Net-zero stochastic planning for pig farm-dominated rural energy systems considering agricultural demand response

Kang, Shuang, Gan, Wei, Zhou, Yue ORCID: https://orcid.org/0000-0002-6698-4714 and Ai, Ping 2026. Net-zero stochastic planning for pig farm-dominated rural energy systems considering agricultural demand response. Energy Conversion and Management 349 , 120759. 10.1016/j.enconman.2025.120759

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Abstract

Given the significant renewable energy potential of rural areas, rural energy systems are emerging as an effective solution to meet local energy demand and achieve net-zero emissions targets. This study proposes a net-zero stochastic planning model for pig farm-dominated rural energy systems, integrating biogas engines, photovoltaic panels, and batteries to economically satisfy local energy demand. First, a comprehensive modelling framework is developed to capture the unique resource availability and energy demand characteristics of pig farms. This includes supplementary lighting requirements for pig growth, biomass availability as well as flexible heating and cooling loads necessary for maintaining optimal farm conditions. Then, a novel operation strategy is introduced, incorporating the flexibility of agricultural demand. It coordinates the demand response mechanism, the battery charging and discharging strategy based on time-of-use electricity prices, and the maximising self-consumption strategy. The demand response mechanism enables price-responsive control of heating and cooling loads by utilising the thermal inertia of pig farms within acceptable temperature limits. Moreover, the net-zero carbon emissions goal for pig farm-dominated rural energy systems is realised using a scenario-based stochastic optimisation method. The approach is demonstrated through a case study of a rural village with a pig farm in Hubei Province, China, illustrating how it can support long-term planning and provide practical guidance for low-carbon rural energy system design. Comparative analyses indicate that the proposed planning model offers both economic and environmental benefits, making it a promising strategy for sustainable rural energy development.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Publisher:	Elsevier
ISSN:	0196-8904
Date of First Compliant Deposit:	15 December 2025
Date of Acceptance:	9 November 2025
Last Modified:	15 Dec 2025 10:15
URI:	https://orca.cardiff.ac.uk/id/eprint/183211

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