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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: In recent scenario, there is abundant availability of renewable energy resources to satisfy the significant increase in residential, industrial, and commercial demand. This paper presents a novel framework to determine the preeminent size of renewable distributed generators (RDGs) by optimizing the system components such as area required for solar‐photovoltaic modules, swept area occupied by wind turbine blades, and area used by fuel cell. A microgrid with hybrid RDG (h‐RDG) is integrated in distribution system to minimize the distribution loss, substation energy requirement, and improve the voltage level of the load. The power loss minimization is formulated as a nonlinear problem and optimized by the proposed Hybrid Nelder Mead‐Particle Swarm Optimization algorithm. The microgrid location is identified by voltage stability index to improve the stability of system. Further, the system is analyzed for energy flow in different seasonal loading conditions with mixture of residential, industrial, and commercial load. The effective performance of the proposed technique is applied to standard 12‐bus, 69‐bus, and a practical Tamil Nadu (TN) 84‐bus radial distribution system (RDS) for different hybrid combinations of h‐RDG in microgrid. The result proves that the proposed method provides a simple and efficient tool for optimal and flexible use of h‐RDG in microgrid under different climatic changes by simultaneously reducing distribution energy loss and improving voltage profile. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a multiobjective method for obtaining optimal size and site of distributed generation (DG), to reduce loss, and DG investment cost while improving the voltage profile in primary distribution networks. To solve the multiobjective problem, a classical technique known as global criterion method is implemented to form a novel objective function equation, which is custom‐built for a distribution system. The application of the global criterion method is explained using a DG that is capable of injecting real power, ie, unity power factor DG, and then extended to DGs capable of injecting reactive power. The method is validated for 2 distribution systems. Results show that the proposed method satisfies the individual objectives simultaneously. The proposed method is also compared with existing methods to exhibit its effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents an application of the chaotic artificial bee colony (CABC) algorithm to identify the optimal location and sizing of the distributed generation (DG) units in order to improve the voltage stability margin in the radial distribution system. Artificial bee colony algorithm is an optimization algorithm based on the intelligent foraging behavior of honey bee swarm. To improve the searching ability of an artificial bee colony algorithm, chaos theory is united with artificial bee colony, called the CABC algorithm. The various impact indices are used to evaluate the multi-objective performance index aimed to identify the optimal location and sizing of combined real and reactive power-based DGs on the distribution systems. The presence of DG in the distribution system has been potential to improve voltage stability of the system. The effect of DG on the weakest bus is analyzed by constructing the PV curve. The effectiveness of the proposed method is tested on 38-node and 69-node radial distribution systems. [ABSTRACT FROM AUTHOR]

This paper presents a mixed-integer nonlinear optimization model for distributed generation (DG) placement in the distribution system. A multiperiod ac optimal power-flow model is developed for minimizing annual energy losses and determining the optimal site and size of DG units. Various system constraints and time-varying demands are incorporated in the model. A novel iterative method for solving the multiperiod DG placement problem based on the Benders decomposition technique is proposed, which reduces the computational burden and facilitates its practical application. Two case studies are presented to illustrate the efficacy of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In a microgrid, the islanding condition occurs when the utility circuit breaker (CB) is opened. In this case, the microgrid is disconnected from the main grid. Therefore, the islanding condition can be detected by monitoring the variables that caused the utility CB to open. In this paper, the utility CB current is measured at the grid side, and the islanding condition is detected based on a feature extracted from the measured signal before the utility CB opening. Discrete wavelet transform is used to extract the features of the measured current, and then, the artificial neural network is trained in order to detect the islanding conditions based on the extracted features. Since the disturbances of distributed generation (DG) units or fault occurrence have no effect on the measured current, the proposed method is an effective one for islanding detection in distribution networks with high penetration of DGs. Copyright © 2014 John Wiley & Sons, Ltd. [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]