Evaluation and improvement of generators reactive power margins in interconnected power systems

The amount of reactive power margin available in a system determines its proximity to voltage instability under normal and emergency conditions. More the reactive power margin, better is the systems security and vice-versa. A hypothetical way of improving the reactive margin of a synchronous generator is to reduce the real power generation within its mega volt-ampere (MVA) ratings. This real power generation reduction will affect its power contract agreements entered in the electricity market. Owing to this, the benefit that the generator foregoes will have to be compensated by paying them some lost opportunity cost. The objective of this study is three fold. Firstly, the reactive power margins of the generators are evaluated. Secondly, they are improved using a reactive power optimization technique and optimally placed unified power flow controllers. Thirdly, the reactive power capacity exchanges along the tie-lines are evaluated under base case and improved conditions. A detailed analysis of all the reactive power sources and sinks scattered throughout the network is carried out in the study. Studies are carried out on a real life, three zone, 72-bus equivalent Indian southern grid considering normal and contingency conditions with base case operating point and optimised results presented.

Leak Detection In Pressure Tubes Of A Pressurized Heavy-Water Reactor By Acoustic-Emission Technique

Leak detection in the fuel channels is one of the challenging problems during the in-service inspection (ISI) of Pressurised Heavy Water Reactors (PHWRs). In this paper, the use of an acoustic emission (AE) technique together with AE signal analysis is described, to detect a leak that was ncountered in one (or more) of the 306 fuel channels of the Madras Atomic Power Station (PHWR), Unit I. The paper describes the problems encountered during the ISI, the experimental methods adopted and the results obtained. Results obtained using acoustic emission signal analysis are compared with those obtained from other leak detection methods used in such cases.

Starting scheme for load commutated inverter-fed wound field synchronous machine using an auxiliary low-power voltage source inverter

Conventional thyristor-based load commutated inverter (LCI)-fed wound field synchronous machine operates only above a minimum speed that is necessary to develop enough back emf to ensure commutation. The drive is started and brought up to a speed of around 10-15% by a complex `dc link current pulsing' technique. During this process, the drive have problems such as pulsating torque, insufficient average starting torque, longer starting time, etc. In this regard a simple starting and low-speed operation scheme, by employing an auxiliary low-power voltage source inverter (VSI) between the LCI and the machine terminals, is presented in this study. The drive is started and brought up to a low speed of around 15% using the VSI alone with field oriented control. The complete control is then smoothly and dynamically transferred to the conventional LCI control. After the control transfer, the VSI is turned off and physically disconnected from the main circuit. The advantages of this scheme are smooth starting, complete control of torque and flux at starting and low speeds, less starting time, stable operation, etc. The voltage rating of the required VSI is very low of the order of 10-15%, whereas the current rating is dependent on the starting torque requirement of the load. The experimental results from a 15.8 hp LCI-fed wound field synchronous machine are given to demonstrate the scheme.

Localisation of discrete change in a transformer winding: a network-function-loci approach

An entirely different approach for localisation of winding deformation based on terminal measurements is presented. Within the context of this study, winding deformation means, a discrete and specific change externally imposed at a particular position on the winding. The proposed method is based on pre-computing and plotting the complex network-function loci e.g. driving-point impedance (DPI)] at a selected frequency, for a meaningful range of values for each element (increasing and decreasing) of the ladder network which represents the winding. This loci diagram is called the nomogram. After introducing a discrete change, amplitude and phase of DPI are measured. By plotting this single measurement on the nomogram, it is possible to estimate the location and identify the extent of change. In contrast to the existing approach, the proposed method is fast, non-iterative and yields reasonably good localisation. Experimental results for actual transformer windings (interleaved and continuous disc) are presented.

A Convex Optimization Framework for Almost Budget Balanced Allocation of a Divisible Good

