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This paper studies an energy management problem for a typical grid-connected microgrid system that consists of renewable energy sources, Combined Heat and Power (CHP) co-generation, and energy storages to satisfy electricity and heat demand simultaneously. We formulate this problem into a stochastic non-convex optimization programming to achieve the minimum microgrid's operating cost, which is difficult to solve due to its non-convexity and coupling feature of constraints. Existing approaches such as dynamic programming (DP) assume that all the system dynamics are known, which results in a high computational complexity and thus are not feasible in practice. The focus of this paper is on the design of a real-time energy management strategy for the optimal operation of microgrids with low computational complexity. Specifically, derived from a modified Lyapunov optimization technique, an online algorithm with random inputs (e.g., the charging/discharging of energy storage devices, power from the CHP system, the electricity from external power grid, and the renewables generation, etc.), which requires no statistic system information, is proposed. We provide an implementation of the proposed energy management algorithm and prove its optimality theoretically. Based on real-world data traces, extensive empirical evaluations are presented to verify the performance of our algorithm.

Oryza rufipogon Griff. (common wild rice; CWR) is the ancestor of Asian cultivated rice (Oryza sativa L.). Investigation of the genetic structure and diversity of CWR in China will provide information about the origin of cultivated rice and the grain quality and yield. In this study, we used 36 simple sequence repeat (SSR) markers to assay 889 accessions, which were highly representative of whole germplasm in China. The analysis revealed a hierarchical genetic structure within CWR. First, CWR has diverged into two ecotypic populations, a south subtropical population (SSP) and a middle subtropical population (MSP), probably owing to natural selection by the different climates. The distribution of specific alleles and haplotypes indicated that Chinese CWR had both indica-like and japonica-like variations; the SSP was an indica-like type, whereas the MSP was more japonica-like. The SSP and MSP further diverged into five (HN, GD-GX1, GX2, FJ and YN) and two (JX-HuN1 and HuN2) geographical populations, respectively. The genetic data suggest the isolation by distance, although water systems also appear to play an important role in the formation of homogenous populations, and occasionally landscape was also involved. The population GD-GX1, which grew widely in Guangdong and Guangxi provinces, was the largest geographical population in China. It had a high level of genetic diversity (GD) and the closest genetic relationship with other inferred populations. The population HN, with the smallest SSR molecular weights and the highest level of GD, may be the most ancestral population.

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