Open AccessPPSO method for distribution network reconfiguration considering the stochastic uncertainty of wind turbine, photovoltaic and load
Author(s) -
Wu Huayi,
Dong Ping
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0686
Subject(s) - control reconfiguration , mathematical optimization , computer science , photovoltaic system , turbine , monte carlo method , wind power , probabilistic logic , topology (electrical circuits) , particle swarm optimization , network topology , distributed generation , control theory (sociology) , power (physics) , mathematics , engineering , control (management) , electrical engineering , combinatorics , quantum mechanics , artificial intelligence , embedded system , operating system , mechanical engineering , statistics , physics
This study presents a new algorithm to solve distribution network reconfiguration for power loss reduction considering the stochastic uncertain of the wind, photovoltaic generation and load demand. At first, the stochastic power output models of distributed generation and load are built. Then, in order to get the minimum power loss under the optimal network topology, Prim's particle swarm optimisation (PPSO) algorithm, is firstly introduced to determine the optimal plan under different conditions of network power injected. The proposed algorithm utilises the Prim's algorithm to generate a radial network topology without checking the loop and island at each iteration. To obtain the stochastic expected value of the power loss, a probabilistic power flow calculation based on Monte‐Carlo simulation is employed to handle the stochastic feature of distributed generations (DG) and load. Finally, the proposed method is applied to 33‐bus radial distribution system. The PPSO have a good performance to solve distribution network reconfiguration problem.