We address the problem of allocating a single divisible good to a number of agents. The agents have concave valuation functions parameterized by a scalar type. The agents report only the type. The goal is to find allocatively efficient, strategy proof, nearly budget balanced mechanisms within the Groves class. Near budget balance is attained by returning as much of the received payments as rebates to agents. Two performance criteria are of interest: the maximum ratio of budget surplus to efficient surplus, and the expected budget surplus, within the class of linear rebate functions. The goal is to minimize them. Assuming that the valuation functions are known, we show that both problems reduce to convex optimization problems, where the convex constraint sets are characterized by a continuum of half-plane constraints parameterized by the vector of reported types. We then propose a randomized relaxation of these problems by sampling constraints. The relaxed problem is a linear programming problem (LP). We then identify the number of samples needed for ``near-feasibility'' of the relaxed constraint set. Under some conditions on the valuation function, we show that value of the approximate LP is close to the optimal value. Simulation results show significant improvements of our proposed method over the Vickrey-Clarke-Groves (VCG) mechanism without rebates. In the special case of indivisible goods, the mechanisms in this paper fall back to those proposed by Moulin, by Guo and Conitzer, and by Gujar and Narahari, without any need for randomization. Extension of the proposed mechanisms to situations when the valuation functions are not known to the central planner are also discussed. Note to Practitioners-Our results will be useful in all resource allocation problems that involve gathering of information privately held by strategic users, where the utilities are any concave function of the allocations, and where the resource planner is not interested in maximizing revenue, but in efficient sharing of the resource. Such situations arise quite often in fair sharing of internet resources, fair sharing of funds across departments within the same parent organization, auctioning of public goods, etc. We study methods to achieve near budget balance by first collecting payments according to the celebrated VCG mechanism, and then returning as much of the collected money as rebates. Our focus on linear rebate functions allows for easy implementation. The resulting convex optimization problem is solved via relaxation to a randomized linear programming problem, for which several efficient solvers exist. This relaxation is enabled by constraint sampling. Keeping practitioners in mind, we identify the number of samples that assures a desired level of ``near-feasibility'' with the desired confidence level. Our methodology will occasionally require subsidy from outside the system. We however demonstrate via simulation that, if the mechanism is repeated several times over independent instances, then past surplus can support the subsidy requirements. We also extend our results to situations where the strategic users' utility functions are not known to the allocating entity, a common situation in the context of internet users and other problems.

Photo-Defined Electrically Assisted Etching Method for Metal Stencil Fabrication

Metal stencils are well known in electronics printing application such as for dispensing solder paste for surface mounting, printing embedded passive elements in multilayer structures, etc. For microprinting applications using stencils, the print quality depends on the smoothness of the stencil aperture and its dimensional accuracy, which in turn are invariably related to the method used to manufacture the stencils. In this paper, fabrication of metal stencils using a photo-defined electrically assisted etching method is described. Apertures in the stencil were made in neutral electrolyte using three different types of impressed current, namely, dc, pulsed dc, and periodic pulse reverse (PPR). Dimensional accuracy and wall smoothness of the etched apertures in each of the current waveforms were compared. Finally, paste transfer efficiency of the stencil obtained using PPR was calculated and compared with those of a laser-cut electropolished stencil. It is observed that the stencil fabricated using current in PPR waveform has better dimensional accuracy and aperture wall smoothness than those obtained with dc and pulsed dc. From the paste transfer efficiency experiment, it is concluded that photo-defined electrically assisted etching method can provide an alternate route for fabrication of metal stencils for future microelectronics printing applications.

Self Assessment-Based Decision Making for Multiagent Cooperative Search

This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

Stochastic Algorithms for Discrete Parameter Simulation Optimization

We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm. Note to Practitioners-Even though SPSA and SFA have been devised in the literature for continuous optimization problems, our results indicate that they can be powerful techniques even when they are adapted to discrete optimization settings. OCBA is widely recognized as one of the most powerful methods for discrete optimization when the parameter sets are of small or moderate size. On a setting involving a parameter set of size 100, we observe that when the computing budget is small, both SPSA and OCBA show similar performance and are better in comparison to SFA, however, as the computing budget is increased, SPSA and SFA show better performance than OCBA. Both our algorithms also show good performance when the parameter set has a size of 10(8). SFA is seen to show the best overall performance. Unlike most other DPSO algorithms in the literature, an advantage with our algorithms is that they are easily implementable regardless of the size of the parameter sets and show good performance in both scenarios.

