Encouraging load-side resource aggregation entities

such as industrial parks

to participate in ancillary services markets can effectively alleviate the contradiction between the growth of wind power installed capacity and the gap in flexible resource allocation in China. Existing compensation methods

however

predominantly adopt unilateral pricing based solely on total electricity served

neglecting demand fluctuations and dispatch costs. This leads to unfair compensation outcomes and low market trading enthusiasm. To address this issue

this paper proposes a dynamic pricing strategy for ancillary services incorporating the comprehensive scheduling costs of industrial parks. First

a load aggregation response model and a dynamic revenue function incorporating dual-rule net income and dispatch costs are developed. Then

a two-layer optimization model for peak regulation and reserve services is established. The upper layer maximizes alliance revenue by solving the park’s optimal scheduling plan and associated costs

while the lower layer combines the revenue function with a Shapley value allocation model to propose a transaction balance index and derive a fair compensation price. Case studies on an electric magnesium industrial park validates the method. Results demonstrate that the approach significantly enhances trading revenue

fairness

and flexibility compared to conventional mechanisms.