EAI Endorsed Transactions on Energy Web (Apr 2024)

Optimal Planning of User-side Scaled Distributed Generation Based on Stackelberg Game

  • Xiaoming Zhang,
  • Wenbin Cao,
  • Yuhang Sun,
  • Li Wang,
  • Qi Chai

DOI
https://doi.org/10.4108/ew.5655
Journal volume & issue
Vol. 11

Abstract

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BACKGROUND: User-side distributed generation represented by distributed photovoltaic and distributed wind turbine has shown an expansion trend of decentralized construction and disordered access, which is difficult to satisfy the demand for large-scale exploitation and sustainable development of distributed generation under the low-carbon transformation vision of the power system. OBJECTIVES: To address the interest conflict and operation security problems caused by scaled distributed generation accessing the distribution network, this paper proposes the optimal planning method of user-side scaled distributed generation based on the Stackelberg game. METHODS: Firstly, a cluster planning and operation mode of distributed generation is established. Then, a prediction method for planning behavior of user-side distributed generation is proposed in order to predict whether users will adopt the self-build mode or the leasing site mode for distributed generation. Finally, in order to reveal the game relationship between the distribution network operator and the users in the allocation of distributed generation resources, a bi-level planning model for scaled distributed generation is established based on the Stackelberg game. RESULTS: The simulation results show that the revenue of the distribution network operator under the gaming model increases by 10.15% and 16.88% compared to the models of all users self-build distributed generation and all users leasing distributed generation site, respectively, while at the same time, individual users also realize different degrees of revenue increase. CONCLUSION: The case analysis validates the effectiveness of the proposed method in guiding the rational and efficient planning of user-side distributed generation.

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