Modeling and control of unified power flow controller for transient stability

FACTS controllers are emerging as viable and economic solutions to the problems of large interconnected ne networks, which can endanger the system security. These devices are characterized by their fast response, absence of inertia, and minimum maintenance requirements. Thyristor controlled equipment like Thyristor Controlled Series Capacitor (TCSC), Static Var Compensator (SVC), Thyristor Controlled Phase angle Regulator (TCPR) etc. which involve passive elements result in devices of large sizes with substantial cost and significant labour for installation. An all solid-state device using GTOs leads to reduction in equipment size and has improved performance. The Unified Power Flow Controller (UPFC) is a versatile controller which can be used to control the active and reactive power in the Line independently. The concept of UPFC makes it possible to handle practically all power flow control and transmission line compensation problems, using solid-state controllers, which provide functional flexibility, generally not attainable by conventional thyristor controlled systems. In this paper, we present the development of a control scheme for the series injected voltage of the UPFC to damp the power oscillations and improve transient stability in a power system. (C) 1998 Elsevier Science Ltd. All rights reserved.

Impact of Energy Expenditure Rate Constraints on the performance of Multihop Wireless Mesh Networks

In this article we study the problem of joint congestion control, routing and MAC layer scheduling in multi-hop wireless mesh network, where the nodes in the network are subjected to maximum energy expenditure rates. We model link contention in the wireless network using the contention graph and we model energy expenditure rate constraint of nodes using the energy expenditure rate matrix. We formulate the problem as an aggregate utility maximization problem and apply duality theory in order to decompose the problem into two sub-problems namely, network layer routing and congestion control problem and MAC layer scheduling problem. The source adjusts its rate based on the cost of the least cost path to the destination where the cost of the path includes not only the prices of the links in it but also the prices associated with the nodes on the path. The MAC layer scheduling of the links is carried out based on the prices of the links. We study the e�ects of energy expenditure rate constraints of the nodes on the optimal throughput of the network.

Modelling of Effect of Non-Uniform Current Density on the Performance of Soluble Lead Redox Flow Batteries

Soluble lead acid redox flow battery (SLRFB) offers a number of advantages. These advantages can be harnessed after problems associated with buildup of active material on. electrodes (residue) are resolved. A mathematical model is developed to understand residue formation in SLRFB. The model incorporates fluid flow, ion transport, electrode reactions, and non-uniform current distribution on electrode surfaces. A number of limiting cases are studied to conclude that ion transport and electrode reaction on anode simultaneously control battery performance. The model fits the reported cell voltage vs. time profiles very well. During the discharge cycle, the model predicts complete dissolution of deposited material from trailing edge side of the electrodes. With time, the active surface area of electrodes decreases rapidly. The corresponding increase in current density leads to precipitous decrease in cell potential before all the deposited material is dissolved. The successive charge-discharge cycles add to the residue. The model correctly captures the marginal effect of flow rate on cell voltage profiles, and identifies flow rate and flow direction as new variables for controlling residue buildup. Simulations carried out with alternating flow direction and a SLRFB with cylindrical electrodes show improved performance with respect to energy efficiency and residue buildup. (C) 2014 The Electrochemical Society. All rights reserved.

Enzymatically degradable EMI shielding materials derived from PCL based nanocomposites

In this study, two different types of multiwall carbon nanotubes (MWNTs) namely pristine (p-MWNTs) and amine functionalized (a-MWNTs) were melt-mixed with polycaprolactone (PCL) to develop biodegradable electromagnetic interference (EMI) shielding materials. The bulk electrical conductivity of the nanocomposites was assessed using broadband dielectric spectroscopy and the structural properties were evaluated using dynamic mechanical thermal analysis (DMTA). Both the electrical conductivity and the structural properties improved after the addition of MWNTs and were observed to be proportional to the increasing fractions in the nanocomposites. The shielding effectiveness of the nanocomposites was studied using a vector network analyzer (VNA) in a broad range of frequencies, X-band (8 to 12 GHz) and K-u-band (12 to 18 GHz) on toroidal samples. The shielding effectiveness significantly improved on addition of MWNTs, more in the case of p-MWNTs than in a-MWNTs. For instance, at a given fraction of MWNTs (3 wt%), PCL with p-MWNTs and a-MWNTs showed a shielding effectiveness of -32 dB and -29 dB, respectively. Moreover, it was observed that reflection was the primary mechanism of shielding at lower fractions of MWNTs, while absorption dominated at higher fractions in the composites. As one of the rationales of this work was to develop biodegradable EMI shielding materials to address the challenges concerning electronic waste, the effect of different MWNTs on the biodegradability of PCL composites was assessed through enzymatic degradation. The enzymatic degradation of the samples cut from the hot pressed films by bacterial lipase was investigated. It was noted that a-MWNTs exhibited almost similar degradation rate as the control PCL sample; however, p-MWNTs showed a slower degradation rate. This study demonstrates the potential use of PCL-MWNT composites as flexible, light weight and eco-friendly EMI shielding materials.

