What is it about?

In order to balance the interests of integrated energy operator (IEO) and users, a novel Stackelberg game-based optimization framework is proposed for the optimal scheduling of integrated demand response (IDR)-enabled integrated energy systems with uncertain renewable generations, where the IEO acts as the leader who pursues the maximization of his profits by setting energy prices, while the users are the follower who adjusts energy consumption plans to minimize their energy costs. Taking into account the inherent uncertainty of renewable generations, the probabilistic spinning reserve is written in the form of a chance constraint; in addition, a district heating network model is built considering the characteristics of time delay and thermal attenuation by fully exploiting its potential, and the flexible thermal comfort requirements of users in IDR are considered by introducing a predicted mean vote (PMV) index. To solve the raised model, sequence operation theory is introduced to convert the chance constraint into its deterministic equivalent form, and thereby, the leader-follower Stackelberg game is tackled into a mixed-integer quadratic programming formulation through Karush-Kuhn-Tucker optimality conditions and is finally solved by the CPLEX optimizer. The results of two case studies demonstrate that the proposed Stackelberg game-based approach manages to achieve the Stackelberg equilibrium between IEO and users by the coordination of renewable generations and IDR. Furthermore, the study on a real integrated energy system in China verifies the applicability of the proposed approach for real-world applications.

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Why is it important?

The findings demonstrate the approach manages to obtain the Stackelberg equilibrium solution efficiently. Besides, the proposed approach is able to promote renewable consumption while maintaining consumers’ thermal comfort within an acceptable range.

Perspectives

(1) To balance the interests of IEO and users, a novel Stackelberg game-based optimization framework coordinating multiple uncertain renewable generations and price-based IDR is proposed. (2) Taking into account the characteristics of time delay and thermal attenuation of DHNs, a sophisticated DHN model is established and integrated into the IES scheduling, and the flexible thermal comfort requirements of users in IDR are considered by introducing a predicted mean vote (PMV) index. (3) To solve the raised scheduling model, sequence operation theory (SOT) is introduced to convert the chance constraint of a spinning reserve into its deterministic equivalence form, which is beneficial to stably and fast find the Stackelberg equilibrium solution. Furthermore, the existence and uniqueness of Stackelberg equilibrium are proved in detail. (4) The proposed method has been successfully applied to two IESs, including a real-world system in China.

Professor/PhD Supervisor/SMIEEE Yang Li
Northeast Electric Power University

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This page is a summary of: Optimal scheduling of integrated demand response-enabled integrated energy systems with uncertain renewable generations: A Stackelberg game approach, Energy Conversion and Management, May 2021, Elsevier,
DOI: 10.1016/j.enconman.2021.113996.
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