Capability Curve Based Enhanced Reactive Power Control Strategy for Stability Enhancement and Network Voltage Management

Reactive power has become a vital resource in modern electricity networks due to increased penetration of distributed generation. This paper examines the extended reactive power capability of DFIGs to improve network stability and capability to manage network voltage profile during transient faults and dynamic operating conditions. A coordinated reactive power controller is designed by considering the reactive power capabilities of the rotor-side converter (RSC) and the grid-side converter (GSC) of the DFIG in order to maximise the reactive power support from DFIGs. The study has illustrated that, a significant reactive power contribution can be obtained from partially loaded DFIG wind farms for stability enhancement by using the proposed capability curve based reactive power controller; hence DFIG wind farms can function as vital dynamic reactive power resources for power utilities without commissioning additional dynamic reactive power devices. Several network adaptive droop control schemes are also proposed for network voltage management and their performance has been investigated during variable wind conditions. Furthermore, the influence of reactive power capability on network adaptive droop control strategies has been investigated and it has also been shown that enhanced reactive power capability of DFIGs can substantially improve the voltage control performance.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Key Agreement Protocol Using Elliptic Curve Matrix Power Function

* Work is partially supported by the Lithuanian State Science and Studies Foundation.

Unit commitment in power systems with plug-in hybrid electric vehicles

With the continued development of renewable energy generation technologies and increasing pressure to combat the global effects of greenhouse warming, plug-in hybrid electric vehicles (PHEVs) have received worldwide attention, finding applications in North America and Europe. When a large number of PHEVs are introduced into a power system, there will be extensive impacts on power system planning and operation, as well as on electricity market development. It is therefore necessary to properly control PHEV charging and discharging behaviors. Given this background, a new unit commitment model and its solution method that takes into account the optimal PHEV charging and discharging controls is presented in this paper. A 10-unit and 24-hour unit commitment (UC) problem is employed to demonstrate the feasibility and efficiency of the developed method, and the impacts of the wide applications of PHEVs on the operating costs and the emission of the power system are studied. Case studies are also carried out to investigate the impacts of different PHEV penetration levels and different PHEV charging modes on the results of the UC problem. A 100-unit system is employed for further analysis on the impacts of PHEVs on the UC problem in a larger system application. Simulation results demonstrate that the employment of optimized PHEV charging and discharging modes is very helpful for smoothing the load curve profile and enhancing the ability of the power system to accommodate more PHEVs. Furthermore, an optimal Vehicle to Grid (V2G) discharging control provides economic and efficient backups and spinning reserves for the secure and economic operation of the power system

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

Normalization and Charter 77 : Violence, Commitment and Resistance in Czechoslovakia

In Czechoslovakia, the occupation of 1968 denoted the beginning of normalization , a political and societal stagnation that lasted two decades. Dissident initiative Charter 77 emerged in 1977, demanding that the leaders of the country respect human rights. The Helsinki process provided a macro-level framework that influenced opposition and dissident activities throughout Eastern Europe. The study contributes a focused empirical analysis of the period of normalization and the dissident movement Charter 77. Dissent in general is seen as an existential attitude; it can be encapsulated as a morally rationalized critical stance as derived from shared experience or interpretation of injustice, which serves as a basis for a shared collective identity comprising oppositional consciousness as one unifying factor. The study suggests that normalization can be understood as a fundamentally violent process and discusses the structural and cultural manifestations of violence with relation to Charter 77. In general, the aim of the system was to passivize the society to such an extent that it would not constitute a potential threat to the hegemonic rule of the regime. Normalization caused societal stagnation and apoliticization, but it also benefited those who accepted the new political reality. The study, however, questions the image of Czechoslovakia s allegedly highly repressive rule by showing that there was also quite considerable tolerance of Charter 77 and consideration before severe repression was brought to bear against dissidents. Furthermore, the study provides understanding of the motives and impetuses behind dissent, the strategic shifts in Charter 77 activities, and the changes in the regime s policies toward Charter 77. The study also adds new perspective on the common image of Charter 77 as a non political initiative and suggests that Charter 77 was, in fact, a political entity, an actively political one in the latter half of the 1980s. Charter 77 was a de facto hybrid of a traditional dissident initiative and an oppositional actor. Charter 77 adopted a two-dimension approach: firstly, it still emphasized its role as a citizens initiative supporting human rights, but, secondly, at the same time, it was a directly political actor supporting and furthering the development of political opposition against the ruling power.

A method of tracking the peak power points for a variable speed wind energy conversion system

In this paper, a method of tracking the peak power in a wind energy conversion system (WECS) is proposed, which is independent of the turbine parameters and air density. The algorithm searches for the peak power by varying the speed in the desired direction. The generator is operated in the speed control mode with the speed reference being dynamically modified in accordance with the magnitude and direction of change of active power. The peak power points in the P-omega curve correspond to dP/domega = 0. This fact is made use of in the optimum point search algorithm. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back pulse-width-modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The turbine characteristics are generated by a dc motor fed from a commercial dc drive. All of the control loops are executed by a single-chip digital signal processor (DSP) controller TMS320F240. Experimental results show that the performance of the control algorithm compares well with the conventional torque control method.

