Voltage propagation method for 3-D power grid analysis

Due to the rapid advances of integrated circuit technology, the size of power distribution network (power grid) is becoming larger and larger. There are usually multi-million nodes on a power grid. Analyzing these huge power grids has become very expensive in terms of both time and memory. This paper presents an efficient parallel implementation of the Additive Schwarz Method (ASM) for IR-drop analysis of large-scale power grid. Based on distributed memory system, a new data storage method is proposed to overcome memory bottleneck of traditional methods. Techniques including overlapping in multiple layer and irregular power grid, via detection and grouping are utilized to accelerate the simulation. Moreover, a new communication strategy exhibiting minimum communication overhead is proposed. The proposed method is very accurate in the final solution, with the maximum error less than 0.1mv. Experimental results on industrial medium size benchmarks show that the proposed method achieves more than 110X speedup over a state-of-the-art direct LU solver. The proposed approach can easily solve very large-scale benchmarks, while LU solver fails to obtain the solution because of system memory limitation. It is the first time reported in literature that IR-drop analysis of power grid with over 190M nodes is successfully solved within 5 minutes.

Analyzing the inertia of power grid systems comprising diverse conventional and renewable energy sources

Electric power has become an essential part of daily life: we plug our electronic devices in, switch our lights on, and expect to have power. As the availability of power is usually taken for granted in modern societies, we mostly feel annoyed at its absence and perceive the importance of power during outages which have severe effects on the public order. Blackouts have had disastrous consequences for many countries and they continue to occur frequently. Such examples demonstrate the necessity for careful analysis and planning of power grids, to ultimately increase the reliability of power grids. The power grids have evolved due to economic, environmental and human-caused factors. In addition to the contingency analysis, nowadays, the operation and planning of power grids are facing many other challenges (such as demand growth, targeted attacks, cascading failures, and renewable energy integration). Thus, many questions arise, including: which buses (nodes) to connect with a new line (link)? What are the impacts of malicious attacks on power grids? How may an initial failure result in a cascade of failures? How to prepare for the integration of renewable energy? Answering such questions requires developing new concepts and tools for analysing and planning of power grids. Power grids are one of the largest and the most complex man-made systems on earth. The complex nature of power grids and its underlying structure make it possible to analyse power grids relying on network science. The applications of network science on power grids have shown the promising potential to capture the interdependencies between components and to understand the collective emergent behaviour of complex power grids. This thesis is motivated by the increasing need of reliable power grids and the merits of network science on the investigation of power grids. In this context, relying on network science, we model and analyse the power grid and its near-future challenges in terms of line removals/additions, malicious attacks, cascading failures, and renewable integration.

With the development of power electronic devices, the research of Flexible AC Transmission System (FACTS) in regulating line power flow and improving static voltage stability is more in-depth. This paper discusses the static voltage stability of power grid with new energy taking into account the distributed static series compensator (DSSC), and evaluates the power flow control efficiency of DSSC from the aspect of system static voltage stability. First, the equivalent circuit and working principle of DSSC are analyzed, and the power flow equations are obtained based on the equivalent power injection model of DSSC; Secondly, based on the power flow calculation equation, the efficiency evaluation index that can reflect the static voltage stability of the system is proposed, and the impact of new energy with different capacities on the static voltage stability is calculated and analyzed; Finally, the proposed method is verified by the simulation analysis of IEEE-24 bus system and actual power grid: the proposed method is fast and simple, and has certain engineering application value.

