Optimal Placement and Sizing of Wind-Pv Integrated Power Generation by Ant Colony Optimization Technique

Abstract

Abstract-This paper concerns the maximum utilization of energy resources like wind and Photovoltaic (PV) power generation for economic operation. It analyses the wind and PV for a considered load profile. The Generation for each system is minimized so that the total annual cost to the customer gets reduced. The total cost is minimized by optimal placement of wind turbine (WT) and PV system. The optimal placement and sizing of these considered generating units is made through an Ant Colony Optimization (ACO) algorithm. The electrical parameters of WT and PV cells determines the maximum power generation. The Sources are depends on atmospheric factors introduces non-linearity in the system and on the demand side load is fluctuating. The conventional optimization technique fails due to its complexity while solving the non-linear problem. This paper proposes an intelligent ACO algorithm to solve the practical 5 kW WT and PV system. The result clearly shows the superiority of the proposed algorithm. Further, this algorithm gives the idea of solving complex Indian practical generating systems.

Elephant Herding Optimization for Optimum Allocation of Electrical Distributed Generation on Distributed Power Networks

“…Let us assume that the elephant individuals with the worst fitness will implement the separating operator at each generation as shown in eqn. (15).…”

“…They are Genetic algorithm [10] is used to place generation, such that loss costs and network disruption are minimized and the rating of the generator gets maximized. The various optimization techniques such as Tabu Search (TS) [11], Particle swarm Optimization (PSO) [12], Artificial Bee Colony (ABC) [13], Bat Motivated Optimization (BMO) [14], Ant Colony Optimization (ACO) [15], Bacterial Swarm Optimization (BSO) [16,17], Enriched Biogeography Based Optimization (EBBO) Algorithm [18] are introduced to solve the optimal allocation in distribution network successfully. The hybrid optimization algorithm include Improved Multi-Objective Harmony Search (IMOHS) [19] is applied to evaluate the impact of DG placement for an optimal planning of a distribution system.…”