Multi-objective design of reward mechanism under coupling effects considering customer classification and demand response behavior

Considering the volatility and randomness of renewable energy, the integrated demand response (IDR) has proved to be an efficient way to solve the imbalance problem between the supply and demand sides. To manage the flexible loads of customers, as an intermediate participant, the residential load aggregator (RLA) is introduced, which can provide a motivational measure to attract customers to participate in electric and heating IDR. In this study, an incentive-based reward mechanism (RM) is proposed for a RLA based on classified residential customers, to obtain the best bidding contracts in the load market. A novel multi-objective optimization model is developed and calculated by an NSGA-II artificial algorithm maximizing profits of the RLA and customers simultaneously. The customers' profit is described as the monetization of dissatisfaction degree considering both psychology and comfort aspects. Furthermore, to demonstrate the practicality and advantage of the RM, the price-based IDR mechanism is also included in the numerical study for comparison. According to the simulation results, although both RM-based and price-based responses have their own advantages and disadvantages on various performances, the RM performs better since it can reduce more energy demand and save more costs for end-users. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license