Strength of Gamma Rhythm Depends on Normalization

Neuronal assemblies often exhibit stimulus-induced rhythmic activity in the gamma range (30-80 Hz), whose magnitude depends on the attentional load. This has led to the suggestion that gamma rhythms form dynamic communication channels across cortical areas processing the features of behaviorally relevant stimuli. Recently, attention has been linked to a normalization mechanism, in which the response of a neuron is suppressed (normalized) by the overall activity of a large pool of neighboring neurons. In this model, attention increases the excitatory drive received by the neuron, which in turn also increases the strength of normalization, thereby changing the balance of excitation and inhibition. Recent studies have shown that gamma power also depends on such excitatory-inhibitory interactions. Could modulation in gamma power during an attention task be a reflection of the changes in the underlying excitation-inhibition interactions? By manipulating the normalization strength independent of attentional load in macaque monkeys, we show that gamma power increases with increasing normalization, even when the attentional load is fixed. Further, manipulations of attention that increase normalization increase gamma power, even when they decrease the firing rate. Thus, gamma rhythms could be a reflection of changes in the relative strengths of excitation and normalization rather than playing a functional role in communication or control.

Effects of anode temperature on working characteristics and performance of a low power arcjet thruster

An arc-heated thruster of 130–800 W input power is tested in a vacuum chamber at pressures lower than 20 Pa with argon or H2–N2 gas mixture as propellant. The time-dependent arc voltage-current curve, outside-surface temperature of the anode nozzle and the produced thrust of the firing arcjet thruster are measured in situ simultaneously, in order to analyze and evaluate the dependence of thruster working characteristics and output properties, such as specific impulse and thrust efficiency, on nozzle temperature.

Mast Cell Curve-Response in Partial Achilles Tendon Rupture After 830 nm Phototherapy

Objective: the aim of this study was to quantify mast cells at different time intervals after partial Achilles tendon rupture in rats treated with low-level laser therapy (LLLT). Background data: There is a high incidence of lesions and ruptures in the Achilles tendon that can take weeks and even months to heal completely. As the mast cells help in the healing repair phase, and LLLT has favorable effects on this tissue repair process, study of this modality on the quantity of mastocytes in the ruptured tendon is relevant. Methods: Sixty Wistar rats were subjected to partial Achilles' tendon rupture by direct trauma, randomized into 10 groups, and then divided into the group treated with 80mW aluminum gallium arsenide infrared laser diode, continuous wave, 2.8W/cm(2) power density, 40J/cm(2) energy density, and 1.12J total energy, and the simulation group. Both the groups were subdivided according to the histological assessment period of the sample, either 6h, 12h, 24h, 2 days, or 3 days after the rupture, to quantify the mastocytes in the Achilles' tendon. Results: the group subjected to LLLT presented a greater quantity of mastocytes in the periods of 6h, 12h, 24h, 2 days, and 3 days after rupture, compared with the simulation groups, but differences were detected between the sample assessment periods only in the simulation group. Conclusions: LLLT was shown to increase the quantity of mastocytes in the assessment periods compared with the simulation groups.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Multi-Objective Reactive Power Support from Wind farms for Network Performance Enhancement

This paper examines the ability of the doubly fed induction generator (DFIG) to deliver multiple reactive power objectives during variable wind conditions. The reactive power requirement is decomposed based on various control objectives (e.g. power factor control, voltage control, loss minimisation, and flicker mitigation) defined around different time frames (i.e. seconds, minutes, and hourly), and the control reference is generated by aggregating the individual reactive power requirement for each control strategy. A novel coordinated controller is implemented for the rotor-side converter and the grid-side converter considering their capability curves and illustrating that it can effectively utilise the aggregated DFIG reactive power capability for system performance enhancement. The performance of the multi-objective strategy is examined for a range of wind and network conditions, and it is shown that for the majority of the scenarios, more than 92% of the main control objective can be achieved while introducing the integrated flicker control scheme with the main reactive power control scheme. Therefore, optimal control coordination across the different control strategies can maximise the availability of ancillary services from DFIG-based wind farms without additional dynamic reactive power devices being installed in power networks.

LSQ14bdq: a type Ic Super-luminous Supernova with a double-peaked light curve

We present data for LSQ14bdq, a hydrogen-poor super-luminous supernova (SLSN) discovered by the La Silla QUEST survey and classified by the Public ESO Spectroscopic Survey of Transient Objects. The spectrum and light curve are very similar to slow-declining SLSNe such as PTF12dam. However, detections within ∼1 day after explosion show a bright and relatively fast initial peak, lasting for ∼15 days, prior to the usual slow rise to maximum light. The broader, main peak can be fit with either central engine or circumstellar interaction models. We discuss the implications of the precursor peak in the context of these models. It is too bright and narrow to be explained as a normal ⁵⁶Ni-powered SN, and we suggest that interaction models may struggle to fit the two peaks simultaneously. We propose that the initial peak may arise from the post-shock cooling of extended stellar material, and reheating by a central engine drives the second peak. In this picture, we show that an explosion energy of ∼2 × 10⁵² erg and a progenitor radius of a few hundred solar radii would be required to power the early emission. The competing engine models involve rapidly spinning magnetars (neutron stars) or fallback onto a central black hole. The prompt energy required may favor the black hole scenario. The bright initial peak may be difficult to reconcile with a compact Wolf-Rayet star as a progenitor since the inferred energies and ejected masses become unphysical.