Siddhartha Kumar Khaitan

Design Techniques and Applications of Cyberphysical Systems: A Survey

Cyberphysical systems (CPSs) are new class of engineered systems that offer close interaction between cyber and physical components. The field of CPS has been identified as a key area of research, and CPSs are expected to play a major role in the design and development of future systems. In this paper, we survey recent advancements made in the development and applications of CPSs. We classify the existing research work based on their characteristics and identify the future challenges. We also discuss the examples of prototypes of CPSs. The aim of this survey is to enable researchers and system designers to get insights into the working and applications of CPSs and motivate them to propose novel solutions for making wide-scale adoption of CPS a tangible reality.

Multifrontal Solver for Online Power System Time-Domain Simulation

This paper proposes the application of unsymmetric multifrontal method to solve the differential algebraic equations (DAE) encountered in the power system dynamic simulation. The proposed method achieves great computational efficiency as compared to the conventional Gaussian elimination methods and other linear sparse solvers due to the inherent parallel hierarchy present in the multifrontal methods. Multifrontal methods transform or reorganize the task of factorizing a large sparse matrix into a sequence of partial factorization of smaller dense frontal matrices which utilize the efficient Basic linear algebra subprograms 3 (BLAS 3) for dense matrix kernels. The proposed method is compared with the full Gaussian elimination methods and other direct sparse solvers on test systems and the results are reported.

A Class of New Preconditioners for Linear Solvers Used in Power System Time-Domain Simulation

In this paper, a new class of preconditioners for iterative methods is proposed for the solution of linear equations that arise in the time-domain simulation of the power system. The system of linear equations results from an attempt to solve the differential algebraic equations (DAE) encountered in the power system dynamic simulation. The preconditioners are based on the multifrontal direct methods. The proposed method is compared to the incomplete LU factorization (ILU) based preconditioned iterative methods and other conventional direct linear sparse solvers. The comparison shows the proposed method achieves great computational efficiency relative to these other methods.

Cyber physical system approach for design of power grids: A survey

Cyber physical systems (CPSs) refer to the class of systems which offer close integration of computation, networking, and physical processes. CPS approach to system design has been conventionally used in several domains, such as smart homes and health-care systems, however, its use in the design of power systems is relatively new. The unique features of CPSs are expected to greatly benefit the smart power grids of tomorrow. In this paper, we review several recent advancements made in the field of CPS approach in design and operation of power grids. We also discuss the application of CPSs in other domains to gain insights into the techniques and design approaches which could also be beneficial for power systems. We present a classification of research work and identify the challenges in wide-scale adoption of CPSs. This survey is intended to enable the researchers and power system operators to get insights into working of CPSs and understand their potential in transforming the future power grids.

A new heuristic for multiple sequence alignment

Multiple sequence alignment is an important task in bioinformatics which forms the basis of many other tasks like protein structure prediction, protein function prediction and phylogenetic analysis. An optimal multiple sequence alignment for a given set of sequences is difficult to determine by standard dynamic programming algorithms because of impractically high computational complexity. Therefore, heuristics are commonly used to reduce the alignment construction time, even though the resulting alignment may not be optimal. ClustalW is one of the most popular progressive multiple sequence alignment algorithm where the pairwise sequence alignments are done according to a static guide-tree based on the sequences alone. For a multiple sequence alignment of N sequences, each of length O(n), the ClustalW algorithm takes O(N2n2) time. In this paper, a modification to the algorithm is proposed which reduces the time complexity of the algorithm to O(N log2 Nn2). The proposed heuristic also makes the alignment process more dynamic as the order of sequences added to the multiple sequence alignment also depends on the already computed multiple sequence alignments.

