With rapid development of smart grids, how to efficiently aggregate and verify multi-source electricity consumption data while ensuring user privacy has become a key research problem, and a number of privacy-preserving data aggregation schemes have been introduced to alleviate this problem. However, most existing schemes only support simple additive homomorphic aggregation, lacking support for more complex functions. To address this challenge, this paper proposes an efficient and verifiable privacy-preserving data aggregation scheme that integrates functional encryption, Diffie–Hellman key exchange, and Schnorr signature to support linear function queries, resists collusion attacks, and ensures verifiability of aggregation results. Experimental results demonstrate that our proposed scheme achieves higher computational and communication efficiency compared with the existing schemes, e.g., GuardGrid, while maintaining strong security and functional expressiveness. Therefore, it provides a feasible and effective approach for building efficient, scalable, and verifiable privacy-preserving systems in smart grids.