Liu Lili, Feng Tiantian, Kong Jiajie, Cui Mingli
School of Economics and Management, China University of Geosciences Beijing, Beijing, 100083, China.
School of Economics and Management, China University of Geosciences Beijing, Beijing, 100083, China; Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing, 100083, China.
J Environ Manage. 2025 Feb;374:123853. doi: 10.1016/j.jenvman.2024.123853. Epub 2025 Jan 13.
Achieving the national climate target would depend on national actions. China has implemented important market mechanisms for a green and low-carbon energy transition, including the Renewable Portfolio Standard (RPS), the Tradable Green Certificate (TGC) market, the green power trading market, and so on. However, how to effectively integrate coupled TGC and green power trading to achieve a balance between maximizing economic benefits and environmental friendliness remains to be explored. Therefore, this study extends prior research by establishing a bi-level decision optimization model to explore market participants' decision making from the perspective of energy supply and economic value, and analyzes the impact of the RPS, TGC price, and the penetration of renewable energy (RE) in the electricity market, the green power market, and the trading strategy of market participants in a multi-market equilibrium state. The feasibility and effectiveness of the bi-level decision optimization model and algorithm are verified using the example of IEEE14 node and historical data of Elia Energy. The results show that: (1) Under the market equilibrium condition, the clearing price in the day-ahead RE market is equal to the clearing price in the day-ahead traditional energy market plus the TGC price. (2) When green power participates in the spot market, there is a complementary relationship between RE generation and traditional energy generation. (3) A shift from decreasing to increasing costs for electricity consumers when RE penetration is above a certain threshold (α>30%) and the TGC price is 100 CNY/MWh, and a decrease in the growth rate of RE generators' profits when RE penetration is above a certain threshold (α>35%). (4) Traditional energy generators with small installed capacities adopt riskier market behaviors to declare more electricity and try to obtain higher profit in market transactions. These insights can make up for the research gap of decision optimization in multi-timescale electricity market, achieve energy optimization allocation and environmental sustainability.
实现国家气候目标将取决于国家行动。中国已实施了重要的市场机制以推动绿色低碳能源转型，包括可再生能源配额制度（RPS）、绿色电力证书（TGC）交易市场、绿色电力交易市场等。然而，如何有效整合耦合的TGC与绿色电力交易，以实现经济效益最大化与环境友好之间的平衡仍有待探索。因此，本研究通过建立双层决策优化模型扩展了先前的研究，从能源供应和经济价值的角度探索市场参与者的决策，并分析RPS、TGC价格以及可再生能源（RE）在电力市场、绿色电力市场中的渗透率和市场参与者在多市场均衡状态下的交易策略的影响。利用IEEE14节点的例子和埃利亚能源的历史数据验证了双层决策优化模型和算法的可行性和有效性。结果表明：（1）在市场均衡条件下，日前RE市场的清算价格等于日前传统能源市场的清算价格加上TGC价格。（2）当绿色电力参与现货市场时，RE发电与传统能源发电之间存在互补关系。（3）当RE渗透率高于一定阈值（α>30%）且TGC价格为100元/兆瓦时，电力消费者的成本从下降转为上升，且当RE渗透率高于一定阈值（α>35%）时，RE发电商利润的增长率下降。（4）装机容量小的传统能源发电商采取风险更高的市场行为申报更多电量，试图在市场交易中获取更高利润。这些见解可以弥补多时间尺度电力市场决策优化的研究空白，实现能源优化配置和环境可持续性。
