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.