Optimal Siting and Sizing of Distributed Renewable Energy in an Active Distribution Network

The distributed generation (DG) plays an important role in the context of the environmental problems and sustain- able development throughout the world. This paper proposes a DG siting and sizing model in an active distribution network (ADN). The objective is to minimize the total cost, including investment, operation and maintenance costs. The proposed model is transferred to a Mixed Integer Second-Order Cone Programming (MISOCP) model based on a distribution network forward backward-sweep power flow and constraint relaxation. The CVX platform and GUROBI solver are used for the solution. The scenario analysis is used for the uncertainties of load and DG. Different numbers of operational scenarios are considered in order to analyze the effect of a non-network solution to the final planning result and total investment. The planning results with and without consideration of active managements, and the planning results with and without taking environmental profits into consideration, are compared and analyzed. The proposed methodology is verified with a modified IEEE 33 example.

Analytical Hybrid Particle Swarm Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Smart Grid

In this paper,the hybridization of standard particle swarm optimisation(PSO)with the analytical method(2/3 rd rule)is proposed,which is called as analytical hybrid PSO(AHPSO)algorithm used for the optimal siting and sizing of distribution generation.The proposed AHPSO algorithm is implemented to cater for uniformly distributed,increasingly distributed,centrally distributed,and randomly distributed loads in conventional power systems.To demonstrate the effectiveness of the proposed algorithm,the convergence speed and optimization performances of standard PSO and the proposed AHPSO algorithms are compared for two cases.In the first case,the performances of both the algorithms are compared for four different load distributions via an IEEE 10-bus system.In the second case,the performances of both the algorithms are compared for IEEE 10-bus,IEEE 33-bus,IEEE 69-bus systems,and a real distribution system of Korea.Simulation results show that the proposed AHPSO algorithm converges significantly faster than the standard PSO.The results of the proposed algorithm are compared with those of an analytical algorithm,and the results of them are similar.

Novel Planning Approach for Fast-charging Station in Integrated System

A promising way to boost popularity of electric vehicles(EVs)is to properly layout fast charging stations(FCSs)by jointly considering interactions among EV drivers,power systems and traffic network constraints.This paper proposes a novel sensitivity analysis-based FCS planning approach,which considers the voltage sensitivity of each sub-network in the distribution network and charging service availability for EV drivers in the transportation network.In addition,energy storage systems are optimally installed to provide voltage regulation service and enhance charging capacity.Simulation tests conducted on two distribution network and transportation network coupled systems validate the efficacy of the proposed approach.Moreover,comparison studies demonstrate the proposed approach outperforms a Voronoi graph and particle swarm optimization combined planning approach in terms of much higher computation efficiency.