Strategies of a Wind–Solar–Storage System in Jiangxi Province Using the LEAP–NEMO Framework for Achieving Carbon Peaking Goals

Yao Xiao, Caixia Yang, Tao Chen, Mingze Lei, Supannika Wattana and Buncha Wattana ()
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Yao Xiao: College of Electrical Engineering, Hunan Mechanical and Electrical Polytechnic, Changsha 410073, China
Caixia Yang: College of Electrical Engineering, Hunan Mechanical and Electrical Polytechnic, Changsha 410073, China
Tao Chen: College of Electrical Engineering, Hunan Mechanical and Electrical Polytechnic, Changsha 410073, China
Mingze Lei: Electrical and Computer Engineering Research Unit, Faculty of Engineering, Mahasarakham University, Maha Sarakham 44150, Thailand
Supannika Wattana: Electrical and Computer Engineering Research Unit, Faculty of Engineering, Mahasarakham University, Maha Sarakham 44150, Thailand
Buncha Wattana: Electrical and Computer Engineering Research Unit, Faculty of Engineering, Mahasarakham University, Maha Sarakham 44150, Thailand

Energies, 2025, vol. 18, issue 5, 1-19

Abstract: Jiangxi Province relies heavily on thermal power and energy imports but is rich in natural resources, particularly lithium. This study explores strategies for advancing wind–solar–storage systems to help Jiangxi transition to a low-carbon energy structure. Using LEAP and NEMO models, four scenarios are examined: the reference (REF) scenario, new energy storage policy scenario (NPS), high wind–solar power capacity scenario (HWSS), and comprehensive optimization scenario (COS). Key findings show that the COS and HWSS offer significant advantages over the REF scenario and NPS in terms of energy storage efficiency, carbon emission reduction, and cost savings. By 2035, under the COS, wind and solar power share rises to 48%, reducing coal use by 5.9 million tons and electricity imports by 40.0 TWh compared to the REF scenario. Battery storage utilization increases by 1499.8 GWh, nearly four times that of the REF scenario. This scenario also cuts CO 2 emissions by 16.8% and lowers cumulative social costs by 5.19 billion USD, delivering optimal economic efficiency. The study also identifies challenges such as high investment costs, underdeveloped business models, and low resource utilization, and recommends setting higher targets, implementing flexible solutions, promoting market reforms, and increasing R&D efforts, among other measures.

Keywords: renewable energy integration; energy structure; energy storage; CO 2 reduction; social costs (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: 2025
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