[Objective] In recent years, the installed capacity of renewable energy in China has rapidly increased, leading to an increasingly prominent contradiction between the reverse distribution of power supply and load. To alleviate generation-side scheduling pressure, large power consumers are regarded as key flexible resources on the load side and are utilized to maintain power supply-demand balance. The current electricity market model is evolving from "two-round declaration with coordinated clearing" approach to a "coupled declaration with unified clearing" mechanism. Under this new model, large consumers are directly exposed to cascading risks caused by the uncertainty of cross-provincial renewable energy output, making traditional risk assessment methods inadequate. To address this, this paper proposes treating renewable energy output uncertainty as a single risk source and constructing a dual-dimension risk assessment model based on credit and price, to support risk management decisions of large power consumers in unified-clearing cross-provincial transactions. [Methods] Firstly, quantitatively characterizing credit risks such as power shortages, premium pricing, and curtailment caused by physical deviations using the variance method, while measuring price risks including extreme, opportunity, and volatility risks arising from market electricity price fluctuations using conditional value-at-risk (CVaR). Secondly, the entropy weight method is employed to objectively weight the aforementioned multi-dimensional risk indicators, quantifying them as risk costs and integrating them into inter-provincial-intra-provincial unified clearing to establish an optimized clearing model that accounts for consumer risk preferences. Finally, typical scenarios of inter-provincial spot trading are simulated to validate the effectiveness of the proposed risk assessment model. [Results] Compared with the generic risk indicators, the proposed method reduces electricity procurement costs for large consumers by 1.4%-2.5% under renewable penetration levels of 10%-55%. The low-price opportunity loss is effectively avoided. [Conclusions]The proposed risk evaluation indicators can effectively and accurately quantify renewable-energy-induced credit and price risks faced by large consumers in inter-provincial spot trading, thereby providing a quantitative basis for differentiated risk warning and power purchase decision-making.