Research and application of modern smart distribution network technology with OMAAPS algorithm
For the problem of voltage exceeding limits in intelligent distribution networks in unknown environments,research is conducted on selecting active distribution networks and multi-agent deep reinforcement learning algorithms as the basis.Simultaneous-ly using a centralized training distributed execution framework,pruning function,and attention mechanism for optimization,and intro-ducing an iterative policy extraction verification algorithm to further improve the training,a multi-agent attention proximal strategy op-timization algorithm can be obtained.Finally,a modern intelligent distribution network technology that integrates multi-agent attention proximal strategy optimization algorithms is designed.The research results show that in practical application,compared with the main-stream sag control method,the electricity cost of the research method is reduced by 1.75%,and the minimum is 582.955 6 yuan.Meanwhile,the average indoor temperature deviation and average voltage deviation are the smallest,corresponding to 0.001 1℃and 1.37*10-7 p.u.,respectively.The above results show that the research method can help users effectively save electricity costs and effectively improve the absorption capacity of modern smart distribution network for new energy such as distributed photovoltaic.
OMAAPS algorithmsmart distribution networkvoltage regulationcivil buildingsenergy system