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Verifying computations such as load profiling, billing validation, and forecasting in smart grids poses an ongoing challenge, whether these tasks are handled internally by utilities or outsourced to external entities. Inaccurate or falsified computations can lead to financial losses, energy inefficiencies, and operational disruptions. This research develops two independent frameworks for achieving reliable and efficient verification of outsourced computations in smart-grid environments. The first framework, Dynamic Slicing, introduces a decentralized verification mechanism that divides large computations into smaller, verifiable slices distributed across multiple servers. By verifying only selected slices rather than complete computations, the client efficiently detects malicious behavior while significantly reducing verification overhead. The second framework, Budget-Aware Verification, extends this line of work by incorporating explicit resource constraints. It models verification as an optimization problem under a fixed client budget, determining how many servers and slices to verify in each round so that verification remains feasible within available resources. This framework adapts the verification process to real-world cost limitations faced by utility clients. Together, these methods improve both performance and cost efficiency-dynamic slicing enhances computational speed, while budget-aware verification optimizes resource usage offering a scalable solution for secure computation in smart grids.