Reactive power and voltage control in grid connected wind farms

Wind power, as an alternative to fossil fuels, is plentiful, renewable, widely distributed, clean, produces no greenhouse gas emissions during operation, and uses little land. In operation, the overall cost per unit of energy produced is similar to the cost for new coal and natural gas installations. However, the stochastic behaviour of wind speeds leads to significant disharmony between wind energy production and electricity demand. Wind generation suffers from an intermittent characteristics due to the own diurnal and seasonal patterns of the wind behaviour. Both reactive power and voltage control are important under varying operating conditions of wind farm. To optimize reactive power flow and to keep voltages in limit, an optimization method is proposed in this paper. The objective proposed is minimization of the voltage deviations of the load buses (Vdesired). The approach considers the reactive power limits of wind generators and co-ordinates the transformer taps. This algorithm has been tested under practically varying conditions simulated on a test system. The results are obtained on a system of 50-bus real life equivalent power network. The result shows the efficiency of the proposed method.

How to run a campaign: Optimal control of SIS and SIR information epidemics

Information spreading in a population can be modeled as an epidemic. Campaigners (e.g., election campaign managers, companies marketing products or movies) are interested in spreading a message by a given deadline, using limited resources. In this paper, we formulate the above situation as an optimal control problem and the solution (using Pontryagin's Maximum Principle) prescribes an optimal resource allocation over the time of the campaign. We consider two different scenarios-in the first, the campaigner can adjust a direct control (over time) which allows her to recruit individuals from the population (at some cost) to act as spreaders for the Susceptible-Infected-Susceptible (SIS) epidemic model. In the second case, we allow the campaigner to adjust the effective spreading rate by incentivizing the infected in the Susceptible-Infected-Recovered (SIR) model, in addition to the direct recruitment. We consider time varying information spreading rate in our formulation to model the changing interest level of individuals in the campaign, as the deadline is reached. In both the cases, we show the existence of a solution and its uniqueness for sufficiently small campaign deadlines. For the fixed spreading rate, we show the effectiveness of the optimal control strategy against the constant control strategy, a heuristic control strategy and no control. We show the sensitivity of the optimal control to the spreading rate profile when it is time varying. (C) 2014 Elsevier Inc. All rights reserved.

Risk-sensitive control of continuous time Markov chains

We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterize the value function via Hamilton Jacobi Bellman equation and obtain an optimal Markov control. We do the same for infinite horizon discounted cost case. In the infinite horizon average cost case we establish the existence of an optimal stationary control under certain Lyapunov condition. We also develop a policy iteration algorithm for finding an optimal control.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

Adaptive Pulse Width Control and Sampling for Low Power Pulse Oximetry

Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

Experimental results on low cost microcontroller based DC drive implementation

This paper presents the experimental results for an attractive control scheme implementation using an 8 bit microcontroller. The power converter involved is a 3 phase full controlled bridge rectifier. A single quadrant DC drive has been realized and results have been presented for both open and closed loop implementations.

Multi-agent Reinforcement Learning for Traffic Signal Control

Optimal control of traffic lights at junctions or traffic signal control (TSC) is essential for reducing the average delay experienced by the road users amidst the rapid increase in the usage of vehicles. In this paper, we formulate the TSC problem as a discounted cost Markov decision process (MDP) and apply multi-agent reinforcement learning (MARL) algorithms to obtain dynamic TSC policies. We model each traffic signal junction as an independent agent. An agent decides the signal duration of its phases in a round-robin (RR) manner using multi-agent Q-learning with either is an element of-greedy or UCB 3] based exploration strategies. It updates its Q-factors based on the cost feedback signal received from its neighbouring agents. This feedback signal can be easily constructed and is shown to be effective in minimizing the average delay of the vehicles in the network. We show through simulations over VISSIM that our algorithms perform significantly better than both the standard fixed signal timing (FST) algorithm and the saturation balancing (SAT) algorithm 15] over two real road networks.

Risk-Sensitive Ergodic Control of Continuous Time Markov Processes With Denumerable State Space

In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

Sampling Period Selection of Control Application Connected to FlexRay Bus

Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

Density control of ZnO nanowires grown using Au-PMMA nanoparticles and their growth behavior.

Au nanoparticles stabilized by poly(methyl methacrylate) (PMMA) were used as a catalyst to grow vertically aligned ZnO nanowires (NWs). The density of ZnO NWs with very uniform diameter was controlled by changing the concentration of Au-PMMA nanoparticles (NPs). The density was in direct proportion to the concentration of Au-PMMA NPs. Furthermore, the growth process of ZnO NWs using Au-PMMA NPs was systematically investigated through comparison with that using Au thin film as a catalyst. Au-PMMA NPs induced polyhedral-shaped bases of ZnO NWs separated from each other, while Au thin film formed a continuous network of bases of ZnO NWs. This approach provides a facile and cost-effective catalyst density control method, allowing us to grow high-quality vertically aligned ZnO NWs suitable for many viable applications.

