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Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands' grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios. [ABSTRACT FROM AUTHOR]

India is blessed with an abundance of diverse rice landraces in its traditional cultivated areas. Two marker systems (simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)) were used to study a set of 298 rice landrace accessions collected from six different regions of India (Andaman and Nicobar Islands, Chhattisgarh, Jharkhand, Uttar Pradesh, Uttarakhand, and West Bengal). Thirty hyper-variable simple sequence repeats (HvSSRs) and 32,782 single nucleotide polymorphisms (SNPs) were used in inferring genetic structure and geographical isolation. Rice landraces from Uttar Pradesh were the most diverse, with a gene diversity value of 0.42 and 0.49 with SSR and SNP markers, respectively. Neighbor-joining trees classified the rice landraces into two major groups with SSR and SNP markers, and complete geographical isolation was observed with SSR markers. Fast STRUCTURE analysis revealed four populations for SSR markers and three populations for SNP markers. The population structure with SSR markers showed that few individuals from Uttarakhand and Andaman and Nicobar Islands were grouped in small clusters. Population structure analysis with SNP markers showed not very distinct region-wise clustering among the rice landraces. Discriminant analysis of principal components (DAPC) and minimum spanning network (MSN) using SSR markers showed region-wise grouping of landraces with some intermixing, but DAPC and MSN with SNP markers showed very clear region-wise clustering. Genetic differentiation of rice landraces between the regions was significant with both SSR (Fst 0.094–0.487) and SNP markers (Fst 0.047–0.285). A Mantel test revealed a positive correlation between the genetic and geographic distance of rice landraces. The present study concludes that rice landraces investigated in this study were very diverse, and unlinked SSR markers show better geographical isolation than a large set of SNP markers. [ABSTRACT FROM AUTHOR]