High Performance Computing for Power System Dynamic Simulation

High-speed extended term (HSET) time domain simulation (TDS) is intended to provide very fast computational capability to predict extendedterm dynamic system response to disturbances and identify corrective actions. The extended-term dynamic simulation of a power system is valuable because it provides ability for the rigorous evaluation and analysis of outages which may include cascading. It is important for secure power grid expansion, enhances power system security and reliability, both under normal and abnormal conditions. In this chapter the design of the envisioned future dynamic security assessment processing system (DSAPS) is presented where HSETTDS forms the core module. The power system is mathematically represented by a system of differential and algebraic equations (DAEs). These DAEs arise out of the modeling of the dynamic components such as generators, exciters, governors, automatic generation control, load tap changers, induction motors, network modeling and so on. To provide very fast computational capability within the HSET-TDS, this chapter motivates the need for high performance computing (HPC) for power system dynamic simulations through detailed modeling of power system components and efficient numerical algorithms to solve the resulting DAEs. The developed HSET-TDS is first validated for accuracy against commercial power simulators (PSSE, DSA Tools, Power- World) and then it is compared for computational efficiency. The chapter investigates some of the promising direct sparse linear solver for fast extended term time domain simulation and makes recommendation for the modern power grid computations. The results provide very important insights with regards to the impact of the different numerical linear solver algorithms for enhancing the power system TDS.

High performance computing in power and energy systems

From the contents: High Performance Computing in Electrical Energy Systems Applications.- High Performance Computing for Power System Dynamic Simulation.- Distributed Parallel Power System Simulation.- A MAS-Based Cluster Computing Platform for Modern EMS.- High-Performance Computing for Real-Time Grid Analysis and Operation.- Dynamic Load Balancing and Scheduling for Parallel Power System Dynamic Contingency Analysis.

Fast parallelized algorithms for on-line extended-term dynamic cascading analysis

Very fast on-line computational capability to predict mid-term dynamic system response to disturbances and identify corrective actions is an important attribute of high-speed extended term (HSET) time domain simulation (TDS). Focusing on the development of computational speed, this paper propose a parallel strategy intended for deployment on the super computer, Blue Gene/L, to simulate the power system dynamics, which can be described as a set of differential algebraic equations (DAEs). To deal with DAE stiffness problems and fully capture benefits of explicit and implicit integration methods, the partition algorithm called recursive projection method (RPM) is employed. Additionally, good load balancing for parallel computation is achieved using waveform relaxation method (WRM) to separate the stiff parts of DAE. Multi-frontal Massively Parallel sparse direct Solver (MUMPS) is utilized to solve the linear systems involved in the implicit methods. This paper reports on the design

Dynamic Load Balancing and Scheduling for Parallel Power System Dynamic Contingency Analysis

Power system simulations involving solution of thousands of stiff differential and algebraic equations (DAE) are extremely computationally intensive and yet crucial for grid security and reliability. Online simulation of minutes to hours for a large number of contingencies requires computational efficiency several orders of magnitude greater than what is todays state-of-the-art. We have developed an optimized simulator for single contingency analysis using efficient numerical algorithms implementation for solving DAE, and scaled it up for large-scale contingency analysis using MPI. A prototype parallel high speed extended term simulator (HSET) on in-house high performance computing (HPC) resources at Iowa State University (ISU) (namely Cystorm Supercomputer) is being developed. Since the simulation times across contingencies vary considerably, we have focused our efforts towards development of efficient scheduling algorithms through work stealing for maximal resource utilization and minimum overhead to perform faster than real time analysis. This chapter introduces a novel implementation of dynamic load balancing algorithm for dynamic contingency analysis. Results indicate potential for significant improvements over the state-of-the-art methods especially master-slave based load balancing typically used in power system community. Simulations of thousands of contingencies on a large real system were conducted and computational savings and scalability results are reported.

EmPower: An Efficient Load Balancing Approach for Massive Dynamic Contingency Analysis in Power Systems

Power system simulations involving solution of thousands of stiff differential and algebraic equations (DAE) are computationally intensive and yet crucial for grid security and reliability. Online simulations of a large number of contingencies require very high computational efficiency. Furthermore, since the simulation times across the contingencies vary considerably, dynamic load balancing of parallel contingency analysis (CA) is required to ensure maximum resource utilization. However, the state-of-the-art contingency analysis techniques fail to fulfill this requirement. In this paper, we present EmPower, an Efficient load balancing approach for massive dynamic contingency analysis in Power systems. For single contingency analysis, EmPower uses time domain simulations and incorporates efficient numerical algorithms for solving the DAE. Further, the contingency analysis approach is scaled for large scale contingency analysis using MPI based parallelization. For enabling an efficient, non-blocking implementation of work-stealing, multithreading is employed within each processor. Simulations of thousands of contingencies on a supercomputer have been performed and the results show the effectiveness of EmPower in providing good scalability and huge computational savings.