Optimal Expansion Planning of Distribution System and DG Placement Using BPSO

A new method to solve the single and multi-objective distribution expansion planning problems including DG is investigated in this paper. The sizing and placement of DG as well as the required power of the main grid would be optimized using proposed method to meet the demand. Binary Particle Swarm Optimization (BPSO) algorithm is used to solve the optimization problem for three objective functions: total expansion cost, total voltage deviation, and total system loss. The goal of presented model is to satisfy operational and economic requirements by using DG as an alternative candidate for distribution system planning to avoid or at least reduce the expanding existing substations and upgrading existing feeders. The 30-bus distribution system is used in this work to evaluate the proposed algorithm. The conventional Weighted Aggregation Method is used to solve the multi-objective optimization problem so that further objective functions and constraints can be easily added to the proposed algorithm. Optimization results show that the DG has economical and electrical advantages in comparison with the traditional method

Power system security improvement using an OPA model and IPSO algorithm

The growing demand for power generation makes power systems increasingly more complex to operate and less secure against outages, so the risk of extensive blackouts is growing and needs to be addressed. Cascading failures are the main reason for extensive blackouts, so to investigate this effect a new method including a standard blackout model, named ORNL-PSerc-Alaska (OPA), and static synchronous series compensator (SSSC) placement using an improved particle swarm optimization (IPSO) algorithm is proposed. This study provides two optimization approaches and presents optimal corrective actions. The results will help operators to implement corrective actions like optimal generation and load redispatching to return the system to a stable operating condition. The effectiveness of the proposed model is demonstrated using a realistic transmission network. Simulation results show a significant effect of SSSC on decreasing the risk of cascading failures and the ability of the proposed method to prevent blackout. </jats:p