The widespread deployment of power grid ad hoc sensor networks based on IEEE 802.15.4 raises reliability challenges when nodes selfishly adapt CSMA/CA parameters to maximize individual performance. Such behavior degrades reliability, energy efficiency, and compliance with strict grid constraints. Existing analytical and simulation approaches often fail to rigorously evaluate configurations under asynchronous, event-driven, and resource-limited conditions. We develop a verification framework that integrates stochastic timed hybrid automata with statistical model checking (SMC) with confidence bounds to formally assess CSMA/CA parameterizations under grid workloads. By encoding node- and system-level objectives in temporal logic and automating protocol screening via large-scale statistical evaluation, the method certifies Nash equilibrium strategies that remain robust to unilateral deviations. In a substation-scale scenario, the certified equilibrium improves utility from 0.862 to 0.914 and raises the delivery ratio from 89.5% to 93.2% when compared with an aggressive tuning baseline. Against a delivery-oriented baseline, it reduces mean per-cycle energy from 152.8 mJ to 149.2 mJ while maintaining comparable delivery performance. Certified configurations satisfy latency, reliability, and energy constraints with robustness coefficients above 0.97 and utility above 0.91.

翻译：基于IEEE 802.15.4的电网自组织传感器网络的大规模部署面临可靠性挑战：当节点为最大化个体性能而自私地调整CSMA/CA参数时，将导致可靠性、能效下降，并违背严格的电网约束。现有分析与仿真方法在异步、事件驱动及资源受限条件下难以严格评估配置方案。我们提出一个集成随机时间混合自动机与带置信界统计模型检验（SMC）的验证框架，用于正式评估电网工作负载下的CSMA/CA参数化。通过将节点级与系统级目标编码为时序逻辑，并基于大规模统计评估自动化协议筛选，该方法可认证对单边偏离具有鲁棒性的纳什均衡策略。在变电站规模场景中，与激进的调优基线相比，经认证的均衡策略将效用从0.862提升至0.914，投递率从89.5%提高至93.2%。与面向投递率的基线相比，该策略在保持相近投递性能的同时，将平均周期能耗从152.8 mJ降至149.2 mJ。经认证的配置方案在鲁棒性系数高于0.97、效用高于0.91的条件下，满足延迟、可靠性与能量约束。