Open AccessStochastic expansion planning of interconnected distribution networks with renewable sources considering uncertainties and power transfer capability
Author(s) -
Liu Jia,
Cheng Haozhong,
Xu Qian,
Lan Zhou,
Zeng Pingliang,
Yao Liangzhong
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0602
Subject(s) - mathematical optimization , computer science , maximum power transfer theorem , transformer , exploit , renewable energy , integer programming , contingency , operations research , power (physics) , engineering , mathematics , linguistics , physics , philosophy , computer security , quantum mechanics , voltage , electrical engineering
This study proposes a stochastic optimisation model for interconnected distribution network planning (IDNP) in the presence of renewable sources (RSs) considering power transfer capability after an N − 1 contingency. Two types of scenarios, feeder contingency, and substation transformer contingency, are formulated in the IDNP problem. Uncertainties of the RS output and load fluctuation are also integrated. The planning method provides planners with the decisions of feeder reformation, new tie lines, new feeders, substation expansion, new substations and new load allocation. The IDNP model is a chance‐constrained mixed integer non‐linear programming problem, which is solved by dynamic niche differential evolution algorithm. A case study carried out on a modified 104‐bus distribution network demonstrates the effectiveness of those techniques. Compared with the traditional planning approach, the IDNP method could exploit asset utilisation by optimising existing networks efficiently as well as improve system economy and security simultaneously.