Iterative linear equation solvers depend on high quality preconditioners to achieve fast convergence. For sparse symmetric systems arising from large power grid analysis problems, however, preconditioners generated by traditional incomplete Cholesky factorizations are usually of low quality, resulting in slow convergence. On the other hand, although preconditioners generated by random walks are quite effective to reduce the number of iterations, it takes considerable amount of time to compute them in a stochastic manner. In this paper, we propose a new preconditioning technique for power grid analysis, named deterministic random walk, that combines the advantages of the above two approaches. Our proposed algorithm computes the preconditioners in a deterministic manner to reduce computation time, while achieving similar quality as stochastic random walk preconditioning by modifying fill-ins to compensate dropped entries. We have proved that for such compensation scheme, our algorithm will not fail for certain matrix orderings, which otherwise cannot be guaranteed by traditional incomplete factorizations. We demonstrate that by incorporating our proposed preconditioner, a conjugate gradient solver is able to outperform a state-of-the-art algebraic multigrid preconditioned solver on public IBM power grid benchmarks for DC power grid analysis, while potentially remaining very efficient for transient analysis.

As VLSI techniques are getting more and more advanced, the size of the power grid network increases dramatically. Therefore, the power grid analysis becomes a challenging task during the design procedure. This work utilizes the macromodeling technique [1] and enhances the Orthogonal Matching Pursuit (OMP) based method [2] to develop an effective and robust incremental analysis method for the power grid network, MA-OMP <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sup> . Given a power grid network, MA-OMP <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sup> not only can deal with the change of its element values but also can handle the modification of its topology. The experimental results show that MA-OMP <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sup> can be an order of magnitude faster than the OMP-based method [2] which can only deal with the change of element values of the power grid. The experimental results also demonstrate that MA-OMP <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sup> can accurately and efficiently handle the modified topology of the power grid network.

A new unequal-weighted sampling method for efficient reliability analysis

The global power grid is undergoing a major transformation as a result of the growing utilization of renewable energy sources (RESs). The incorporation of these RESs is leading to a decline in the use of conventional synchronous generators and an increase in the use of inverter-based RESs. This shift is causing a decrease in the grid's inertia, presenting substantial difficulties for grid operators to maintain frequency stability. The purpose of this study is to examine the impact of declining inertia on the frequency behavior of the grid, as RESs become more prevalent. In order to measure the impact, this study utilizes eigenvalue analysis of power grids to assess the sensitivity of grid frequency and rate of change of frequency (RoCoF) characteristics, as well as the lowest frequency, to variations in grid inertia resulting from changes in RES penetration. Moreover, we have introduced indices that quantify the impact of RES penetration on the grid frequency behaviour in comparison to a grid without RES. To showcase the proposed approach, this research presents case studies using the modified IEEE 39 bus test system, which demonstrate the ability to assess the impact of a high RESs penetration on grid frequency characteristics.

As the increasing size of power grids, IR drop analysis has become more computationally challenging both in runtime and memory consumption. In this paper, we propose a linear complexity simulator named PowerRush, which consists of an efficient SPICE Parser, a robust circuit Builder and a linear solver. The proposed solver is a pure algebraic method which can provide an optimal convergence without geometric information. It is implemented by Algebraic Multigrid Preconditioned Conjugate Gradient method, in which an aggregation based algebraic multigrid with K-Cycle acceleration is adopted as a preconditioner to improve the robustness of conjugate gradient iterative method. In multigrid scheme, double pairwise aggregation technique is applied to the matrix graph in coarsening procedure to ensure low setup cost and memory requirement. Further, a K-Cycle multigrid scheme is adopted to provide Krylov subspace acceleration at each level to guarantee optimal or near optimal convergence. Experimental results on real power grids have shown that PowerRush has a linear complexity in runtime cost and memory consumption. The DC analysis of a 60 Million nodes power grid can be solved by PowerRush for 0.01mV accuracy in 170 seconds with 21.89GB memory used.

