The Renewable Electricity Planning and Operation Model (REPO)
The Renewable Electricity Planning and Operation (REPO) Model is a capacity expansion and dispatch model that includes provincial details for China. The REPO model extends the open-source Balmorel model and features important technology and policy characteristics in China. The REPO model covers 32 areas that represent China’s administrative provinces. The electricity demand, resource potential, existing power installation, and existing transmission capacity are all represented at the provincial level. The model has covered various conventional and renewable power generation technologies, CCS technologies, and storage technologies. The model depicts the resource potentials and curves for wind and solar power. The technological improvements of renewables are also considered in the model. The model applies an objective function to minimize the discounted total cost of the power system, providing the optimal capacity and power generation of each technology, transmission capacity between provinces, and carbon emissions.
China Transportation Energy and GHG emissions Model (CTEGM)
CTEGM is a comprehensive evaluation model of China's transportation energy technology pathways and policies. CTEGM is composed of input module, transportation service demand analysis module, high-speed rail to civil aviation passenger substitution effect analysis module, traffic structure and management analysis module, civil aviation transportation low-carbon development module, vehicle ownership analysis module and output module, which can be coupled to Energy Technology Life Cycle Analysis Model (TLCAM). The model framework can realize the integrated analysis of transportation energy supply and transportation service demand, the comprehensive life cycle evaluation of more than 100 vehicle fuel-powertrain technology pathways, and the overall evaluation of transportation technology pathways and policies.
Energy Technology Life Cycle Analysis Model (TLCAM)
TLCAM can calculate the full life cycle energy consumption and GHG emission intensity list of the major end-use energy sources, and then calculate the full life cycle energy consumption and GHG emission intensity of the transportation fuel cycle and the vehicle cycle. The analysis module on transportation technology focuses on more than 100 combined technical pathways of transportation fuels/transport powertrain, enabling energy consumption and carbon emission analysis covering vehicles and transportation fuels.
China Multi-gas Optimal Reduction Evaluation model (China-MORE)
China-More is a bottom-up mid-and long-term multi-sector multi-greenhouse gas emission reduction evaluation model based on the energy system optimization VEDA-TIMES model platform. The China-MORE model adopts the principle of system analysis, takes the energy system optimization module as the core, and combines modules such as energy service demand, multiple greenhouse gas emissions, primary pollutant emissions, power technology diffusion, emission space allocation, and uncertainty analysis.
The core modules of the model are the energy system optimization module and the emission module. The energy system optimization module identifies the least-cost way to meet energy-service demands through minimization of the total discounted system cost over the entire modeling time horizon. At the same time, the pollutant emission module and the GHGs emission module calculate the emissions for different scenarios. On this basis, the model can be used to analyze the long-term optimized decarbonization pathway of China through either a policy-driven or goal-driven approach.
The China-MORE model simulates all greenhouse gases emission of CO2, CH4, N2O, and F-gas, which provides an important research tool to formulate mid-and long-term low-emission development strategies of China. It's a powerful tool to analyze the gap between current emission reduction efforts and China's carbon neutrality goal because of its strength in the exploration of ways to use multiple greenhouse gas joint emission reduction strategies to achieve carbon neutrality goals at a lower system cost.
Publications：
Su X, Ghersi F, Teng F, et al. The economic impact of a deep decarbonisation pathway for China: a hybrid model analysis through bottom-up and top-down linking[J]. Mitigation and Adaptation Strategies for Global Change, 2022, 27(1): 1-37.
Teng F, Su X, Wang X. Can China peak its non-CO2 GHG emissions before 2030 by implementing its nationally determined contribution?[J]. Environmental science & technology, 2019, 53(21): 12168-12176.
Yang, X.; Teng, F.; Xi, X. Q.; Khayrullin, E.; Zhang, Q. Cost-benefit analysis of China’s Intended Nationally Determined Contributions based on carbon marginal cost curves. Appl. Energy 2018, 227, 415– 425, DOI: 10.1016/j.apenergy.2017.08.016
Yang, X.; Teng, F.; Wang, X.; Zhang, Q. System optimization and co-benefit analysis of China’s deep de-carbonization effort towards its INDC target. Energy Procedia 2017, 105, 3314– 3319, DOI: 10.1016/j.egypro.2017.03.754
Yang, X.; Teng, F. The air quality co-benefit of coal control strategy in China. Resources Conservation and Recycling 2018, 129, 373– 382, DOI: 10.1016/j.resconrec.2016.08.011
Yang, X.; Teng, F. Air quality benefit of China’s mitigation target to peak its emission by 2030. Climate Policy 2018, 18 (1), 99– 110, DOI: 10.1080/14693062.2016.1244762
Wang, X.; Teng, F.; Yang, X.; Wei, R. Q. Assessing the role of electricity storage in China’s high renewable energy penetration future. Energy Procedia 2017, 105, 4084– 4089, DOI: 10.1016/j.egypro.2017.03.865