Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing Schemes

Advancement of renewable energy resources, development of smart grids, and the effectiveness of demand response programs, can be considered as solutions to deal with the rising of energy consumption. However, there is no benefit if the consumers do not have enough automation infrastructure to use the facilities. Since the entire kinds of buildings have a massive portion in electricity usage, equipping them with optimization-based systems can be very effective. For this purpose, this paper proposes an optimization-based model implemented in a Supervisory Control and Data Acquisition, and Multi Agent System. This optimization model is based on power reduction of air conditioners and lighting systems of an office building with respect to the price-based demand response programs, such as real-time pricing. The proposed system utilizes several agents associated with the different distributed based controller devices in order to perform decision making locally and communicate with other agents to fulfill the overall system’s goal. In the case study of the paper, the proposed system is used in order to show the cost reduction in the energy bill of the building, while it respects the user preferences and comfort level.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); Project GREEDI (ANI|P2020 17822); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Tpc1 is an important Zn(II)(2)Cys(6) transcriptional regulator required for polarized growth and virulence in the rice blast fungus

The establishment of polarity is a critical process in pathogenic fungi, mediating infection-related morphogenesis and host tissue invasion. Here, we report the identification of TPC1 (Transcription factor for Polarity Control 1), which regulates invasive polarized growth in the rice blast fungus Magnaporthe oryzae. TPC1 encodes a putative transcription factor of the fungal Zn(II)(2)Cys(6) family, exclusive to filamentous fungi. Tpc1-deficient mutants show severe defects in conidiogenesis, infection-associated autophagy, glycogen and lipid metabolism, and plant tissue colonisation. By tracking actin-binding proteins, septin-5 and autophagosome components, we show that Tpc1 regulates cytoskeletal dynamics and infection-associated autophagy during appressorium-mediated plant penetration. We found that Tpc1 interacts with Mst12 and modulates its DNA-binding activity, while Tpc1 nuclear localisation also depends on the MAP kinase Pmk1, consistent with the involvement of Tpc1 in this signalling pathway, which is critical for appressorium development. Importantly, Tpc1 directly regulates NOXD expression, the p22(phox) subunit of the fungal NADPH oxidase complex via an interaction with Mst12. Tpc1 therefore controls spatial and temporal regulation of cortical F-actin through regulation of the NADPH oxidase complex during appressorium re-polarisation. Consequently, Tpc1 is a core developmental regulator in filamentous fungi, linking the regulated synthesis of reactive oxygen species and the Pmk1 pathway, with polarity control during host invasion

An evolutionary framework for measuring epigenomic information and estimating cell-type-specific fitness consequences

Here we ask the question "How much information do epigenomic datasets provide about human genomic function?" We consider nine epigenomic features across 115 cell types and measure information about function as a reduction in entropy under a probabilistic evolutionary model fitted to human and nonhuman primate genomes. Several epigenomic features yield more information in combination than they do individually. We find that the entropy in human genetic variation predominantly reflects a balance between mutation and neutral drift. Our cell-type-specific FitCons scores reveal relationships among cell types and suggest that around 8% of nucleotide sites are constrained by natural selection