中圖分類號(hào)：TM933 文獻(xiàn)標(biāo)志碼：A DOI: 10.16157/j.issn.0258-7998.245003
中文引用格式： 馮迎春，陶力，劉敦楠，等. 新型電力系統(tǒng)下基于改進(jìn)灰狼算法的用戶購(gòu)電策略研究[J]. 電子技術(shù)應(yīng)用，2024，50(10)：69-75.
英文引用格式： Feng Yingchun，Tao Li，Liu Dunnan，et al. User optimal purchase strategy with improved gray wolf algorithm in novel power system[J]. Application of Electronic Technique，2024，50(10)：69-75.

User optimal purchase strategy with improved gray wolf algorithm in novel power system

Abstract： As China’s novel power system construction is continuously accelerating, the reform on the electricity sales side continues to deepen, and the competition in the retail market has become increasingly fierce. As a market entity with a large scale of electricity consumption, large-scale interactive users need to formulate reasonable strategies when making power purchase decisions to maximize benefits. This paper proposes an optimization model for power purchase decisions based on the improved gray wolf optimization algorithm. Firstly, reasonable design of power purchase decisions is carried out from the aspects of green electricity consumption rights and responsibilities, temporary electricity demand, controllable electricity plans, and minimization of total electricity bills. Then, based on the combination of different retail packages, an improved grey wolf optimization algorithm is constructed to iteratively solve the optimal strategy for the power purchase decision model. The results of the example show the effectiveness and rationality of this power purchase strategy, which can effectively release the dividends of power system reform.

Key words : power purchase strategy；retail package；green power consumption；demand response；gray wolf optimization