Minimize active power loss with distribution network reconfiguration considering intermittent renewable energy source uncertainties

With the economy fast development and urbanization moving forward in China, electricity demand of urban center keeps growing. The users are paying more attention on the electricity quality and harmony with the environment. At the same time, the advantages of distributed generation, such as the high efficiency, lower carbon emission have been paid more attention. As above, the distribution network is facing unprecedentedly large amount of distributed generation, especially the intermittent renewable energy source (IRS). But the uncertainties of IRS generation have effect on the safe and reliable operation of distribution network. So it is necessary to put emphasis on the distribution network operation considering system uncertainties. This paper presents a novel distribution network reconfiguration model considering the load and IRS output uncertainties. The model minimizes the expectation of the total active power loss. The Monte Carlo simulation is selected for the probabilistic power flow. An evolutionary algorithm suitable for distribution network reconfiguration is proposed. The algorithm is based on Partheno Genetic Algorithm with Tree Structure Encoding technology. Baran&Wu 33 and TPC 84 case are presented to testify the proposed model and algorithm.