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Parallel Statistical Model Checking for Safety Verification in Smart Grids

机译:智能电网安全验证的并行统计模型检查

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By using small computing devices deployed at user premises, Autonomous Demand Response (ADR) adapts users electricity consumption to given time-dependent electricity tariffs. This allows end-users to save on their electricity bill and Distribution System Operators to optimise (through suitable time-dependent tariffs) management of the electric grid by avoiding demand peaks. Unfortunately, even with ADR, users power consumption may deviate from the expected (minimum cost) one, e.g., because ADR devices fail to correctly forecast energy needs at user premises. As a result, the aggregated power demand may present undesirable peaks. In this paper we address such a problem by presenting methods and a software tool (APD-Analyser) implementing them, enabling Distribution System Operators to effectively verify that a given time-dependent electricity tariff achieves the desired goals even when end-users deviate from their expected behaviour. We show feasibility of the proposed approach through a realistic scenario from a medium voltage Danish distribution network.
机译:通过使用部署在用户房屋中的小型计算设备,自治需求响应(ADR)可以使用户的电力消耗适应给定的时间依赖性电价。这使最终用户可以节省电费,而配电系统运营商可以通过避免需求高峰来优化(通过适当的与时间有关的电价)电网管理。不幸的是,即使使用ADR,用户的功耗也可能偏离预期的(最低成本),例如,因为ADR设备无法正确预测用户场所的能源需求。结果,合计的功率需求可能呈现不期望的峰值。在本文中,我们通过介绍方法和实现这些方法的软件工具(APD-Analyser)来解决此类问题,使配电系统运营商能够有效验证给定的与​​时间有关的电费,即使最终用户偏离了他们自己的目标,也能达到预期的目标预期的行为。我们通过来自中压丹麦配电网的实际场景展示了该方法的可行性。

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