An Architecture of a Multi-Agent System for SCADA - Dealing With Uncertainty, Plans and Actions

This paper presents a multi-agent system approach to address the difficulties encountered in traditional SCADA systems deployed in critical environments such as electrical power generation, transmission and distribution. The approach models uncertainty and combines multiple sources of uncertain information to deliver robust plan selection. We examine the approach in the context of a simplified power supply/demand scenario using a residential grid connected solar system and consider the challenges of modelling and reasoning with
uncertain sensor information in this environment. We discuss examples of plans and actions required for sensing, establish and discuss the effect of uncertainty on such systems and investigate different uncertainty theories and how they can fuse uncertain information from multiple sources for effective decision making in
such a complex system.

Investigation into the effect of molybdenum-site substitution on the performance of Sr2Fe1.5Mo0.5O6-δ for intermediate temperature solid oxide fuel cells

In this paper, niobium doping is evaluated as a means of enhancing the electrochemical performance of a Sr₂Fe_1.5Mo_0.5O_6-δ (SFM) perovskite structure cathode material for intermediate temperature solid oxide fuel cells (IT-SOFCs) applications. As the radius of Nb approximates that of Mo and exhibits +4/+5 mixed valences, its substitution is expected to improve material performance. A series of Sr₂Fe_1.5Mo_0.5-xNb_xO_6-δ (x = 0.05, 0.10, 0.15, 0.20) cathode materials are prepared and the phase structure, chemical compatibility, microstructure, electrical conductivity, polarization resistance and power generation are systematically characterized. Among the series of samples, Sr₂Fe_1.5Mo_0.4Nb_0.10O_6-δ (SFMNb_0.10) exhibits the highest conductivity value of 30 S cm^-1 at 550°C, and the lowest area specific resistance of 0.068 Ω cm² at 800°C. Furthermore, an anode-supported single cell incorporating a SFMNb_0.10 cathode presents a maximum power density of 1102 mW cm^-2 at 800°C. Furthermore no obvious performance degradation is observed over 15 h at 750°C with wet H₂(3% H₂O) as fuel and ambient air as the oxidant. These results demonstrate that SFMNb shows great promise as a novel cathode material for IT-SOFCs.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Electrical energy storage and Smart Grid technologies to integrate the next generation of Renewable Power Systems

The growth of renewable power sources, distributed generation and the potential for alternative fuelled modes of transport such as electric vehicles has led to concerns over the ability of existing grid systems to facilitate such diverse portfolio mixes in already congested power systems. Internationally the growth in renewable energy sources is driven by government policy targets associated with the uncertainties of fossil fuel supplies, environmental issues and a move towards energy independence. Power grids were traditionally designed as vertically integrated centrally managed entities with fully dispatchable generating plant. Renewable power sources, distributed generation and alternative fuelled vehicles will place these power systems under additional stresses and strains due to their different operational characteristics. Energy storage and smart grid technologies are widely proposed as the tools to integrate these future diverse portfolio mixes within the more conventional power systems. The choice in these technologies is determined not only by their location on the grid system, but by the diversification in the power portfolio mix, the electricity market and the operational demands. This paper presents a high level technical and economic overview of the role and relevance of electrical energy storage and smart grid technologies in the next generation of renewable power systems.

Impact of Wind Generation Mix on Transient Stability for an Interconnected Power System

The rapid growth of wind generation in many European countries is pushing power systems into
uncharted territory. As additional wind generators are installed, the changing generation mix may
impact on power system stability. This paper adopts the New England 39 bus system as a test
system for transient stability analysis. Thermal generator models are based on a likely future plant
mix for existing systems, while varying capacities of fixed-speed induction generators (FSIG) and
doubly-fed induction generators (DFIG) are considered. The main emphasis here has been placed
on the impact of wind technology mix on inter-area oscillations following transient grid
disturbances. In addition, both rotor angle stability and transient voltage stability are examined, and
results are compared with current grid code requirements and standards. Results have shown that
FSIGs can reduce tie-line oscillations and improve damping following a transient disturbance, but
they also cause voltage stability and rotor angle stability problems at high wind penetrations. In
contrast, DFIGs can improve both voltage and rotor angle stability, but their power output
noticeably oscillates during disturbances.

Small Signal Stability Performance of Power System during High Penetration of Wind Generation

The small signal stability of interconnected power systems is one of the important aspects that need to be investigated since the oscillations caused by this kind of instability have caused many incidents. With the increasing penetration of wind power in the power system, particularly doubly fed induction generator (DFIG), the impact on the power system small signal stability performance should be fully investigated. Because the DFIG wind turbine integration is through a fast action converter and associated control, it does not inherently participate in the electromechanical small signal oscillation. However, it influences the small signal stability by impacting active power flow paths in the network and replacing synchronous generators that have power system stabilizer (PSS). In this paper, the IEEE 39 bus test system has been used in the analysis. Furthermore, four study cases and several operation scenarios have been conducted and analysed. The selective eigenvalue Arnoldi/lanczos's method is used to obtain the system eigenvalue in the range of frequency from 0.2 Hz to 2 Hz which is related to electromechanical oscillations. Results show that the integration of DFIG wind turbines in a system during several study cases and operation scenarios give different influence on small signal stability performance.

Complete control of high-harmonic generation for high average power applications

We present a new dual-gas multi-jet HHG source which can be perfectly controlled via phasematching of the long and short trajectory contributions and is applicable for high average power driver laser systems. © 2011 Optical Society of America.