M. R. Mosavi, A. Akhyani,
Volume 9, Issue 2 (6-2013)
Abstract
In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modified algorithm overcomes the ACO in obtaining global optimal solution and convergence speed, when applied to optimizing the PMU placement problem. We also compare this simulink with SA, PSO and GA that to find capability of ACO in the search of optimal solution. The fitness function includes observability, redundancy and number of PMU. Logarithmic Least Square Method (LLSM) is used to calculate the weights of fitness function. The suggested optimization method is applied in 30-bus IEEE system and the simulation results show modified ACO find results better than PSO and SA, but same result with GA.
M. Esmaeilzadeh, I. Ahmadi, N. Ramezani,
Volume 14, Issue 2 (6-2018)
Abstract
Distributed generation (DG) has been widely used in distribution network to reduce the energy losses, improve voltage profile and system reliability, etc. The location and capacity of DG units can influence on probability of protection mal-operation in distribution networks. In this paper, a novel model for DG planning is proposed to find the optimum DG location and sizing in radial distribution networks. The main purpose of the suggested model is to minimize the total cost including DG investment and operation costs. The operation costs include the cost of energy loss, the cost of protection coordination and also the mal-operation cost. The proposed DG planning model is implemented in MATLAB programming environment integrated with DIgSILENT software. The simulation results conducted on the standard 38-bus radial distribution network confirm the necessity of incorporating the protection coordination limits in the DG planning problem. Additionally, a sensitivity analysis has been carried out to illustrate the significance of considering these limits.
P. Paliwal,
Volume 18, Issue 4 (12-2022)
Abstract
This paper presents a multi-stage planning framework for analysis of stochastic distributed energy resources (DERs) comprising of solar, wind, and battery storage. The existing models do not consider penetration level analysis in conjunction with sizing, placement, and economic assessment. The main objective of this research is to embed all these dimensions of system planning in one structure. The first stage involves reliability constrained component sizing. The second stage pertains to placement of DERs based on loss minimization and voltage profile. The third stage is the main thrust of this work which provides exhaustive economic evaluation and cost-benefit analysis. The novelty of this work lies in the consideration of penetration level in backdrop of all three stages. The proposed formulation is implemented on a 33-Bus radial distribution feeder located in Jaisalmer, Rajasthan, India. Four penetration levels viz. 10, 20, 40, and 60 percent have been investigated and analyzed under different planning scenarios. The results facilitate the determination of optimum penetration level.
