Constrained Thompson Sampling for Real-Time Electricity Pricing With Grid Reliability Constraints
Constrained Thompson Sampling for Real-Time Electricity Pricing With Grid Reliability Constraints
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DOI：
10.1109/tsg.2020.3004770
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发表时间：
2019-08
影响因子：
9.6
通讯作者：
Nathaniel Tucker;Ahmadreza Moradipari;M. Alizadeh
中科院分区：
文献类型：
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作者：
Nathaniel Tucker;Ahmadreza Moradipari;M. Alizadeh
我们考虑了电力聚合器在通过实时广播调度信号来实施负荷整形计划时试图学习客户的用电模型的问题。我们采用多臂强盗问题来描述客户对调度信号响应的随机性和未知性。我们提出了一种带约束的Thompson抽样启发式算法CON-TS-RTP，用于解决电力聚合器试图影响用户使用以匹配各种期望的需求分布(即，减少高峰时段的需求、整合更多间歇性可再生发电、跟踪期望的日负荷分布等)的负荷成形问题。建议的CON-TS-RTP启发式算法考虑了日变化的目标负荷分布(即反映可再生预测和期望需求模式的多个目标负荷分布)，并考虑了配电系统的运行约束，以确保用户获得足够的服务并避免潜在的电网故障。我们讨论了我们的算法的遗憾界限，并讨论了整个学习过程中维护的分配系统约束的操作可靠性。
We consider the problem of an electricity aggregator attempting to learn customers’ electricity usage models while implementing a load shaping program by means of broadcasting dispatch signals in real-time. We adopt a multi-armed bandit problem formulation to account for the stochastic and unknown nature of customers’ responses to dispatch signals. We propose a constrained Thompson sampling heuristic, Con-TS-RTP, as a solution to the load shaping problem of the electricity aggregator attempting to influence customers’ usage to match various desired demand profiles (i.e., to reduce demand at peak hours, integrate more intermittent renewable generation, track a desired daily load profile, etc). The proposed Con-TS-RTP heuristic accounts for day-varying target load profiles (i.e., multiple target load profiles reflecting renewable forecasts and desired demand patterns) and takes into account the operational constraints of a distribution system to ensure that customers receive adequate service and to avoid potential grid failures. We provide a discussion on the regret bounds for our algorithm as well as a discussion on the operational reliability of the distribution system’s constraints being upheld throughout the learning process.