Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

The Xenopus

primordial germ cells (PGCs) are determined by the presence of maternally derived germ plasm. Germ plasm components both protect PGCs from somatic differentiation and begin a unique gene expression program. Segregation of the germline from the endodermal lineage occurs during gastrulation, and PGCs subsequently initiate zygotic transcription. However, the gene network(s) that operate to both preserve and promote germline differentiation are poorly understood. Here, we utilized RNA-sequencing analysis to comprehensively interrogate PGC and neighboring endoderm cell mRNAs after lineage segregation. We identified 1865 transcripts enriched in PGCs compared with endoderm cells. We next compared the PGC-enriched transcripts with previously identified maternal, vegetally enriched transcripts and found that ∼38% of maternal transcripts were enriched in PGCs, including PGC-directed knockdown and overexpression studies revealed an early requirement for in germ plasm localization, zygotic transcription and PGC number. We identified as the most highly expressed and enriched homolog in PGCs. We compared the PGC transcriptome with human PGC transcripts and showed that 80% of genes are conserved, underscoring the potential usefulness of for understanding human germline specification