Abstract
This paper investigates the issue of frequency regulation of a single-area alternating current (AC) power system connected to an electric vehicle (EV) aggregator through a nonideal communication network. It is assumed that the command control action is received by the EV aggregator with constant delay and the power system experiences uncertain parameters. A novel effective iterative algorithm, direct search, is proposed for the time-delayed system to design the gains of a proportional-integral (PI) controller. The proposed direct search algorithm can find a feasible solution whenever at least one solution lays in the space search. Thus, by choosing a wide space search, we can expect that the PI controller assures the closed-loop stability, theoretically. The proposed approach has low conservative results over the existing approaches. For the uncertain time-delayed system, a robust PI controller is designed, which is resilient against the system uncertainties and time delay. Numerical simulations are carried out to show the merits of the developed controller.

Abstract
The evaluation index of renewable power forecasting plays an important role in guiding the power grid dispatching department and the operation of renewable power plants. Most of the current evaluation indexes can hardly reflect the relationship between prediction error and system flexibility. Firstly, this paper studies the evaluation index of system flexibility, determines the weight of different flexibility indexes by entropy method, and quantifies the flexibility of power system. On the basis of the existing index, the system flexibility is introduced to improve the existing index, and a new error evaluation index Root Weighted Squared Error is obtained. The simulation results show that the new evaluation index has good performance in measuring the level of single station prediction and multi-station scheduling.

Abstract
To increase the security level and stability of the power systems, high controllability capability is needed. The voltage security margin (VSM) index in power systems can be also affected by various transmission switching (TS) maneuvers. However, one of the major challenges in optimal power flow problems using TS, is that there is no limit to the number of switching on the network over specific periods, thus increasing the probability of a failure occurrence, reducing also the reliability and lifetime of circuit breakers. In this work, a model of optimal power flow (OPF) problem using smart TS concerning the reliability of the CBs to reduce the number of switching and operation costs is presented, formulated with a non-linear function. Thus, a linearization method is implemented to linearize CBs reliability formulation, considering as well locally reactive power compensation devices such as capacitors, allowing more active power flow through the lines to supply more loads. An optimal planning and operation of capacitors can be introduced as another solution to increase the voltage security margin and network loading. The proposed linearized AC power flow model is evaluated in a real case study of the Fars Regional Electric Network in Iran.

Abstract
Electrical energy consumption pattern has always been important for power distribution companies, because load variations and method of electricity consumption affect energy losses amount. For this, distribution companies frequently encourage the network users to correct their energy consumption behavior by suggesting some incentives. Reconfiguration of distribution systems for a specific load pattern is an effective way to reduce the losses. Hence, some papers have considered load variations in distribution system reconfiguration (DSR) to show importance of consumption pattern for reconfiguration decisions. However, most of specialized studies have been ignored load changes in their reconfiguration models because of a significant increase in computational burden and processing time. On the other hand, neglecting the consumption pattern causes the energy losses is calculated inaccurately. Therefore, this paper intends to evaluate effect of load pattern on reconfiguration plans in order to find out importance of considering load variations in energy losses minimization via DSR. The analysis has been conducted on well-known distribution systems by AMPL (a classic optimization tool).

Abstract
High penetration of distributed energy resources in distribution networks is facilitated through the microgrids (MGs) structure. From the technical point of view, the MG operator (MGO) is responsible for the internal operation of the MG regarding which the distribution system operator (DSO) cannot take any decision. From the market viewpoint, the MGO participates in the wholesale markets regarding which the scheduling of the MG's resources is monitored. Therefore, the operation problem of the MGO considering its participation in the wholesale markets under uncertainty has been investigated in many studies. In this paper, a two-stage stochastic optimization approach is developed to model the MGO's bidding strategies in the day-ahead energy and reserve markets considering its stochastic decisions in a real-time market. In this model, the uncertainties of demand, wind speed, and solar radiation are modeled through different scenarios using the probability distribution functions (PDFs) of these parameters. Moreover, the uncertainty of the real-time energy price is modeled using the information gap decision theory (IGDT) method. To show the effectiveness of the model, it is applied on a MG test system.

Abstract
The increasing penetration of uncertain generation from renewable resources poses a challenge for keeping flexibility of power system. Therefore, in order to deal with the condition of insufficient flexibility, a day-ahead modified dispatching model considering the flexibility of power system is proposed. In this modified model, the flexibility is represented by up-regulated flexibility coefficient and down-regulated flexibility coefficient, and these parameters will be used to construct the wind power deviation cost in the objective function which is used to increase the regulated capacity of power system. In the case study, two wind power nodes in the IEEE 30-bus system are connected to two actual wind power farms in Hebei province respectively to verify the validity of the modified model. Finally, Simulation results show that, compared with conventional dispatching models, the modified dispatching model can not only reduce the economic cost, but also increase available regulated capacity to enhance the flexibility of power system.