An improved optimization technique for estimation of solar photovoltaic parameters

The nonlinear current vs voltage (I-V) characteristics of solar PV make its modelling difficult. Optimization techniques are the best tool for identifying the parameters of nonlinear models. Even though, there are different optimization techniques used for parameter estimation of solar PV, still the best optimized results are not achieved to date. In this paper, Wind Driven Optimization (WDO) technique is proposed as the new method for identifying the parameters of solar PV. The accuracy and convergence time of the proposed method is compared with results of Pattern Search (PS), Genetic Algorithm (GA), and Simulated Annealing (SA) for single diode and double diode models of solar PV. Furthermore, for performance validation, the parameters obtained through WDO are compared with hybrid Bee Pollinator Flower Pollination Algorithm (BPFPA), Flower Pollination Algorithm (FPA), Generalized Oppositional Teaching Learning Based Optimization (GOTLBO), Artificial Bee Swarm Optimization (ABSO), and Harmony Search (HS). The obtained results clearly reveal that WDO algorithm can provide accurate optimized values with less number of iterations at different environmental conditions. Therefore, the WDO can be recommended as the best optimization algorithm for parameter estimation of solar PV

進化的及び樹状突起のメカニズムを考慮したソフトコンピューティング技術の提案

富山大学・富理工博甲第117号・宋振宇・2017/03/23富山大学201

A new perspective on the irregular satellites of Saturn - I Dynamical and collisional history

The dynamical features of the irregular satellites of the giant planets argue against an in-situ formation and are strongly suggestive of a capture origin. Since the last detailed investigations of their dynamics, the total number of satellites have doubled, increasing from 50 to 109, and almost tripled in the case of Saturn system. We have performed a new dynamical exploration of Saturn system to test whether the larger sample of bodies could improve our understanding of which dynamical features are primordial and which are the outcome of the secular evolution of the system. We have performed detailed N--Body simulations using the best orbital data available and analysed the frequencies of motion to search for resonances and other possible perturbing effects. We took advantage of the Hierarchical Jacobian Symplectic algorithm to include in the dynamical model of the system also the gravitational effects of the two outermost massive satellites, Titan and Iapetus. Our results suggest that Saturn's irregular satellites have been significantly altered and shaped by the gravitational perturbations of Jupiter, Titan, Iapetus and the Sun and by the collisional sweeping effect of Phoebe. In particular, the effects on the dynamical evolution of the system of the two massive satellites appear to be non-negligible. Jupiter perturbs the satellites through its direct gravitational pull and, indirectly, via the effects of the Great Inequality, i.e. its almost resonance with Saturn. Finally, by using the Hierarchical Clustering Method we found hints to the existence of collisional families and compared them with the available observational data.Comment: 26 Pages, 27 Figures, 4 Table

Chaos embedded opposition based learning for gravitational search algorithm

Due to its robust search mechanism, Gravitational search algorithm (GSA) has achieved lots of popularity from different research communities. However, stagnation reduces its searchability towards global optima for rigid and complex multi-modal problems. This paper proposes a GSA variant that incorporates chaos-embedded opposition-based learning into the basic GSA for the stagnation-free search. Additionally, a sine-cosine based chaotic gravitational constant is introduced to balance the trade-off between exploration and exploitation capabilities more effectively. The proposed variant is tested over 23 classical benchmark problems, 15 test problems of CEC 2015 test suite, and 15 test problems of CEC 2014 test suite. Different graphical, as well as empirical analyses, reveal the superiority of the proposed algorithm over conventional meta-heuristics and most recent GSA variants.Comment: 33 pages, 5 Figure