Network Reduction Algorithm Research Articles

Switching Device-Cognizant Sequential Distribution System Restoration

This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compared to existing studies, this paper considers types, capabilities and operational limits of different switching devices, making it applicable in practice. We develop a novel multi-phase method to find the optimal sequential operation of various switching devices and repair faulted areas. We consider circuit breakers, reclosers, sectionalizers, load breaker switches, and fuses. The switching operation problem is decomposed into two mixed-integer linear programming (MILP) subproblems. The first subproblem determines the optimal network topology and estimates the number of steps to reach that topology, while the second subproblem generates a sequence of switching operations to coordinate the switches. For repairing the faults, we design an MILP model that dispatches repair crews to clear faults and replace melted fuses. After clearing a fault, we update the topology of the network by generating a new sequence of switching operations, and the process continues until all faults are cleared. To improve the computational efficiency, a network reduction algorithm is developed to group line sections, such that only switchable sections are present in the reduced network. The proposed method is validated on the IEEE 123-bus and 8500-bus systems.

High-Dimensional Extension of the TICER Algorithm

The TICER (TIme-Constant Equilibration Reduction) algorithm is a well-known resistor-capacitor (RC) network reduction algorithm. It finds wide applications in integrated circuit post-layout simulation tools. However, the original algorithm is one-dimensional in that each step eliminates one circuit node to obtain an approximately equivalent circuit by connecting additional elements to the neighboring nodes after each elimination. This work extends the TICER algorithm to its high-dimensional version in the sense that each step eliminates a subcircuit as a whole to obtain an approximately equivalent circuit, again by connecting extra elements to the neighboring nodes after each elimination. In practice the high-dimensional TICER (HD-TICER) algorithm finds many advantages over the classical one-dimensional TICER (1D-TICER) algorithm, which is a special case of the HD-TICER algorithm. An elegant mathematical derivation of the HD-TICER algorithm is provided by applying the notion of driving point impedance (DPI). The advantages of the HD-TICER algorithm are demonstrated by application to reductions of some purely resistive networks and RC networks. An approximate time constant estimation method is also provided for selection of a subblock circuit to eliminate.

Carbon Communities and Hotspots for Carbon Emissions Reduction in China

With China’s commitment to peak its emissions by 2030, sectoral emissions are under the spotlight due to the rolling out of the national emission trading scheme (ETS). However, the current sector policies focus either on the production side or consumption while the majority of sectors along the transmission were overlooked. This research combines input–output modelling and network analysis to track the embodied carbon emissions among thirty sectors of thirty provinces in China. Based on the large-data resolution network, a two-step network reduction algorithm is used to extract the backbone of the network. In addition, network centrality metrics and community detection algorithms are used to assess each individual sector’s roles, and to reveal the carbon communities where sectors have intensive emission links. The research results suggest that the sectors with high out-degree, in-degree or betweenness can act as leverage points for carbon emissions mitigation. In addition to the electricity sector, which is included in the national ETS, the study also found that the metallurgy and construction sectors should be prioritized for emissions reduction from national and local levels. However, the hotpots are different across provinces and thus provincial specific targeted policies should be formed. Moreover, there are nineteen carbon communities in China with different features, which provides direction for provincial governments’ external collaboration for synergistic effects.

Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism

Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.

Development of Shortest Path Searching Network Reduction Algorithm

This study developed searching network reduction algorithm for reduce shortest path searching time. Developed algorithm is searching nodes that have the including possibility of less weights path than temporal path that consists minimum number of nodes and minimum sum of the straight line distances. The node that has the including possibility of shortest path is the node that the sum of straight line distance from start node and straight line distance to target node is less than the value that temporary path`s weights divided by minimum weights units. If searching network reconstitutes only these nodes, the time of shortest path searching will be reduced. This developed algorithm has much effectiveness that start node and target node is close in large network.

Development of Shortest Path Searching Network Reduction Algorithm

Development of Shortest Path Searching Network Reduction Algorithm

Electrical Network Reduction for Load Flow and Short-Circuit Calculations Using Power Factory Software

The primary purpose in constructing equivalents is to represent a portion of a network containing many but having only a few buses by a reduced network containing only the boundary and, perhaps, a few selected from within the original sub-network. The equivalent constructed gives an exact reproduction of the self and transfer impedances of the external system as seen from its boundary buses. PowerFactory’s network reduction algorithm produces an equivalent representation of the reduced part of the network and calculates its parameters. This equivalent re-presentation is valid for both load flow and short-circuit calculations, including asymmetrical faults (that is, single-phase faults).

Aggregation of Buses for a Network Reduction

A simple but precise model would improve the computation efficiency for planning a large-scale power system. Recent development of a new network reduction algorithm yields such a model with a given grouping of buses. While the flow over the reduced network is estimated precisely, a proper value of the flow limit still remains unresolved. In this study, a method is proposed to group buses based on the congestion profile in the original network and to assign the flow limits of a reduced network. The method is tested on modified IEEE 30-bus and 118-bus systems at various load profiles, and the simulation results are compared.

A rank correlation-based method for power network reduction

We present a coherency measure and a network reduction algorithm. The rank correlation function was used to determine the mutual couplings of generators. Generators were grouped at two correlation levels. These are grouping tolerances whose values are unique for a given system. The first produces the most strictly coupled generators to be aggregated, and the second identifies the generators to be saved during reduction. The terminals of the generators in each group were extended to include load buses to partition the network. Previously reported techniques were used to reduce generator and load buses.

Modeling of VLSI RC parasitics based on the network reduction algorithm

This paper presents a method of modeling of R and C parasitics in VLSI circuits. A network representation is generated for finite difference discretization of 2-D Laplace's equation, and a reduction algorithm is applied to this network. The solution area can be defined by any set of polygons. If n is the number of discretization nodes the new algorithm is O(n/sup 1.5/). It yields directly the coefficients of capacitance or admittance matrix. In contrast to other methods, in the network reduction approach, the time required for modeling depends mainly upon the complexity of the solution area but weakly upon the number of terminals. This feature is particularly valuable in application to circuit extraction.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A parasitics extraction and network reduction algorithm for analog VLSI

A transmission line model for the extraction of circuit parasitics in integrated circuits is presented. This model is shown to give a better account of the DC and aC characteristics of interconnects than models incorporating exclusively the R or C components. A network-reduction technique that is used to simplify the extracted RC network at user-specified accuracies to manageable complexities, especially for large VLSI circuits, is also discussed. The model and circuit reduction algorithms are applied to practical sample circuits and results of simulations illustrating the reduction in circuit complexity and the degree of modeling accuracy by these methods are given. >