Optimal PMU placement for fault observability in distributed power system by using simultaneous voltage and current measurements

This paper proposes a new strategy to achieve fault observability of power systems while aiming minimum required number of Phasor Measurement Units (PMUs) in the network. The proposed method exploits the nodal voltage and mesh current analyses where the impedance and admittance matrices of the network and its dual circuit are developed and utilized for fault location. The criterion of determining the number and the places of PMUs is to be able to obtain the fault location and impedance in a unique manner (i.e., without multi estimation.) In addition, the method considers faults along the lines as opposed to the faults only on system buses available in the literature. The proposed approach provides an economical solution to decrease measurement costs for large power networks, distributed generation networks, and micro grids. Simulation results for IEEE 7-bus, 14-bus, and 30-bus systems verify the effectiveness of the proposed approach. © 2013 IEEE

Control of UPFC using Hamilton-Jacobi-Bellman formulation based neural network

In this paper, the micro grid stability is investigated by utilizing a non-linear optimal controller and FACTS device. Using micro grid continuous-time model and control design impose a huge computational burden due to the required high sampling rate to achieve stability when utilizing a digital controller. Thus, developing of an advanced discrete-time (DT) stabilizing controller design is of paramount importance in the micro grids. In this paper a nonlinear discrete-time stabilizing controller using Unified Power Flow Controller (UPFC) is proposed for micro grids by employing the discrete-time Hamilton-Jacobi- Bellman (HJB) optimal control method. The designed optimal controller is applied to control the UPFC\u27s series voltage and to optimally mitigate the power oscillations. The micro grid under consideration is comprised of a synchronous generator, renewable energy sources, and loads. The UPFC series voltage is considered as control input and the optimal strategy is applied. A discretized micro grid nonlinear dynamical model is derived and successive approximation method is utilized to approximate the cost function of the generator states and the UPFC control parameters. Finally, a neural network (NN) is utilized to approximate the cost function using the weighted residual method. By applying the developed optimal controller, it is shown that oscillations caused by faults are mitigated more effectively compared to the conventional generator controllers. © 2012 IEEE

Micro grid stability improvements by employing storage

Storage devices can be used in a power grid to store the excess energy when the energy production is high and the demand is low and utilize the stored energy when the produced energy cannot meet the high demands of the consumers. This paper represents two different studies of micro grid consisting of a conventional synchronous generator, as well as renewable energy sources, energy storage, and loads in order to investigate the effective energy flow control and transient stability improvement by employing storage. Thermal storage, unlike electrical one (such as battery) is more environmental friendly, has longer life span, and is more effective in power flow control. In this paper, resistive type thermal storages are proposed and its stability effects on micro grids are evaluated. A suitable model is developed for the storage and the grid\u27s stability analysis is adopted by using linearization methods. Consequently, by designing an optimal controller for the storage the stability of the micro grid is improved as verified through the simulations. © 2013 IEEE