Alexander J. Flueck

Agent Based Restoration With Distributed Energy Storage Support in Smart Grids

The goal of this paper is to present a new and completely distributed algorithm for service restoration with distributed energy storage support following fault detection, location, and isolation. The distributed algorithm makes use of intelligent agents, which possess three key characteristics, namely autonomy, local view, and decentralization. The switch agents will detect, locate and isolate the fault, then restore the load. The distributed energy storage agent will support the system in grid-connected as well as islanded operation. Important restoration issues such as load priority restoration and islanding coordination of multiple distributed energy storage systems will be discussed. Two case studies on the modified IEEE 34 node test feeder will be presented.

A message-passing distributed-memory parallel power flow algorithm

This paper presents a parallel direct linear solver based on a message-passing distributed-memory multiprocessor architecture such as a cluster of workstations. The results show that the new algorithm can achieve nearly linear speedup for two large-scale power system cases on a small cluster of GNU/Linux dual-processor workstations. The workstations are connected via 100 Mbit/s Ethernet, i.e., the parallel machine consists of hardware readily found in any engineering department. Based on the presented parallel direct linear solver, it is possible to parallelize totally the Newton power flow solution process. In addition, the METIS-based partitioning scheme can handle common control devices such as PV-PQ switching. Furthermore, by tuning the vertex and branch weights, the performance of the power flow solution can be optimized for the available hardware. For a workstation cluster on 100 Mbit/s Ethernet, the speedup appears to saturate beyond eight processors due to load imbalance and the aggregate growth of the partition separators. Nevertheless, the message-passing distributed-memory multiprocessor architecture can be used in other power system applications, such as state estimation and transient stability. Furthermore, an iterative linear solver could improve scalability.

Modeling of communication latency in smart grid

The goal of this paper is to model the communication latency among distributed intelligent agents because latency 1) is not zero, 2) is not constant, and 3) can have a significant impact on the higher-level capabilities of a smart grid installation, in particular any protection or coordination functions. Communication latency is considered an inherent parameter which affects the performance of the communication network — the backbone of the multi-agent system. Due to many stochastic factors in a communication environment, communication latency will be best modeled as a random parameter with a probability density function. The latency of sending/receiving messages among distributed intelligent agents is randomly generated based on user input data. In the numerical studies, two abnormal events occurring in the modified IEEE 34 node test feeder will be simulated to validate the proposed methodology. The simulation will measure how fast the smart grid responds to the disturbances when considering fixed latency, as well as random latency.

Agent-Based Distributed Volt/Var Control With Distributed Power Flow Solver in Smart Grid

In this paper, a new and completely distributed algorithm for integrated volt/var control is presented. The algorithm is based on a multiagent system, which provides distributed intelligence to smart grid. The voltage regulator and shunt capacitor controlled by intelligent agents collaborate to determine the optimal setting for the entire system. The optimization objectives include maintaining the system voltage profile within a specified range, minimizing system loss, and reducing the switching of shunt capacitors. To achieve these objectives, an updated agent-based distributed power flow solver is used. The proposed algorithm is validated through the modified IEEE 34 node test feeder.

A Novel Agent-Based Distributed Power Flow Solver for Smart Grids

The goal of this paper is to present a novel agent based distributed power flow solver for general unbalanced radial distribution systems utilizing multiagent system communication. The distributed solver makes use of intelligent agents, which possess three key characteristics, namely autonomy, local view, and decentralization. Comprehensive models of distribution systems will be considered, including lines, switching devices, voltage regulators, transformers, shunt capacitors, distributed energy storage systems, and different load types. The distributed intelligent agents will use the backward/forward sweep technique to iteratively solve the power flow. A distinguishing feature of the new solver is that it deals with the problem from a completely distributed perspective. The proposed solution algorithm is evaluated on three standard IEEE distribution test systems with very promising results.

Integrating Renewable and Distributed resources - IIT Perfect Power Smart Grid Prototype

The goal of this paper is to provide a brief overview of the Perfect Power Smart Grid Prototype at Illinois Institute of Technology, while highlighting some of the multi-agent system applications. The Perfect Power Prototype is supported by the Department of Energy under the Renewable and Distributed Systems Integration Program, which focuses on effectively integrating distributed resources (including distributed generation technologies, renewable generation technologies, energy storage devices, and demand response methods) for decreased peaking power demand on the grid and for providing necessary ancillary services. The IIT Perfect Power Prototype plans to accomplish the above integration tasks via autonomous multi-agent systems.

Using PETSc to develop scalable applications for next-generation power grid

Developing scalable software for existing and emerging power system problems is a challenging task and requires considerable time and effort. This effort can be reduced by using high performance software libraries, such as PETSc, which are tested on a gamut of scientific applications, used on single-core machines to supercomputers, have highly optimized implementations, and a wide array of tested numerical solvers. High performance libraries have not yet been used by the power system community for developing power system applications, but such libraries have been well ex- plored by researchers doing PDE simulations. This paper introduces the high performance library PETSc and motivates using such high performance libraries for developing existing and future power system applications.

Power System Real-Time Event Detection and Associated Data Archival Reduction Based on Synchrophasors

The aim of this paper is to present methods on real-time event detection and data archival reduction based on synchrophasor data produced by phasor measurement unit (PMU). Event detection is performed with principal component analysis and a second order difference method with a hierarchical framework for the event notification strategy on a small-scale microgrid. Compared with the existing methods, the proposed method is more practical and efficient in the combined use of event detection and data archival reduction. The proposed method on data reduction, which is an “event oriented auto-adjustable sliding window method,” implements a curve fitting algorithm with a weighted exponential function-based variable sliding window accommodating different event types. It works efficiently with minimal loss in data information especially around detected events. The performance of the proposed method is shown on actual PMU data from the Illinois Institute of Technology campus microgrid, thus successfully improving the situational awareness of the campus power system network.

An implicitly-coupled solution approach for combined electromechanical and electromagnetic transients simulation

This paper presents a novel implicitly-coupled solution approach for the combined electromechanical and electromagnetic transients simulation. Unlike the existing hybrid simulators that use an explicit approach to interface separate transient stability (TS) and electromagnetic transients (EMT) programs, the authors propose combining the equations of the two simulators and solving them simultaneously by an implicit approach. To combine the two sets of equations with their different time steps, and ensure that the TS and EMT solutions are consistent, the equations for TS and coupled-in-time EMT equations are solved simultaneously, referred to as TSEMT simulation. The simulation results for the proposed implicitly-coupled solution approach on the WECC 9-bus system are discussed. Along with the implicitly-coupled solution approach, a novel strategy, referred to as TS3ph-TSEMT, based on difference between the phasor boundary bus voltages of the detailed and external systems is also proposed to terminate the implicitly-coupled TSEMT simulation and continue with only the TS simulation. The computational efficiency of the proposed TS3ph-TSEMT approach is presented for the 9-bus and 118-bus systems.

Real-Time Power System Dynamics Simulation Using a Parallel Block-Jacobi Preconditioned Newton-GMRES Scheme

Real-time dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations. The main bottleneck in these simulations is the solution of the linear system during each nonlinear iteration of Newtons method. We present a parallel linear solution scheme using the Krylov subspace-based iterative solver GMRES with a BlockJacobi preconditioner. The scheme shows promise for real-time dynamics simulation, with a good speed up for a 2383-bus, 327-generator test case. Results obtained for both stable and unstable operating conditions show that real-time simulation speed can be realized by using the proposed parallel linear solution scheme.