Distribution Expansion Planning Considering Financial Losses Due to Interruptions and Voltage Sags Using Genetic Algorithms

Nowadays, power distribution companies face new challenges in modern societies. Amongst them, a major challenge concerns customers demanding high service of quality and high reliability in their energy of supply to fulfill those demands. This paper proposes to broaden the classical concepts of multi-stage distribution expansion planning in a way to consider power quality costs. A genetic algorithm is proposed to determine the best investment schedule to ensure an economical and reliable energy supply under the constraints of network line load capacities, voltage drops, and load demands. The proposed function fitness joins topics such as: investment costs and financial losses due to interruptions and voltage sags according to the sensibility curve in each customer. The results show that power quality cost is significant and must be considered during the evolutionary process.