Flow behavior of LDPE and its blends with LLDPE I and II: A comparative study

Studies on melt rheological properties of blends of low density polyethylene (LDPE) with selected grades of linear low density polyethylene (LLDPE), which differ widely in their melt flow indices, are reported, The data obtained in a capillary rheometer are presented to describe the effects of blend composition and shear rate on flow behavior index, melt viscosity, and melt elasticity. In general, blending of LLDPE I that has a low melt flow index (2 g/10 min) with LDPE results in a decrease of its melt viscosity, processing temperature, and the tendency of extrudate distortion, depending on blending ratio. A blending ratio around 20-30% LLDPE I seems optimum from the point of view of desirable improvement in processability behavior. On the other hand, blending of LLDPE II that has a high melt flow index (10 g/10 min) with LDPE offers a distinct advantage in increasing the pseudoplasticity of LDPE/LLDPE II blends.

Hybrid structural control using magnetorheological dampers for base isolated structures

In this paper two nonlinear model based control algorithms have been developed to monitor the magnetorheological (MR) damper voltage. The main advantage of the proposed algorithms is that it is possible to directly monitor the voltage required to control the structural vibration considering the effect of the supplied and commanded voltage dynamics of the damper. The efficiency of the proposed techniques has been shown and compared taking an example of a base isolated three-storey building under a set of seismic excitations. Comparison of the performances with a fuzzy based intelligent control algorithm and a widely used clipped optimal strategy has also been shown.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Measurement of air leakage in air-handling units and air conditioning ducts

The purpose of this article is to report the experience of design and testing of orifice plate-based flow measuring systems for evaluation of air leakages in components of air conditioning systems. Two of the flow measuring stations were designed with a beta value of 0.405 and 0.418. The third was a dual path unit with orifice plates of beta value 0.613 and 0.525. The flow rates covered with all the four were from 4-94 l/s and the range of Reynolds numbers is from 5600 to 76,000. The coefficients of discharge were evaluated and compared with the Stolz equation. Measured C-d values are generally higher than those obtained from the equation, the deviations being larger in the low Reynolds number region. Further, it is observed that a second-degree polynomial is inadequate to relate the pressure drop and flow rate. The lower Reynolds number limits set by standards appear to be somewhat conservative.

Robustness Study of a Dynamic Inversion Control Law for a High Performance Aircraft

In the design of °ight control system modeling uncertainties in the form of param-eter variations is one of the major problems. It is even more critical for high performance aircrafts,since such aircrafts are purposefully designed unstable to enhance their performance (especially ma-neuverability). Hence the °ight control system needs to be quite e®ective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addi-tion, the control system must also be su±ciently robust to cater for possible parameter variations and inaccuracies . The primary aim of this paper is to carry out a robustness study of a dynamic inversion based nonlinear control design for a high performance aircraft, which has been developed recently [1].

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

An Actor-Critic Algorithm for Finite Horizon Markov Decision Processes

We develop a simulation based algorithm for finite horizon Markov decision processes with finite state and finite action space. Illustrative numerical experiments with the proposed algorithm are shown for problems in flow control of communication networks and capacity switching in semiconductor fabrication.

Distributed Simulation Of Flexible Manufacturing Systems

Flexible Manufacturing Systems (FMS), widely considered as the manufacturing technology of the future, are gaining increasing importance due to the immense advantages they provide in terms of cost, quality and productivity over the conventional manufacturing. An FMS is a complex interconnection of capital intensive resources and high levels of system performance is very crucial for survival in a competing environment.Discrete event simulation is one of the most popular methods for performance evaluation of FMS during planning, design and operation phases. Indeed fast simulators are suggested for selection of optimal strategies for flow control (which part type to enter and at what instant), AGV scheduling (which vehicle to carry which part), routing (which machine to process the part) and part selection (which part for processing next). In this paper we develop a C-net based model for an FMS and use the same for distributed discrete event simulation. We illustrate using examples the efficacy of destributed discrete event simulation for the performance evaluation of FMSs.

Proportional resonant controller based circulating power setup for thermal testing of multilevel inverter

A regenerative or circulating-power method is presented in this paper for heat run test on the legs of a three-level neutral point clamped (NPC) inverter. This test ensures that only losses are drawn from the dc supply, while rated power is circulated between the two legs, thus minimising wastage of energy. A proportional-resonant (PR) controller based current control scheme is proposed here for the circulating power test setup in NPC inverter. Simulation and experimental results are presented to validate the controller design at various operating conditions. Results of thermal test on the inverter legs are presented at two different operating conditions.

A general geomorphological recession flow model for river basins

Recession flows in a basin are controlled by the temporal evolution of its active drainage network (ADN). The geomorphological recession flow model (GRFM) assumes that both the rate of flow generation per unit ADN length (q) and the speed at which ADN heads move downstream (c) remain constant during a recession event. Thereby, it connects the power law exponent of -dQ/dt versus Q (discharge at the outlet at time t) curve, , with the structure of the drainage network, a fixed entity. In this study, we first reformulate the GRFM for Horton-Strahler networks and show that the geomorphic ((g)) is equal to D/(D-1), where D is the fractal dimension of the drainage network. We then propose a more general recession flow model by expressing both q and c as functions of Horton-Strahler stream order. We show that it is possible to have = (g) for a recession event even when q and c do not remain constant. The modified GRFM suggests that is controlled by the spatial distribution of subsurface storage within the basin. By analyzing streamflow data from 39 U.S. Geological Survey basins, we show that is having a power law relationship with recession curve peak, which indicates that the spatial distribution of subsurface storage varies across recession events. Key Points The GRFM is reformulated for Horton-Strahler networks. The GRFM is modified by allowing its parameters to vary along streams. Sub-surface storage distribution controls recession flow characteristics.