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A large amount of renewable energy resources are integrated into electricity transmission networks. For efficient operation, transmission networks should be smart, in which it is necessary to have the function of estimating the state of the power system. This function determines bus voltage magnitude and phase, which are used for monitoring, operating, and controlling transmission networks. Transmission network state estimation is developed to estimate bus voltage magnitude and phase by many methods, which include genetic algorithms. Published articles have not mentioned in detail how to apply genetic algorithms to estimate the state of large transmission networks, and the application is limited to small networks. Therefore, this work seeks to estimate the state of large transmission networks by genetic algorithms. Strong decoupling was observed between active power and the voltage phase, as well as between reactive power and voltage magnitude, while a weak coupling, between active power and voltage magnitude, as well as between reactive power and voltage phase; voltage magnitude has a value of around 1.0 p.u, and the voltage phase has a value of around 0.0. This paper proposes a novel approach to genetic algorithms for estimating the state of smart transmission networks. In this novel approach, voltage magnitude and phase are separately estimated at each iteration of genetic algorithms. The approach is validated on IEEE 14-, 30-, and 118-bus networks. Results show that our approach can use phasor measurement unit data to estimate the state of large smart transmission networks by genetic algorithms.

The production of metabolic energy in form of ATP by oxidative phosphorylation depends on the coordinated action of hundreds of nuclear-encoded mitochondrial proteins and a handful of proteins encoded by the mitochondrial genome (mtDNA). We used the yeast Saccharomyces cerevisiae as a model system to systematically identify the genes contributing to this process. Integration of genome-wide high-throughput growth assays with previously published large data sets allowed us to define with high confidence a set of 254 nuclear genes that are indispensable for respiratory growth. Next, we induced loss of mtDNA in the yeast deletion collection by growth on ethidium bromide-containing medium and identified twelve genes that are essential for viability in the absence of mtDNA (i.e. petite-negative). Replenishment of mtDNA by cytoduction showed that respiratory-deficient phenotypes are highly variable in many yeast mutants. Using a mitochondrial genome carrying a selectable marker, ARG8m, we screened for mutants that are specifically defective in maintenance of mtDNA and mitochondrial protein synthesis. We found that up to 176 nuclear genes are required for expression of mitochondria-encoded proteins during fermentative growth. Taken together, our data provide a comprehensive picture of the molecular processes that are required for respiratory metabolism in a simple eukaryotic cell.

Variable structure control with sliding mode can provide good control performance and excellent robustness. Unfortunately, the chattering phenomenon investigated due to discontinuous switching gain restricting their applications. In this paper, a chattering free improved variable structure control (IVSC) for a class of mismatched uncertain interconnected systems with an unknown time-varying delay is proposed. A sliding function is first established to eliminate the reaching phase in traditional variable structure control (TVSC). Next, a new reduced-order sliding mode estimator (ROSME) without time-varying delay is constructed to estimate all unmeasurable state variables of plants. Then, based on the Moore-Penrose inverse approach, a decentralized single-phase robustness sliding mode controller (DSPRSMC) is synthesized, which is independent of time delays. A DSPRSMC solves a complex interconnection problem with an unknown time-varying delay term and drives the system’s trajectories onto a switching surface from the initial time instance. Particularly, by applying the well-known Barbalat’s lemma, the chattering phenomenon in control input is alleviated. Moreover, a sufficient condition is established by using an appropriate Lyapunov theory and linear matrix inequality (LMI) method such that a sliding mode dynamics is asymptotically stable from the beginning time. Finally, a developed method is validated by numerical example with computer simulations.