面向区域配电网的分布式能效数据分析与优化技术

Distributed energy efficiency data analysis and optimization technology for regional distribution networks

分布式电源出力的间歇性及用电负荷的不确定性使得电力生产及储能调度面临巨大挑战,对区域配电网的经济性、可靠性有重大影响。为此,提出一种面向区域配电网的分布式能效数据分析与优化技术。首先,通过分析区域配电网新能源电站、用电负荷和储能电站各主体运行特性,分别建立各单元模块数学模型,基于神经网络模型对新能源发电量及用电负荷进行预测。然后,以电能约束下的能效数据最优为目标,以S-ADMM法为基础,提出了一种源网荷储协同优化经济调度算法,辅助优化区域性的能源电力生产和储能调控的配电网运行控制。实验结果表明,所提的分布式能效数据分析与优化技术能够有效提升区域配电网的能效,显著提升各主体收益,平均收益率可提升20%以上,为用户提供了更多的购电选择,有助于区域化分布式新能源生产的总体调控和储能运行控制。

The intermittency of distributed power generation output and the uncertainty of electricity load pose great challenges to power production and energy storage scheduling,which have a significant impact on the economy and reliability of regional distribution networks.Therefore,a distributed energy efficiency data analysis and optimization technology for regional distribution networks is proposed in the article.By analyzing the operational characteristics of new energy power stations,electricity loads,and energy storage power stations in the regional distribution network,mathematical models for each unit module are established.Based on neural network models,new energy generation and electricity loads are predicted.Subsequently,with the goal of optimizing energy efficiency data under energy constraints,a source network load storage collaborative optimization economic dispatch algorithm based on the S-ADMM method was proposed to assist in optimizing regional energy production and energy storage regulation of distribution network operation control.The experimental results show that the distributed energy efficiency data analysis and optimization technology proposed in the article can effectively improve the energy efficiency of the regional distribution network,significantly increase the income of each entity,and increase the average return rate by more than 20%.It provides users with more power purchase options,which is helpful for the overall regulation of regional distributed new energy production and energy storage operation control.