Open AccessDispatching approach for active distribution network considering PV generation reliability and load predicting interval
Author(s) -
Ying Yiqiang,
Wu Yingjun,
Su Yiqiang,
Fu Rong,
Liang Xinyi,
Xu Hao
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0766
Subject(s) - interval (graph theory) , reliability (semiconductor) , photovoltaic system , particle swarm optimization , computer science , range (aeronautics) , mathematical optimization , fuzzy logic , grid , mode (computer interface) , power (physics) , reliability engineering , algorithm , mathematics , artificial intelligence , engineering , operating system , physics , geometry , quantum mechanics , combinatorics , aerospace engineering , electrical engineering
With the increasing proportion of the grid‐connected PV power generation, the uncertainties and difficult predictions of PV output make it more difficult to deploy the distribution network. Firstly, the photovoltaic output interval model is established based on the light intensity which is approximate satisfied Beta distribution. Secondly, based on the empirical mode decomposition, the sparse Bayesian learning method and the load forecasting method, the load demand forecasting interval model is established. On this basis, a reliability‐economic oriented optimal dispatch model for the distribution network is proposed, which takes into account the prediction range of PV output and load demand. Then, based on fuzzy sampling method and multi‐objective particle swarm optimisation algorithm, a method to solve the proposed model is presented. Finally, simulation results show the effectiveness of the method.