Generalized Silver Codes

For an n(t) transmit, n(r) receive antenna system (n(t) x n(r) system), a full-rate space time block code (STBC) transmits at least n(min) = min(n(t), n(r))complex symbols per channel use. The well-known Golden code is an example of a full-rate, full-diversity STBC for two transmit antennas. Its ML-decoding complexity is of the order of M(2.5) for square M-QAM. The Silver code for two transmit antennas has all the desirable properties of the Golden code except its coding gain, but offers lower ML-decoding complexity of the order of M(2). Importantly, the slight loss in coding gain is negligible compared to the advantage it offers in terms of lowering the ML-decoding complexity. For higher number of transmit antennas, the best known codes are the Perfect codes, which are full-rate, full-diversity, information lossless codes (for n(r) >= n(t)) but have a high ML-decoding complexity of the order of M(ntnmin) (for n(r) < n(t), the punctured Perfect codes are considered). In this paper, a scheme to obtain full-rate STBCs for 2(a) transmit antennas and any n(r) with reduced ML-decoding complexity of the order of M(nt)(n(min)-3/4)-0.5 is presented. The codes constructed are also information lossless for >= n(t), like the Perfect codes, and allow higher mutual information than the comparable punctured Perfect codes for n(r) < n(t). These codes are referred to as the generalized Silver codes, since they enjoy the same desirable properties as the comparable Perfect codes (except possibly the coding gain) with lower ML-decoding complexity, analogous to the Silver code and the Golden code for two transmit antennas. Simulation results of the symbol error rates for four and eight transmit antennas show that the generalized Silver codes match the punctured Perfect codes in error performance while offering lower ML-decoding complexity.

Training-Symbol Embedded, High-Rate, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Distributed space-time block codes (DSTBCs) from complex orthogonal designs (CODs) (both square and nonsquare), coordinate interleaved orthogonal designs (CIODs), and Clifford unitary weight designs (CUWDs) are known to lose their single-symbol ML decodable (SSD) property when used in two-hop wireless relay networks using amplify and forward protocol. For such networks, in this paper, three new classes of high rate, training-symbol embedded (TSE) SSD DSTBCs are constructed: TSE-CODs, TSE-CIODs, and TSE-CUWDs. The proposed codes include the training symbols inside the structure of the code which is shown to be the key point to obtain the SSD property along with the channel estimation capability. TSE-CODs are shown to offer full-diversity for arbitrary complex constellations and the constellations for which TSE-CIODs and TSE-CUWDs offer full-diversity are characterized. It is shown that DSTBCs from nonsquare TSE-CODs provide better rates (in symbols per channel use) when compared to the known SSD DSTBCs for relay networks. Important from the practical point of view, the proposed DSTBCs do not contain any zeros in their codewords and as a result, antennas of the relay nodes do not undergo a sequence of switch on/off transitions within every codeword, and, thus, avoid the antenna switching problem.

Multilevel inverters for low-power application

Multilevel inverters are an attractive solution in the medium-voltage and high-power applications. However in the low-power range also it can be a better solution compared to two-level inverters, if MOSFETs are used as devices switching in the order of 100 kHz. The effect of clamping diodes in the diode-clamped multilevel inverters play an important role in determining its efficiency. Power loss introduced by the reverse recovery of MOSFET body diode prohibits the use of MOSFET in hard-switched inverter legs. A technique of avoiding reverse recovery loss of MOSFET body diode in a three-level neutral point clamped inverter is suggested. The use of multilevel inverters topology enables operation at high switching frequency without sacrificing efficiency. High switching frequency of operation reduces the output filter requirement, which in turn helps in reducing the size of the inverter. This study elaborates the trade-off analysis to quantify the suitability of multilevel inverters in the low-power applications. Advantages of using a MOSFET-based three-level diode-clamped inverter for a PM motor drive and UPS systems are discussed.

Magnetoelectric Effect in L1(0)-CoPd Thin Films

The effect of an applied electric field on the magnetic properties of L1(0)-ordered CoPd thin films is investigated by first-principle calculations. Both the magnetic moment and the magnetocrystalline anisotropy of the surface atoms are changed by the electric field, but the net effect depends on the surface termination. The magnetocrystalline anisotropy switches from in-plane to perpendicular in the presence of external electric field. Typical magnetic-moment changes are 0.1 mu(B) per eV/angstrom The main mechanism is the shift of the Fermi level, but the anisotropy change also reflects a crystal-field change due to incomplete screening.

Collision Cones for Quadric Surfaces

The problem of collision prediction in dynamic environments appears in several diverse fields, which include robotics, air vehicles, underwater vehicles, and computer animation. In this paper, collision prediction of objects that move in 3-D environments is considered. Most work on collision prediction assumes objects to be modeled as spheres. However, there are many instances of object shapes where an ellipsoidal or a hyperboloid-like bounding box would be more appropriate. In this paper, a collision cone approach is used to determine collision between objects whose shapes can be modeled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained in the form of analytical expressions in the relative velocity space. For objects of arbitrary shapes, exact representations of planar sections of the 3-D collision cone are obtained.