Historical-based bidding strategy in transactive energy market for household: Data driven analysis

Abstract

The energy market design is changing to enable distribution-level transactions in smart cities, encouraging end-users to participate efficiently in the market. The Transactive Energy (TE) concept opens the floor for a new market settlement philosophy that can benefit the end-user and Distributed Generators (DGs). The bidding of the customers in the distribution level market raises many concerns in the latest reports due to many factors (e.g., lack of information about the participant’s flexibility). This paper proposes a non-intrusive bidding strategy to enhance the accuracy of the household’s participation in the transactive electricity market. The proposed model utilizes the historical household user energy consumption to build the thermal model and develop the bidding strategy. The proposed approach examines the bidding in the context of user preferences of the total consumption, time at bidding, day of bidding, and ambient temperature. The results prove that the proposed strategy can significantly improve the flexibility’s recognition of the customers’ participation in the transactive market. Finally, the efficacy of the bidding method is examined via numerical analysis of actual data.