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The growing share of renewable energy has an increasingly significant impact on the electricity market. Locational marginal price (LMP), as a sensitive price signal, has a potential but considerable correlation with renewable energy generation. In this context, this paper focuses on the joint fluctuation laws between LMP and renewables consumed to generate electricity. At first, LMP and renewables consumption data from Independent System Operator New England (ISO‐NE) are collected and preprocessed. Then, through highly comparative time‐series analysis (hctsa), it is found that discrete symbolization features have effective description ability. Therefore, a coarse‐grained method is conducted to convert the real matrix data into a symbol vector based on numerical distribution analysis. Next, joint fluctuation complex networks are constructed according to the symbol vector. From a global perspective, the joint fluctuation network follows an exponential distribution and exhibits hierarchical modularity. From a local perspective, the joint fluctuation network follows a power‐law distribution. The research results of this paper provide a new perspective to understand the evolution of the electricity market with large‐scale renewable energy and have reference value for identifying the valuable joint fluctuation patterns and improving the LMP forecast results. [ABSTRACT FROM AUTHOR]