Sharmistha Sharma

A Load Flow based Approach for Optimum Allocation of Distributed Generation Units in the Distribution Network for Voltage Improvement and Loss Minimization

DG is nothing but a small scale generation unit connected directly to the distribution network or near customer load center. This system may or may not be connected to the electric grid. DG has a limited size of 10MW or less especially when DG is used in a distribution network. DG is installed at the place where it becomes impracticable to build a central generation plant. DG is installed to improve the voltage profile as well as minimize losses. DG allocation is a crucial factor. Optimum DG allocation provides a variety of benefits. But inappropriate DG allocation can cause low or over voltage in the network. In this paper a load flow based method using ETAP software is used to determine the optimum location & optimum size of DG in a 33 bus distribution system for voltage profile improvement & loss reduction.

Optimal location and sizing of DG to minimize loss of distribution system using SIMBO-Q method

Determination of optimal location and size of Distributed Generation units is one of the major problems of distribution network. Optimum locations and sizes of DG sources have profoundly impacted on the system losses of a distribution network. This paper presents a new optimization technique known as Swine Influenza Model Based Optimization with Quarantine (SIMBO-Q) to determine optimal allocation and sizing of distributed generation units in distribution network to minimize active power loss. SIMBO-Q performs the optimization through quarantine and treatment based on probability. SIMBO variants can be used to solve DG siting and sizing problem with improved convergence and accuracy. The proposed algorithm is applied to a 33-bus distribution system. The results obtained with the proposed method are compared with the results of PSO and numerical studies represent the effectiveness and outperformance of the proposed method.

Energy management of microgrids with renewables using soft computing techniques

Distributed economic dispatch for a microgrid in grid-connected mode with renewable energy is considered in this paper. The objective of minimizing the microgrid net cost accounts for conventional distributed generation cost, utility of elastic loads, penalized cost of distributed storage, and a worst-case transaction cost. The objective function is split into two parts and the generation costs and the worst case transaction costs are minimized individually as well as the entire microgrid net cost is optimized as a whole. The optimization is done using three metaheuristic soft computing algorithms and comparative study among the three is studied. Numerical results are reported to corroborate the effectiveness of the novel approach.