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arXiv 1507.04657eess.SYcs.SY
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智能电网中独立系统运营商操作理论:考虑随机可再生能源、需求响应与存储

A Theory for the Operation of the Independent System Operator in a Smart Grid with Stochastic Renewables, Demand Response and Storage

Texas A&M University(德克萨斯农工大学)

Rahul Singh, Ke Ma, Anupam Thatte, P. R. Kumar, Le Xie

AI总结:

本文提出了一种理论框架,用于设计在去中心化方式下生成最优需求响应的架构和算法,以应对包含多个随机可再生能源和动态负载的智能电网。该理论考虑了动态需求的最优响应,并通过模拟结果展示了其在社会福利方面的优势。

摘要:

本文针对设计在去中心化方式下生成最优需求响应的架构和算法这一关键问题进行了研究。通过最优需求响应,我们指代连接智能电网的智能体的效用最大化。去中心化指的是在该情况下,独立系统运营商(ISO)不需要知道智能体的动力学/效用,也不需要智能体了解连接电网的其他智能体的动力学/效用。ISO与智能体之间的通信仅限于ISO宣布定价政策,而智能体根据该定价政策回应其能源生成/消费报价。我们为确定性和随机性情况提供了完整的解决方案。该方案特征化了一种价格迭代方案,其结果导致社会福利的最优性。我们还为存在共同随机性影响并被所有智能体观察到的情况提供了最优解。该解可能计算复杂,我们提出了近似方法。对于更一般的部分观察随机性情况,我们展示了显著降低复杂度的放松方法。我们还提供了一种近似策略,以导致模型预测控制(MPC)方法。比较现有ISO所采用的架构与所得到的最优需求响应的模拟结果展示了我们方案在社会福利效用方面的优势。据作者所知,这是首次明确指出动态需求最优响应的此类工作。

英文摘要:

In this paper, we address a key issue of designing architectures and algorithms which generate optimal demand response in a decentralized manner for a smart-grid consisting of several stochastic renewables and dynamic loads. By optimal demand response, we refer to the demand response which maximizes the utility of the agents connected to the smart-grid. By decentralized we refer to the desirable case where neither the independent system operator (ISO) needs to know the dynamics/utilities of the agents, nor do the agents need to have a knowledge of the dynamics/utilities of other agents connected to the grid. The communication between the ISO and agents is restricted to the ISO announcing a pricing policy and the agents responding with their energy generation/consumption bids in response to the pricing policy. We provide a complete solution for both the deterministic and stochastic cases. It features a price iteration scheme that results in optimality of social welfare. We also provide an optimal solution for the case where there is a common randomness affecting and observed by all agents. This solution can be computationally complex, and we pose approximations. For the more general partially observed randomness case, we exhibit a relaxation that significantly reduces complexity. We also provide an approximation strategy that leads to a model predictive control (MPC) approach. Simulation results comparing the resulting optimal demand response with the existing architectures employed by the ISO illustrate the benefit in social welfare utility realized by our scheme. To the best of the authors' knowledge, this is the first work of its kind to explicitly mark out the optimal response of dynamic demand.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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