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arXiv · 1705.04577

Incentivizing Reliable Demand Response with Customers' Uncertainties and Capacity Planning

Joshua Comden·Zhenhua Liu·Yue Zhao
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Abstract

One of the major issues with the integration of renewable energy sources into the power grid is the increased uncertainty and variability that they bring. If this uncertainty is not sufficiently addressed, it will limit the further penetration of renewables into the grid and even result in blackouts. Compared to energy storage, Demand Response (DR) has advantages to provide reserves to the load serving entities (LSEs) in a cost-effective and environmentally friendly way. DR programs work by changing customers' loads when the power grid experiences a contingency such as a mismatch between supply and demand. Uncertainties from both the customer-side and LSE-side make designing algorithms for DR a major challenge. This paper makes the following main contributions: (i) We propose DR control policies based on the optimal structures of the offline solution. (ii) A distributed algorithm is developed for implementing the control policies without efficiency loss. (iii) We further offer an enhanced policy design by allowing flexibilities into the commitment level. (iv) We perform real world trace based numerical simulations which demonstrate that the proposed algorithms can achieve near optimal social cost. Details can be found in our extended version.

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Joshua Comden, Zhenhua Liu, Yue Zhao. 2017-05-11. Incentivizing Reliable Demand Response with Customers' Uncertainties and Capacity Planning. https://doi.org/10.1145/3078505.3078546

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