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Interactive game vector: A stochastic operation-based pricing mechanism for smart energy systems with coupled-microgrids

Author:
Lu, Tianguang, Ai, Qian, Wang, Zhaoyu
Source:
Applied energy 2018 v.212 pp. 1462-1475
ISSN:
0306-2619
Subject:
algorithms, case studies, energy, markets, models, prices, renewable energy sources, trade, uncertainty, China
Abstract:
To accommodate the large scale of renewable energy resources now widely integrated into power systems, an interactive two-level pricing mechanism for coupled microgrids (MG) in a smart energy system is proposed that considers operational quality and renewable generation uncertainty. In the upper level of the pricing mechanism, the distribution energy market operator (DEMO) guarantees operational quality by trading energy with coupled microgrids, while the actual transactions between networked microgrids is performed at the lower level. Stochastic programming is applied to handle the uncertainty caused by large-scale renewable integration. An innovative time-varying game vector and energy transaction strategy deal with the spatio-temporal market interaction of the networked microgrids, where each microgrid is able to directly trade all types of energy with any other microgrid at any time. The proposed model is solved using a customized hierarchical genetic algorithm. Case studies on an IEEE bus test feeder and an existing energy system in China demonstrate the effectiveness of the proposed methodology.
Agid:
6013786