Packetized energy allocation and thermodynamic modeling for autonomous residential energy systems

PurposeThis article develops a physically grounded energy allocation architecture for autonomous, grid-independent residential systems based on discrete energy packets and thermodynamic constraints. It examines whether such a system can achieve stable and resilient energy allocation without reliance on continuous grid connectivity or market-based pricing.Design/methodology/approachA system-level modeling framework is proposed in which energy is represented as discrete, physically embodied packets governed by conservation laws, degradation dynamics and bounded storage. The architecture integrates autonomous home energy systems, a wireless coordination layer and artificial intelligence (AI)-based allocation. Mathematical models for energy flow, degradation and stress-feedback are formulated and system behavior is evaluated through simulation under varying conditions.FindingsSimulation results under stylized assumptions indicate bounded energy flows, preservation of baseline energy availability and automatic damping of consumption under stress. The model indicates bounded and stable behavior under the assumptions of the proposed framework without runaway accumulation or collapse with thermodynamic constraints providing effective regulation in place of centralized control or pricing.Research limitations/implicationsThe study is conceptual and does not include hardware implementation, behavioral modeling or empirical validation. Further research is required on deployment, feasibility, material constraints and user adaptation.Practical implicationsThe framework provides a basis for designing resilient, decentralized residential energy systems under constrained conditions.Social implicationsThe proposed energy allocation framework has implications for how energy access, responsibility and consumption behavior are structured at the household level. By linking energy availability directly to physical constraints, the system promotes transparency in resource use and may encourage conservation-oriented behavior.Originality/valueThe work integrates packetized energy, thermodynamic modeling and AI-based coordination into a unified allocation architecture.