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Data-driven recommandation mechanism for flexible load management

This paper proposes a distributed control system for flexible loads using a recommendation mechanism. The recommendation mechanism is implemented at the aggregator level and coordinates the flexible loads through smart controllers based on a ranking algorithm. In the existing demand response system, the aggregator broadcasts control sequences to flexible loads and collect schedules from them. The problems associated with such systems are: (1) consumers can overwrite control orders from aggregators and flexible loads may not fully achieve their flexibility requirements; (2) as more and more flexible loads involve in demand response, they also need competition to motivate better flexible service. To overcome these issues, a recommendation system becomes necessary. The system works as an advanced filter to select the most “manageable” flexible loads by ranking their past usage. Thus, the aggregator can identify them using the designed recommendation system based on historical data. We demonstrate the recommendation process and simulate it on an IEEE system. The results show that the proposed algorithm can save money from the flexibility and perform better than the system without recommendation mechanism.