Open AccessOptimal operation and cost–benefit allocation for multi‐participant cooperation of integrated energy system
Author(s) -
Luo YanHong,
Zhang XinWen,
Yang DongSheng,
Sun QiuYe,
Zhang HuaGuang
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.0894
Subject(s) - profit (economics) , incentive , computer science , game theory , cooperative game theory , operations research , optimal allocation , environmental economics , order (exchange) , energy (signal processing) , cost allocation , mathematical optimization , microeconomics , economics , engineering , statistics , mathematics , accounting , finance
In the trend of multi‐energy integration development and the intellectualisation for demand‐side, the application of integrated energy system (IES) contained demand response is of great significance to the economic operation of energy systems. The energy hubs are widely studied as effective tools for integrating regional energy in the IES. With the expansion of schedulable devices, the mode of multiple energy hubs (MEHs) cooperative operation is proposed in this study. Moreover, in order to adjust the periodic loads, the authors further study the responsiveness of electric vehicles, air‐conditioning and energy storages according to time‐of‐use price incentive mechanisms, and the total operation cost is minimised. Meanwhile, the eco‐friendly target is achieved by the pollutant trading market. Furthermore, due to the complementary characteristic of MEHs, the economics allocation issues are also carefully considered where the cost and benefit of each participant are allocated by cooperative game theory to make them satisfied with the profit brought by cooperation. The simulation takes three hubs cooperation as an example to verify the effectiveness of the proposed methods. The results show that the total profit increased by 53.54% and the peak load is reduced by 27.06% after optimal operation, and the modified propensity to disrupt verifies the fairness of allocation.