Optimal spatio-temporal emergency crew planning for a distribution system

Author(s):  
Ali Koc ◽  
Amith Singhee ◽  
Haijing Wang ◽  
Ashish Sabharwal ◽  
Richard Mueller ◽  
...  
2017 ◽  
Vol 18 (2) ◽  
pp. 713-722 ◽  
Author(s):  
Jaime Veintimilla-Reyes ◽  
Annelies De Meyer ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven

Abstract Water in sufficient quantity and quality is indispensable for multiple purposes like domestic and industrial use, irrigated agriculture, hydropower generation and ecosystem functioning. In many regions of the world, water availability is limited and even declining. Moreover, water availability is variable in space and time and often does not match with the spatio-temporal demand pattern. To overcome the temporal discrepancy between availability and consumption, reservoirs are constructed. Monitoring and predicting the water available in the reservoirs, the needs of the consumers and the losses throughout the river and water distribution system are necessary requirements to fairly allocate the available water to the different users, prevent floods and ensure sufficient water flow in the river. In this paper, this surface water allocation problem is considered a Network Flow Optimisation Problem (NFOP) solved by spatio-temporal optimisation using linear programming techniques.


2012 ◽  
Vol 105 ◽  
pp. 12-20 ◽  
Author(s):  
Francois Proulx ◽  
Manuel J. Rodriguez ◽  
Jean B. Sérodes ◽  
Christian Bouchard

2019 ◽  
Vol 149 ◽  
pp. 375-385 ◽  
Author(s):  
Yoann Perrin ◽  
Didier Bouchon ◽  
Vincent Delafont ◽  
Laurent Moulin ◽  
Yann Héchard

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1981 ◽  
Author(s):  
Lidan Chen ◽  
Yao Zhang ◽  
Antonio Figueiredo

Electric vehicles (EVs) can be regarded as a kind of demand response (DR) resource. Nevertheless, the EVs travel behavior is flexible and random, in addition, their willingness to participate in the DR event is uncertain, they are expected to be managed and utilized by the EV aggregator (EVA). In this perspective, this paper presents a composite methodology that take into account the dynamic road network (DRN) information and fuzzy user participation (FUP) for obtaining spatio-temporal projections of demand response potential from electric vehicles and the electric vehicle aggregator. A dynamic traffic network model taking over the traffic time-varying information is developed by graph theory. The trip chain based on housing travel survey is set up, where Dijkstra algorithm is employed to plan the optimal route of EVs, in order to find the travel distance and travel time of each trip of EVs. To demonstrate the uncertainties of the EVs travel pattern, simulation analysis is conducted using Monte Carlo method. Subsequently, we suggest a fuzzy logic-based approach to uncertainty analysis that starts with investigating EV users’ subjective ability to participate in DR event, and we develop the FUP response mechanism which is constructed by three factors including the remaining dwell time, remaining SOC, and incentive electricity pricing. The FUP is used to calculate the real-time participation level of a single EV. Finally, we take advantage of a simulation example with a coupled 25-node road network and 54-node power distribution system to demonstrate the effectiveness of the proposed method.


Author(s):  
Zhiguo Li ◽  
Amith Singhee ◽  
Haijing Wang ◽  
Abhishek Raman ◽  
Stuart Siegel ◽  
...  

2005 ◽  
Vol 41 ◽  
pp. 15-30 ◽  
Author(s):  
Helen C. Ardley ◽  
Philip A. Robinson

The selectivity of the ubiquitin–26 S proteasome system (UPS) for a particular substrate protein relies on the interaction between a ubiquitin-conjugating enzyme (E2, of which a cell contains relatively few) and a ubiquitin–protein ligase (E3, of which there are possibly hundreds). Post-translational modifications of the protein substrate, such as phosphorylation or hydroxylation, are often required prior to its selection. In this way, the precise spatio-temporal targeting and degradation of a given substrate can be achieved. The E3s are a large, diverse group of proteins, characterized by one of several defining motifs. These include a HECT (homologous to E6-associated protein C-terminus), RING (really interesting new gene) or U-box (a modified RING motif without the full complement of Zn2+-binding ligands) domain. Whereas HECT E3s have a direct role in catalysis during ubiquitination, RING and U-box E3s facilitate protein ubiquitination. These latter two E3 types act as adaptor-like molecules. They bring an E2 and a substrate into sufficiently close proximity to promote the substrate's ubiquitination. Although many RING-type E3s, such as MDM2 (murine double minute clone 2 oncoprotein) and c-Cbl, can apparently act alone, others are found as components of much larger multi-protein complexes, such as the anaphase-promoting complex. Taken together, these multifaceted properties and interactions enable E3s to provide a powerful, and specific, mechanism for protein clearance within all cells of eukaryotic organisms. The importance of E3s is highlighted by the number of normal cellular processes they regulate, and the number of diseases associated with their loss of function or inappropriate targeting.


2019 ◽  
Vol 47 (6) ◽  
pp. 1733-1747 ◽  
Author(s):  
Christina Klausen ◽  
Fabian Kaiser ◽  
Birthe Stüven ◽  
Jan N. Hansen ◽  
Dagmar Wachten

The second messenger 3′,5′-cyclic nucleoside adenosine monophosphate (cAMP) plays a key role in signal transduction across prokaryotes and eukaryotes. Cyclic AMP signaling is compartmentalized into microdomains to fulfil specific functions. To define the function of cAMP within these microdomains, signaling needs to be analyzed with spatio-temporal precision. To this end, optogenetic approaches and genetically encoded fluorescent biosensors are particularly well suited. Synthesis and hydrolysis of cAMP can be directly manipulated by photoactivated adenylyl cyclases (PACs) and light-regulated phosphodiesterases (PDEs), respectively. In addition, many biosensors have been designed to spatially and temporarily resolve cAMP dynamics in the cell. This review provides an overview about optogenetic tools and biosensors to shed light on the subcellular organization of cAMP signaling.


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