Analysis of different segmented quantity strategy variations among affiliation-differentiated power retail companies in medium- and long-term electricity transactions

Purpose As China’s power market gradually shifts toward market-based electricity sales transactions, a growing number of diverse electricity suppliers are emerging. The escalating market competition compels power retail companies with different affiliations to actively seek trading strategies that maximize their resource advantages. Design/methodology/approach This study aims to constructs a power trading model for three types of power retail companies (PRCs) (power generation-affiliated power retail companies (PGAPRCs), grid-affiliated power retail companies (GAPRCs) and independent power retail companies (IPRCs)) with different affiliations in monthly centralized bidding in medium- and long-term electricity transactions. With the goal of maximizing social welfare, the study uses game theory to optimize and analyze the profitability models of these three types of PRCs. Findings When a single electricity retailer exists, the profit variation range for the three classes of qualified retailers diminishes with an increasing number of segments, yet the magnitude of these changes becomes more stable. As the three classes of qualified retailers select different numbers of segments, the profit variation range for retailers of each qualification experiences differing degrees of change across various segment ratios, demonstrating differential sensitivity to fluctuations in the awarded quantity, and can maximize their profits by choosing an optimal segment ratio. In addition, the volatility of the market clearing price diminishes progressively as the number of segments rises. Originality/value Based on the established affiliation-based classification of PRCs and to the best of the authors’ knowledge, this study is the first to construct a unified trading model for PGAPRCs, GAPRCs and IPRCs. Its originality lies in introducing game theory to analyze their differentiated profit models under varying bid segment strategies within monthly centralized bidding. The value is providing quantitative evidence that increasing bid segments reduces market price volatility and revealing how different companies can optimize profits by selecting specific segmentation ratios, offering concrete decision-making support for both market participants and regulators.