The spatial mismatch between China’s energy resources and demand, alongside rapid clean energy growth, has caused significant wind, solar, and hydropower curtailment, necessitating power market reforms for resource optimization. The inter-provincial power spot market enables renewable energy integration and power balancing via a“unified market, two-level operation”system. Yet, static price caps struggle to balance supply-demand dynamics and supply-price stability goals, with limited analysis of bidding behaviors of power plants and electricity purchasers. Using 2022 trial data, a big data-driven approach examines bidding characteristics and clearing outcomes of thermal, hydro, wind, solar power, and counterpart provinces’purchasers, uncovering temporal and seasonal patterns. The KMeans algorithm classifies bidding behaviors of various units, identifying differences in duration, bid volume, and price to analyze influencing factors. Findings support market mechanism optimization, enhancing renewable energy integration and dual-carbon goals.