Capacity Demand Analysis of Rural Biogas Power Generation System with Independent Operation Considering Source-Load Uncertainty

Miao Zhou, Jun Liu, Aihong Tang and Xinyu You ()
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Miao Zhou: State Grid Hubei Electric Power Co, Ltd., Electric Power Research Institute, Wuhan 430077, China
Jun Liu: State Grid Hubei Electric Power Co, Ltd., Electric Power Research Institute, Wuhan 430077, China
Aihong Tang: School of Automation, Wuhan University of Technology, Wuhan 430062, China
Xinyu You: School of Automation, Wuhan University of Technology, Wuhan 430062, China

Energies, 2024, vol. 17, issue 8, 1-15

Abstract: With the greatly increased penetration rate of wind power, photovoltaic, and other new energy sources in the power system, the proportion of controllable units gradually decreased, resulting in increased system uncertainty. The biogas power generation system can effectively alleviate the pressure caused by source-load uncertainty in such high-permeability systems of new energy sources such as wind power and photovoltaic. Hence, from the perspective of the power system, this paper introduces a capacity demand analysis method for a rural biogas power generation system capable of independent operation amidst source-load uncertainty. To enhance the depiction of pure load demand uncertainty, a scene set generation method is proposed, leveraging quantile regression analysis and Gaussian mixture model clustering. Each scene’s data and probability of occurrence elucidate the uncertainty of pure load demand. An integrated optimal operation model for new energy and biogas-generating units, free from energy storage capacity constraints, is established based on the generated scenario set. Addressing considerations such as biogas utilization rate and system operation cost, a biogas storage correction model, utilizing the gas storage deviation degree index and the cost growth rate index, is developed to determine biogas demand and capacity. The example results demonstrate the significant reduction in gas storage construction costs and charging and discharging imbalances achieved by the proposed model while ensuring systemic operational cost effectiveness.

Keywords: high permeability; biogas power generation; capacity demand analysis; scenario set; rural power grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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