客户不确定性下灵活可靠的需求响应
Harnessing Flexible and Reliable Demand Response Under Customer Uncertainties
摘要：
需求响应（DR）是一种具有成本效益和环境友好的方法，通过利用客户需求的灵活性来减轻可再生能源整合中的不确定性。然而，现有的DR计划遭受低参与由于严格的承诺要求或不可靠的自愿计划。此外，能量存储/储备的容量规划传统上与需求响应程序设计分开进行，这导致效率低下。此外，客户往往面临着很高的不确定性，他们的成本在提供需求响应，这是没有很好的研究文献。本文首先通过一个随机最优化问题对联合容量规划和需求响应程序设计问题进行建模，该问题综合考虑了可再生能源发电、客户电力需求以及客户提供DR的成本等不确定性因素。一个分布式的算法，然后开发实现控制策略，而没有效率损失。我们还通过在承诺水平上允许灵活性，提供更好的政策设计。我们进行基于真实世界轨迹的数值模拟。结果表明，所提出的算法可以实现接近最优的社会成本，并显着的社会成本节省相比，基线方法。
英文摘要：
Demand response (DR) is a cost-effective and environmentally friendly approach for mitigating the uncertainties in renewable energy integration by taking advantage of the flexibility of customers' demands. However, existing DR programs suffer from either low participation due to strict commitment requirements or not being reliable in voluntary programs. In addition, the capacity planning for energy storage/reserves is traditionally done separately from the demand response program design, which incurs inefficiencies. Moreover, customers often face high uncertainties in their costs in providing demand response, which is not well studied in literature. This paper first models the problem of joint capacity planning and demand response program design by a stochastic optimization problem, which incorporates the uncertainties from renewable energy generation, customer power demands, as well as the customers' costs in providing DR. We propose online DR control policies based on the optimal structures of the offline solution. A distributed algorithm is then developed for implementing the control policies without efficiency loss. We further offer enhanced policy design by allowing flexibilities into the commitment level. We perform real world trace based numerical simulations. Results demonstrate that the proposed algorithms can achieve near optimal social costs, and significant social cost savings compared to baseline methods.
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