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Numerous potential advantages to the requirements and effectiveness of the supplied electricity can be accomplished by the installation of distributed generation units. In order to take full advantage of these benefits, it is essential to position the Distributed Generation (DG) units in appropriate locations. Otherwise, their installation may have an adverse effect on the quality of energy and system operation. Several optimization techniques have been created over the years to optimize distributed generation integration. Optimization techniques are therefore constantly changing and have been the main attention of many fresh types of research lately. This article evaluates cutting-edge techniques of optimizing the issue of positioning and sizing distributed generation units from renewable energy sources based on recent papers that have already been applied to distribution system optimization. Furthermore, this article pointed out the environmental, economic, technological and regulatory drivers that lead to a rapid interest in the DG system based on renewable sources. A summary of popular meta-heuristic optimization tools discussed in table form with merits and demerits to increase fresh prospective paths to multi-approach that have not yet been studied. [ABSTRACT FROM AUTHOR]

In the present study, we sequenced and assembled the complete chloroplast genome of Fagopyrum leptopodum (Diels) Hedberg. The chloroplast genome of F. leptopodum was composed of 85 protein-coding genes, 8 ribosomal RNA genes, and 37 transfer RNA genes. The F. leptopodum chloroplast genome is 159,375 bp in length, with a GC content of 37.81%. Phylogenetic analysis based on the combined chloroplast gene dataset indicated that the F. leptopodum exhibited a close relationship with Fagopyrum luojishanense. [ABSTRACT FROM AUTHOR]

This article investigates the use of optimal reference point placement to improve performance of non-dominated sorting genetic algorithm (NSGA). Placement of reference points for many-objective optimization is inspired by wheel and Von Neumann topologies of Particle Swarm Optimization (PSO). Results obtained show that the pattern of reference point placement determines performance efficiency of NSGA. The better-performing wheel topology (called wheel reference point genetic algorithm (wRPGA), is compared to three other many-objective evolutionary algorithms: knee-driven evolutionary algorithm (KnEA), non-dominated sorting genetic algorithm III (NSGAIII) and multi-objective evolutionary algorithm based on dominance and decomposition (MOEAD/D). The selected many-objective benchmark problems are Walking Fish Group 2 (WFG2) and Deb-Thiele-Laumanns-Zitzler 2 (DTLZ2). It is also tested on a 3-objective cost function for a hypothetical model of a stand-alone microgrid. Through the simulations, the wheel configuration performed 88.9% better than the Von Neumann configuration. The wheel topology also achieved better performance with respect to inverted generational distance (IGD) compared to KnEA, NSGAIII and MOEAD/D for 7 out of 15 IEEE Congress on Evolutionary Computation (CEC) 2017 benchmark problems. wRPGA gave a good approximation of the Pareto front for the 3-objective model representing the hypothetical microgrid. [ABSTRACT FROM AUTHOR]

Operational planning of prosumer microgrids with solar and wind energy sources is quite a complex task considering the intermittency of these sources and energy import/export from prosumers. Reserve capacities which can be reliably provided by dispatchable sources like conventional generators (CGs) may be needed to ensure reliability of the grid. However, these sources produce emissions which have adverse effects on the environment. Hence, emission curtailment should be incorporated in the operational planning of microgrids with these generators. In this paper, a mathematical formulation for the joint economic and emission dispatch of a renewable energy-assisted prosumer microgrid is presented and solved using the CPLEX Solver in Advanced Interactive Multidimensional Modelling System (AIMMS). A modified microgrid test system is used as a case study in this work. Results show that incorporating an emission function in the objective of the operational dispatch formulation not only reduces emissions, but could be of advantage to customers as larger capacities of their behind-the-meter resources get the chance to provide grid ancillary services; however, it also puts a restriction on the profit that could be made from selling energy to the main grid during periods when energy prices are high. [ABSTRACT FROM AUTHOR]

The introduction of new operation enhancement technologies plus increasing application of power electronics, coupled with the continuous increase in load demand, has increased the risk of power networks to voltage instability and susceptibility to voltage collapse. This frequent occurrence of voltage collapse in modern power system has been a growing concern among power system utilities. This paper proposes alternative techniques for the identification of critical nodes that are liable to voltage instability in a power system. The first method is based on the critical mode corresponding to the smallest eigenvalues, while the second technique is based on the centrality measure to identify the most influential node of the networks. The eigenvector centrality measure is formulated from the response matrices of both the load and generator nodes of the networks. The effectiveness of the suggested approaches is tested using the IEEE 30-bus and the Southern Indian 10-bus power networks. The results are compared with the techniques based on the traditional power flow. The whole procedure of the results involved in the identification of critical nodes through the proposed methods is totally non-iterative and thereby saves time and requires less computational burden. [ABSTRACT FROM AUTHOR]