An incentive-compatible distributed integrated energy market mechanism design with adaptive robust approach. (15th January 2021)

• Record Type: Journal Article
• Authors: Yao, Yunting; Gao, Ciwei; Lai, Kexing; Chen, Tao; Yang, Jianlin
• Is Part Of: Applied energy. Volume 282(2021)Part A
• Publication Date: 2021-01-15
• Subjects: Adaptive robust optimization -- Distributed integrated energy market -- Incentive-compatibility theory -- Market mechanism design; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.116155
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: The transactive energy framework was proposed in the recent years to enable the distributed energy trading among distributed integrated energy market. However, sharing energy might lead to profit loss to some participants. As a result, the incentive of joining the coalition for some participants will be diminished. Currently, researches have focused on encouraging participants to share energy by offering compensation, but the incentive compatibility is not modeled effectively. To address this problem, this paper, for the first time, develops an optimization model for the market organizer (i.e., the integrated energy service provider) to allocate the cooperative surplus according to the market contribution while the crucial attributes of the market mechanism are ensured (i.e., social welfare maximization, individual rationality, cost recovery and incentive compatibility), so that market participants can earn their fair shares and profit reductions can be circumvented. On the other hand, the problem caused by the highly uncertain and intermittent power outputs from distributed renewable energy resources imposes additional challenge for organizing a transactive energy market, which calls for the exploitations of effective algorithms to identify representative scenarios. In this paper, adaptive robust optimization algorithm is adopted to identify the scenarios that enhances conservativeness and economy and improves the efficiency of market clearing process, which transforms the problem into a tri-level model and solves by iterating between internal and external formulations. Simulation results show that social welfare increases $2, 751 compared with independent operation mode, and calculation efficiency can be improved by 71.55% utilizing the ARO method. Highlights: An incentive-compatible trading mechanism is designed for integrated energy users. Adaptive robust optimization formulation is developed to optimize system operation. Efficient solution algorithm is developed to handle large-scale random scenes. Four attributes are met ensuring the fair and effective distribution of benefits.