Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

Hardware Performance Analysis of the SHACAL-2 Encryption Algorithm

A hardware performance analysis of the SHACAL-2 encryption algorithm is presented in this paper. SHACAL-2 was one of four symmetric key algorithms chosen in the New European Schemes for Signatures, Integrity and Encryption (NESSIE) initiative in 2003. The paper describes a fully pipelined encryption SHACAL-2 architecture implemented on a Xilinx Field Programmable Gate Array (FPGA) device that achieves a throughput of over 25 Gbps. This is the fastest private key encryption algorithm architecture currently available. The SHACAL-2 decryption algorithm is also defined in the paper as it was not provided in the NESSIE submission.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Feasibility of online collaborative voltage stability control of power systems

This paper presents the results of feasibility study of a novel concept of power system on-line collaborative voltage stability control. The proposal of the on-line collaboration between power system controllers is to enhance their overall performance and efficiency to cope with the increasing operational uncertainty of modern power systems. In the paper, the framework of proposed on-line collaborative voltage stability control is firstly presented, which is based on the deployment of multi-agent systems and real-time communication for on-line collaborative control. Then two of the most important issues in implementing the proposed on-line collaborative voltage stability control are addressed: (1) Error-tolerant communication protocol for fast information exchange among multiple intelligent agents; (2) Deployment of multi-agent systems by using graph theory to implement power system post-emergency control. In the paper, the proposed on-line collaborative voltage stability control is tested in the example 10-machine 39-node New England power system. Results of feasibility study from simulation are given considering the low-probability power system cascading faults.

An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

Allocating transmission loss to loads and generators through complex power flow tracing

This paper presents a new method for complex power flow tracing that can be used for allocating the transmission loss to loads or generators. Two algorithms for upstream tracing (UST) and downstream tracing (DST) of the complex power are introduced. UST algorithm traces the complex power extracted by loads back to source nodes and assigns a fraction of the complex power flow through each line to each load. DST algorithm traces the output of the generators down to the sink nodes determining the contributions of each generator to the complex power flow and losses through each line. While doing so, active- and reactive-power flows as well as complex losses are considered simultaneously, not separately as most of the available methods do. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses are carried out using an equation, which has a physical basis, and considers the coupling between active- and reactive-power flows as well as the cross effects of active and reactive powers on active and reactive losses. The tracing algorithms introduced can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

A method for determining generators’ shares in loads, line flows and losses

This paper presents a new method for calculating the individual generators’ shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows. Starting from a power flow solution, the line flow matrix is formed. This matrix is used for identifying node types, tracing the power flow from generators downstream to loads, and to determine generators’ participation factors to lines and loads. Neither exhaustive search nor matrix inversion is required. Hence, the method is claimed to be the least computationally demanding amongst all of the similar methods.