The recent developments in electric vehicles (EVs) causes several issues that have not been satisfactorily addressed. One of the foremost problems is the charging–discharging processes of EV batteries with diverse characteristics. Although a charging station is the first choice in this regard, a battery swap station (BSS) is also a suitable alternative solution as it eliminates long waiting periods and battery degradation due to fast charging. BSS has the capability to ensure prompt and efficient service for electric vehicles. Since BSS has a large number of battery systems, optimum planning of the charging–discharging operations of the batteries is critical for both BSS and the grid. This study presents an optimal charging–discharging schedule for multiple BSSs based on the swap demand of privately owned EVs and electric bus (EB) public transportation system. In addition, BSSs reinforce the power grid by providing ancillary services such as peak shaving and valley filling with demand response programs. In order to increase the flexibility of the operation, the mobile swapping station (MSS) concept, an innovative and dynamic service, is introduced to the literature and added to the model. The results indicate that BSS is an essential agent in the ancillary services market and the MSS concept is a yielding solution for both BSSs and power networks. Last, the data utilized in the study for swap demand calculation and power grid analysis are real-world data from Berlin, Germany.

Over the last decade, the Common Information Model (CIM), as specified by IEC 61970 / 61968, has become an important document format for the storage of power grid data. Its object-oriented design makes it easily maintainable and extensible for many use cases in the energy sector. As a result, more and more power grid analysis and simulation tools allow the import and export of CIM based power grid data. Unfortunately, many of them are proprietary and therefore not convenient in the research area since their component models and numerical back-ends often cannot be modified by the user. Thus, open-source alternatives are in demand, such as simulation environments based on the popular modeling language Modelica. Therefore, this paper presents our approach of a template based CIM to Modelica converter. The usage of templates makes it easily adaptable for the generation of Modelica system models targeting arbitrary Modelica libraries. The presented approach is implemented in an open-source project called CIMverter, evaluated on a real-world case with two Modelica power system libraries, and validated against a proprietary simulation tool.

There is a big difference between transmission line state estimation results and actual measured values, which seriously affects the normal operation of power grid analysis and other links. As a kind of static basic data, the accuracy of transmission line parameters affects the result of state estimation. Power system state estimation is the basis of dispatch automation application functions. State estimation can not only provide more credible basic data for power grid analysis, but also the difference between state estimation results and actual measured values can reflect the quality of basic power grid data. In order to solve the low state estimation accuracy of the short-distance non-transposition double-circuit transmission line on the same tower with the power plant directly connected to the grid, simulate line and grid operation through PSCAD, phase split modeling of the line, calculate line parameters, analyze the influence of the self-inductance and mutual inductance of lines under different phase sequence arrangements and the reasons for the lower accuracy of the line reactive power.KeywordsDouble-circuit transmission lines on the same towerState estimationPSCAD simulation

The study of static voltage stability is actually based on asymptotic stability, which is affected by the operation state of the power grid. In this paper, the voltage stability margin index is deduced, and the stability margin of the existing power grid under different actual working conditions is analyzed based on the proposed index. the leading factors and the worst system conditions are determined by practical experience. The correctness of the proposed method is verified by the simulation analysis of the actual provincial power grid.

Yield has always been a driving consideration during fabrication of modern semiconductor industry. Statistically, the largest portion of wafer yield loss is defective scan failure. This paper presents efficient failure analysis methods for initial yield ramp up and ongoing product with scan diagnosis. Result of our analysis shows that more than 60% of the scan failure dies fall into the category of shift mode in the very deep submicron (VDSM) devices. However, localization of scan shift mode failure is very difficult in comparison to capture mode failure because it is caused by the malfunction of scan chain. Addressing the biggest challenge, we propose the most suitable analysis method according to scan failure mode (capture / shift) for yield enhancement. In the event of capture failure mode, this paper describes the method that integrates scan diagnosis flow and backside probing technology to obtain more accurate candidates. We also describe several unique techniques, such as bulk back-grinding solution, efficient backside probing and signal analysis method. Lastly, we introduce blocked chain analysis algorithm for efficient analysis of shift failure mode. In this paper, we contribute to enhancement of the yield as a result of the combination of two methods. We confirm the failure candidates with physical failure analysis (PFA) method. The direct feedback of the defective visualization is useful to mass-produce devices in a shorter time. The experimental data on mass products show that our method produces average reduction by 13.7% in defective SCAN & SRAM-BIST failure rates and by 18.2% in wafer yield rates.

An efficient contingency evaluation method for power system security analysis