This paper proposes an alternative to solve the distribution network reconfiguration (DNR) problem, aiming real power losses' minimization. For being a problem that has complexity for its solution, approximate techniques are adequate for solving it. Here, the proposition is a technique based on the firefly metaheuristic, named selective firefly algorithm, where the positioning of these insects is compressed in a selective range of values. The algorithm is applied to the DNR, and all its implementation and adequacy to the problem studied are presented. To define the search space, the methodology presented initially considers a set of candidate switches for opening based on the studied systems' mesh analysis. To reduce these possibilities, a refinement through a load flow analysis criterion (LFAC) is proposed. This LFAC considers the real power losses on each branch for a configuration with all switches closed, then, selecting possible switches to elimination from the set previously established. To demonstrate the behavior and the viability of the LFAC, it was initially applied on a 5 buses' and 7 branches' system. Also, to avoid getting stuck on results that may be considered not good, a disturbance resetting the population is set to occur every time a counter reaches a pre-defined number of times that the best solution does not change. Results found for simulations with 33, 70, and 84 buses are presented and comparisons with selective particle swarm optimization (SPSO) and selective bat algorithm (SBAT) are made.

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This paper proposes a model-based predictive controller for doubly-fed induction generator direct power control. The control law is derived by optimization of an objective function that considers the control effort and the difference between the predicted outputs (active and reactive power) and the specific references, with predicted outputs calculated using a linearized state-space model. In this case, the controller uses active and reactive power loop directly for the generator power control. Because the generator leakage inductance and resistance information were required for this control method, the influence of the estimation errors for these parameters was also investigated. Simulation results are carried out to validate the proposed controller.Index Terms-Direct power control, doubly-fed induction generator (DFIG), model-based predictive control, wind energy.

The energy sector is currently undergoing a rapid transformation with the integration of power electronic converter (PEC)-interfaced renewable energy sources (RES), such as wind and solar photovoltaic (PV) systems, at both the transmission and distribution networks. Power system stability has been significantly influenced by this power grid transformation. This paper comprehensively reviews major power system stability issues affected due to large-scale integration of PEC-interfaced RES in power grids, with some example case studies relevant for each stability category. According to the review, stability issues are mainly originating from reduction in synchronous inertia, reduction in reactive power reserve, low short-circuit strength of the power network, and fault ride-through (FRT) strategy/capability of the PEC-interfaced RES. Decrease in synchronous inertia could affect both the rotor angle stability and the frequency stability, while decrease in short-circuit strength and reactive power reserve could cause voltage stability and rotor angle stability issues in power networks. Sub-synchronous control interactions are also receiving a lot of attention by the power industry due to increasing oscillatory stability incidents reported in power networks with PEC-interfaced RES. FRT capabilities/strategies of PEC-interfaced RES are also playing a pivotal role in power grid stability due to its influence on active and reactive power, hence more emphasis should be placed on FRT schemes of PEC-interfaced RES, since future power grids are expected to operate with 100% PEC-interfaced generation sources. Stability improvement strategies could be implemented to address multiple stability issues in PEC-interfaced power networks; however, rigorous stability studies are required to identify the optimal conditions to implement these improvement strategies. Furthermore, ongoing structural changes in power grids to accommodate remotely sited PEC-interfaced RES are also influencing the stability of power grids. Therefore, all these factors must be carefully considered by system operators when planning and operating power grids in a secure and stable manner with high penetration levels of PEC-interfaced RES.

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