کنفرانس مهندسی برق ایران

صفحه اصلی / بیست و نهمین کنفرانس مهندسی برق ایران

The Use of NSGA-2 for Optimal Placement and Management of Renewable Energy Sources When Considering Network Uncertainty and Fault Current Limiters

نویسندگان :

Ali Akbar Farahani¹ Seyed Hossein Hesamedin Sadeghi²

1- دانشگاه صنعتی امیرکبیر (پلی تکنیک تهران) 2- دانشگاه صنعتی امیرکبیر (پلی تکنیک تهران)

کلمات کلیدی :

.Renewable energy sources, network uncertainty, support vector regression, multi-objective optimization, fault current limiters

چکیده :

Due to abundant benefits of renewable energy sources (RESs), their participation in distribution networks is booming. However, they could have adverse effects on the protection coordination schemes. This paper proposes a non-dominated sorting genetic algorithm (NSGA-2) that is a multi-objective optimization procedure to obtain the best locations and sizes of renewable energy sources (RESs) with fault current limiters (FCLs), reducing the short-circuit level of buses. Also, the support vector regression, which is a supervised time series prediction approach in machine learning, is introduced to consider the uncertainty of load demands, network bid changes, and the generated powers of some RESs based on probabilistic states. The efficiency of the proposed procedure is established on the IEEE 33-bus test network.