An efficient framework for integrating distributed generation and capacitor units for simultaneous grid-connected and islanded network operations

This paper proposes a two-stage planning approach for the efficient utilization of distributed generation (DG) and capacitor banks (CBs) for the simultaneous grid-connected and islanded operations of the balanced distribution networks. The first stage determines the optimal installation locations and capacities of DGs and CBs using an improved variant of the Jaya optimization algorithm (IJaya) to minimize the power losses and voltage deviation during the grid-connected operation of the distribution network. The second stage identifies the optimal operating point of the DG and CB combination to carry the maximum load during the islanded network operation under power supply-demand imbalance conditions. For the second stage, an analytical approach is proposed to identify the best operating power factor for the DG-CB combination, calculating the power loss, and under-utilization of the installed real-reactive power sources. Simulation results on the IEEE 33-bus grid-dependent distribution network demonstrate that the proposed IJaya significantly improved the network performance and outperforms various existing optimization methods. In addition, during the network's islanded operation, maintaining the network power factor equal to the source power factor (pfsource) makes the DG-CB combination operate at their rated capacities

A novel grid-oriented dynamic weight parameter based improved variant of Jaya algorithm

Jaya algorithm (JA) is a single-step metaheuristic optimization technique that is free from algorithm-specific parameters. Regardless of its simplicity, JA proved its effective performance against the variety of optimization algorithms (Du et al., 2018). However, like other swarm-based optimization techniques, the JA also suffers from the inadequacies of slow or premature convergence (Farah and Belazi, 2018). In this study, an improved variant of JA (IJaya) is proposed whose functioning depends on the randomly initiated bounds based grid-oriented weight parameters. Initially, aiming to balance the global exploration and local exploitation capabilities of JA, a dynamic weight parameter is introduced as a varying coefficient for the entire solution updating expression of JA. Then, to maintain the population diversity and to mitigate the complexity of parameter tuning, the introduced weight parameter is dealt with the randomly selected parameter bounds based grid-search mechanism. The proposed IJaya algorithm is benchmarked on well-known 15 unconstrained mathematical test functions, and its performance is analyzed against the standard JA, one modified variant of JA, some well-known state-of-the-art, and few newly introduced optimization algorithms. Furthermore, the non-parametric Friedman and Quade rank tests are also conducted which confirmed the superiority of proposed IJaya both in convergence rate and solution quality. The paper also presents the results obtained by IJaya in two classical structural design problems (a cantilever beam and a 3-bar truss) and a real-world electrical power engineering problem. Numerical results clearly prove the efficiency of the proposed algorithm

Abiotic factors affecting the development of Ulva sp. (Ulvophyceae; Chlorophyta) in freshwater ecosystems

The influence of physicochemical factors on the development of Ulva species with distromatic tubular morphology was studied in three streams located in Poznan, Poland. The study evaluated key environmental factors that may influence the colonisation and growth of Ulva populations in freshwater systems. In total, nine environmental parameters were included: temperature, water depth, pH, oxygen (O2), ammonium (NH4),nitrate (NO3-), phosphate(PO43-), sodium chloride (NaCl) and total iron (Fe). Morphometric features of thalli (length and width, percentage of furcated and young thalli) and surface area of free-floating mats formed by the freshwater populations of Ulva were compared at all sites. Principal components analysis indicated the most important factors influencing Ulva development were sodium chloride concentrations and water depth. Two other key chemical factors affecting the freshwater form of Ulva were phosphate and nitrite concentrations. High concentrations of sodium chloride inhibited the development of Ulva, leading to a lower number of thalli in the Ulva mats. At the siteswith stable and deeper water, the surface area of the mats was larger. Both phosphate and nitrite concentrations were positively correlated with an increase in the number of thalli in the mats and the thalli length