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Summary: Identifying maximum penetration level (MPL) of Solar Photo‐Voltaic Generation (SPVG) in the distribution system is crucial for system planners and network operators to keep the system parameters within the acceptable limits. This paper provides a systematic and extensive procedure for evaluation of MPL of SPVG and its enhancement methods in distribution systems. More importantly, it illustrates a novel algorithm for affixing the penetration cap of Solar PV. The methodology initially derives a new stability index for locating SPVGs in the system, including both active and reactive power support from SPVGs. The study shows the utility of redefining MPL of SPVGs by considering the reactive power injection through solar inverters also. Deviating from the practice of considering the conventional constraints of voltage rise and maximum loading for MPL estimation, the paper considers loss minimization as the major constraint. The algorithm has potential to identify distributed integration scenario of SPVGs compared to the limited number of placements in the extant algorithms. This paper provides a novel algorithm to evaluate of maximum penetration level (MPL) of solar photo voltaic generation (SPVG) and its enhancement methods in distribution systems. The utility of redefining the MPL of SPVG by considering the reactive power injection through solar inverter is illustrated. The algorithm has distinct advantages over the extant algorithms in identifying a distributed integration scenario. [ABSTRACT FROM AUTHOR]

Summary: The continuous increase of the distributed energy resources (DERs) penetration levels leads to voltage stability problems in the distribution system. One of the approaches for the mentioned emerging challenge is the proper placement of automatic voltage regulators (AVRs). This paper investigates the optimal placement and sizing of AVRs in a distribution network by presenting a new modification of the teaching‐learning‐based optimization (TLBO) algorithm. The objective functions consist of minimizing the distribution system voltage deviation, energy generation cost, and electrical losses. The modification improves the convergence velocity and accuracy of the TLBO algorithm using the combination of mutation technique and quasi‐opposition‐based‐learning concept. This paper compares the performance of the proposed algorithm with other famous evolutionary algorithms. The test distribution system contains installed DERs that work more efficiently after the placement of AVRs based on the mentioned objective functions by the proposed optimization algorithm. The simulation results display the best optimization algorithms for AVRs placement with a significant level of less than 0.10 (ie, probability‐value). The proposed multiobjective optimization algorithm's considerable merit is the accuracy and convergence velocity in solving this specific optimization problem. [ABSTRACT FROM AUTHOR]

Summary: The purpose of this paper is to present a model for optimal placement of distributed generation units and sectionalizing switches (relocation of the existing switches and installation of new ones) to increase distribution network resilience against the threat of transmission system outage. The proposed model is formulated as a multi‐objective optimization problem with the objectives of minimizing investment costs and maximizing load restoration. In this regard, distribution system operation during normal conditions as well as transmission system outages is considered. In addition, the unique characteristics of the real power grid in Khuzestan province in southwestern of Iran are addressed in the proposed model which makes the model applicable to the real networks with similar characteristics in many parts of the Middle East. This grid has two completely different load patterns (in terms of load curve shape and peak load) corresponding to two hot and temperate periods, which causes completely different concerns for the network's operator. The proposed model is solved using multi‐objective genetic algorithm (NSGA‐II), and it is implemented on the 33‐node test system and the results are analyzed. Moreover, it is applied to the 327‐node real‐world test system in Khuzestan province to demonstrate its applicability to large networks. In both cases, the results confirm the effectiveness of the proposed optimization model. [ABSTRACT FROM AUTHOR]

Summary: A hybrid AC/DC microgrid takes advantages of both DC and AC microgrids with distributed generation (DG) units in both the respective grids connected through a bidirectional interlinking converter (BIC). Control of hybrid AC/DC microgrid presents a significant research and engineering challenge and hence needs increased research efforts. Existing control algorithms restrict individual controllers to control only designated parameters. This paper proposes MPC‐based distributed control algorithm that will analyze grid conditions, and it would designate BIC to regulate the highest deviated parameter (AC/DC voltage or current) in all nonlinear conditions by performing multivariable optimization using variable control scheme in MPC. Other parameters would be controlled by individual controllers as per their capability. MPC being a nonlinear control technique having an excellent dynamic response and constraint inclusion feature has advantage as compared to other linear and nonlinear techniques. The performance of the proposed algorithm has been compared against other techniques and proved in MATLAB/SIMULINK simulation. [ABSTRACT FROM AUTHOR]

Summary: Provisional microgrids create by the connection of two beside microgrids to achieve economic benefits. So far, there have been many reviews on AC microgrids. However, due to the many advantages of DC microgrids, they cannot be ignored. To achieve the advantages of both AC and DC microgrids, hybrid structures were considered. The subject of controlling hybrid microgrids is relatively more complex. Due to the variable nature of the distributed generation resources, this complexity in islanding conditions is even greater than normal conditions. This paper proposes a robust frequency control for islanding provisional microgrid including hybrid AC/DC part as a master microgrid and AC conventional part as a slave microgrid. As authors are aware, there are no scientific reports for frequency control of the proposed microgrid. One of the issues affecting the performance of this controller is the choice of weighting functions. To achieve optimal controller, an algorithm is used to determine the best weighting functions according to the way the controller works, and by examining the sensitivity functions. Finally, simulations were performed to investigate the performance of the controller and the results of using this controller for this microgrid were examined. [ABSTRACT FROM AUTHOR]

SUMMARY Distributed generation (DG) systems are small-scale power generation technologies that offer better reliability of supply, reduced transmission, and distribution losses and cost. The benefits of DG greatly depend on their placement and size. Most of the existing analytical methods developed so far are applicable for single DG installation only. Further, in meta-heuristic-based methods, location and sizing problem of DG were dealt separately in which optimal locations are identified with sensitivity-based methods, and optimal sizing is obtained using meta-heuristic algorithms which may lead to incorrect location and suboptimal sizing. In this paper, a novel method that employs harmony search algorithm with differential operator is proposed to install multiple DG units optimally in distribution system with an objective of minimizing active power loss and improving voltage profile. The proposed method is tested on 33-bus and 69-bus radial distribution systems to demonstrate its performance and efficacy. Results show that the proposed method is superior to existing methods in quality of solution. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]