgrid system powered by wind, solar, and biogas energy. It undertakes multi-objective optimization to achieve the highest utilization of renewable energy, the most economical cost, and the minimum carbon emissions while ensuring the reliability of the system's power supply. The study explores the economically and technically optimal configuration of this microgrid energy system under certain climatic conditions. The results indicate that the optimal configuration for a rural microgrid powered by wind, solar, and biogas energy should include a 2.6 kW biogas generator, 30.00 kW solar panels, 5.24 kW wind turbines, a 2.6 kW battery storage system, and a 10.00 kW bidirectional inverter. This configuration results in the lowest total net cost of the system, achieving optimal outcomes in terms of total net cost, cost per kilowatt-hour, and supply reliability.

Downloads

Download data is not yet available.

References

ZHAO, C., WANG, B., et al. (2022). OPTIMAL CONFIGURATION OPTIMIZATION OF ISLANDED MICROGRID USING IMPROVED GREY WOLF OPTIMIZER ALGORITHM. Acta Energiae Solaris Sinica. 43(01), 256-262.

TAN, Y., LV, Z. L, LI, J. (2016). Multi-objective optimal sizing method for distributed power of wind-solar-diesel-battery independent microgrid based on improved electromagnetism-like mechanism. Pwer System Protection and Control. 44(08), 63-70.

WANG, X. Y., TANG, Z., PU, R. Q. (2019). Optimal Configuration for Stand-alone Microgrid Capacity Based on Improved Operation Control Strategy. Water Resources and Power. 37(04), 192-196.

YU, K. X., LI, F. X., LI, S. S. (2021). Simulation of Multi-Objective Capacity Optimization Configuration of Isolated Microgrid Based on Improved BASDE Algorithm. Power System and Clean Energy. 37(08), 109-117.

Sharma, K. K., Gupta, A., Kumar, R., Chohan, J. S., Sharma, S., Singh, J., & Dwivedi, S. P. (2021). Economic evaluation of a hybrid renewable energy system (HRES) using hybrid optimization model for electric renewable (HOMER) software—a case study of rural India. International Journal of Low-Carbon Technologies, 16(3), 814-821. DOI: https://doi.org/10.1093/ijlct/ctab012

Ma, L., Gao, S., Li, M., Pei, Y., & Cheng, S. (2023). Evolutionary multi-objective optimization algorithms in microgrid power dispatching. Frontiers in Energy Research, 10, 1053325. DOI: https://doi.org/10.3389/fenrg.2022.1053325

CHENG R, Feng LI, CHANG Y.(2019). Power capacity optimization design of standalone microgrid. Distributed Energy Resources,4(3), 8-15.

YANG, Q., YUAN, Y., et al. Optimal capacity configuration of standalone hydro-photovoltaic-storage microgrid. Electric Power Automation Equipment. 35(10), 37-44.

Ali, S. A., Mohd R. A., et al.(2020). Feasibility analysis of grid-connected and islanded operation of a solar PV microgrid system: A case study of Iraq. Energy, 191(C). DOI: https://doi.org/10.1016/j.energy.2019.116591

CHENG, R., CHANG, Y., HUANG, H., et al. (2017). Multi-objective Based Optimal Capacity Design of Isolated Microgrid. Distributed Energy Resources, 35(10), 198-202.

NI, W. B., KANG, K., et al. Optimization of Capacity Configuration for Island Microgrids. Telecom Power Technology. 37(12), 16-18.

Xu, Y., Wu, L., Walker, S. L., Lian, J., Verma, A., & Zhang, R. (2021). Guest editorial: Multi‐energy microgrid: Modelling, operation, planning, and energy trading. Energy Conversion and Economics, 2(3), 119-121. DOI: https://doi.org/10.1049/enc2.12042

Mekonnen, T., Bhandari, R., & Ramayya, V. (2021). Modeling, analysis and optimization of grid-integrated and islanded solar PV systems for the Ethiopian residential sector: Considering an emerging utility tariff plan for 2021 and beyond. Energies, 14(11), 3360. DOI: https://doi.org/10.3390/en14113360

Qingcheng, Y. A. O., & Xiaoling, Y. U. A. N. (2020). Optimal configuration of independent microgrid based on Monte Carlo processing of source and load uncertainty. Energy Storage Science and Technology, 9(1), 186.

Li, X., Gao, J., You, S., Zheng, Y., Zhang, Y., Du, Q., & Qin, Y. (2022). Optimal design and techno-economic analysis of renewable-based multi-carrier energy systems for industries: A case study of a food factory in China. Energy, 244, 123174. DOI: https://doi.org/10.1016/j.energy.2022.123174

Yang, L., Hu, Z., Xie, S., Kong, S., & Lin, W. (2019). Adjustable virtual inertia control of supercapacitors in PV-based AC microgrid cluster. Electric Power Systems Research, 173, 71-85. DOI: https://doi.org/10.1016/j.epsr.2019.04.011