Robust approach to dynamic statistical process control

Statistical Process Control (SPC) technique are well established across a wide range of industries. In particular, the plotting of key steady state variables with their statistical limit against time (Shewart charting) is a common approach for monitoring the normality of production. This paper aims with extending Shewart charting techniques to the quality monitoring of variables driven by uncertain dynamic processes, which has particular application in the process industries where it is desirable to monitor process variables on-line as well as final product. The robust approach to dynamic SPC is based on previous work on guaranteed cost filtering for linear systems and is intended to provide a basis for both a wide application of SPC monitoring and also motivate unstructured fault detection.

Determinación de la acción residual en diferentes dosis de chlorpyrifos (Lorsban) con énfasis en la dosis mínima, para control de cogollero (Spodoptera frugiperda J.E. Smith; Lepidotera: Noctuidae) en maíz

Este ensayo fue realizado con el objetivo de conocer cuál es el efecto de diferente dosis de chlorpyripos sobre el tiempo de protección, buscando la dosis más adecuada para control del gusano cogollero, spodoptera frugiperda (j.e Smith) , en maíz. De manera que este estudio nos permitiera decidir cuál es el momento indicado de un recuento para una posterior aplicación del pesticida y 6 fundamentalmente bajar los costos de protección. Al evaluar la acción residual se encontró diferencia significativa entre las dosis de 1,0.5, 0.25, 0.125,0.0625 1t/mz de chlorpyrifos. La dosis de 0.25 1t/mz no es diferente de la dosis de 1 1t/mz cuanto a la acción residual de chlorpyrifos y sus promedio de rendimiento tienen también mucha similiridad pero su costo determinan la diferencia. Los resultado conducen a decidir la recomendación de la dosis de 0.25 1t/mz por ser la más económica con una acción residual de 23.3 días y un costo de control de $ 242.55 con 2.2 aplicaciones promedio en todo el periodo del cultivo, a diferencia de la dosis más alta usada de 1 1t/mz con una acción residual de 21.9 días, un promedio de 2.6 aplicaciones y un costo de $ 795.6 y el rendimiento final no es diferente entre ellas. Por otro lado de asegura que con una sola aplicación de chlorpyrifos se garantiza la mortalidad de larvas de spodoptera frugiperda (j.e. Smith) durante a los 5 a 10 días después de aplicación. Todo los anteriores permite dar un lapso estable en el tiempo que se sabe tomar para recuento, decidir la dosis mínima más económica, por su acción residual y bajar así los costó de producción.

Clearigate ® Treatments for Control of Giant Salvinia

Results of recent field trials using the chelated copper formulation Clearigate® 4 showed that applying a 20% solution by volume was effective for controlling populations of giant salvinia in irrigation canals. 5 Lower rates may be efficacious, thereby reducing chemical use and cost; however, little is known about the dose-response effects of Clearigate® against giant salvinia. The objective of this study was to determine the effective rate range of chelated copper applied as Clearigate® for control of giant salvinia.

Seafood safety: economics of Hazard Analysis and Critical Control Point (HACCP) programmes

Seventy percent of the world's catch of fish and fishery products is consumed as food. Fish and shellfish products represent 15.6 percent of animal protein supply and 5.6 percent of total protein supply on a worldwide basis. Developing countries account for almost 50 percent of global fish exports. Seafood-borne disease or illness outbreaks affect consumers both physically and financially, and create regulatory problems for both importing and exporting countries. Seafood safety as a commodity cannot be purchased in the marketplace and government intervenes to regulate the safety and quality of seafood. Theoretical issues and data limitations create problems in estimating what consumers will pay for seafood safety and quality. The costs and benefits of seafood safety must be considered at all levels, including the fishers, fish farmers, input suppliers to fishing, processing and trade, seafood processors, seafood distributors, consumers and government. Hazard Analysis Critical Control Point (HACCP) programmes are being implemented on a worldwide basis for seafood. Studies have been completed to estimate the cost of HACCP in various shrimp, fish and shellfish plants in the United States, and are underway for some seafood plants in the United Kingdom, Canada and Africa. Major developments within the last two decades have created a set of complex trading situations for seafood. Current events indicate that seafood safety and quality can be used as non-tariff barriers to free trade. Research priorities necessary to estimate the economic value and impacts of achieving safer seafood are outlined at the consumer, seafood production and processing, trade and government levels. An extensive list of references on the economics of seafood safety and quality is presented. (PDF contains 56 pages; captured from html.)