Reserves from Controllable Swimming Pool Pumps: Reliability Assessment and Operational Planning

Modarresi, Mohammad Sadegh
Xie, Le
Singh, Chanan
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This paper introduces a conceptual framework, a capacity assessment method, and a data-driven optimization algorithm to aggregate flexible loads such as in-ground swimming pool pumps for reliable provision of spinning reserves. Enabled by Internet of Things (IoT) technologies, many household loads offer tremendous opportunities for aggregated demand response at wholesale level markets. The spinning reserve market is one that fits well in the context of swimming pool pumps in many regions of the U.S. and around the world (e.g. Texas, California, Florida). This paper offers rigorous treatment of the collective reliability of many pool pumps as firm generation capacity. Based on the reliability assessment, an optimal scheduling of pool pumps is formulated and solved using scenario-based approach. The case study is performed using empirical data from Electric Reliability Council of Texas (ERCOT). Cost-benefit analysis based on a city suggests the potential business viability of the proposed framework.
Markets, Policy, and Computation, Ancillary service, demand response, internet of things (IoT), reliability assessment, scenario based optimization
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