Optimal placement of Distributed Generation for a projected load increase using Relative Electrical Distance approach

There is a lot of pressure on all the developed and second world countries to produce low emission power and distributed generation (DG) is found to be one of the most viable ways to achieve this. DG generally makes use of renewable energy sources like wind, micro turbines, photovoltaic, etc., which produce power with minimum green house gas emissions. While installing a DG it is important to define its size and optimal location enabling minimum network expansion and line losses. In this paper, a methodology to locate the optimal site for a DG installation, with the objective to minimize the net transmission losses, is presented. The methodology is based on the concept of relative electrical distance (RED) between the DG and the load points. This approach will help to identify the new DG location(s), without the necessity to conduct repeated power flows. To validate this methodology case studies are carried out on a 20 node, 66kV system, a part of Karnataka Transco and results are presented.

Completely random nanoporous Cu4O3-CuO-C composite thin films for potential application as multiple channel photonic band gap based filter in the telecommunication wavelengths

In 2003, Babin et al. theoretically predicted (J. Appl. Phys. 94:4244, 2003) that fabrication of organic-inorganic hybrid materials would probably be required to implement structures with multiple photonic band gaps. In tune with their prediction, we report synthesis of such an inorganic-organic nanocomposite, comprising Cu4O3-CuO-C thin films that experimentally exhibit the highest (of any known material) number (as many as eleven) of photonic band gaps in the near infrared. On contrary to the report by Wang et al. (Appl. Phys. Lett. 84:1629, 2004) that photonic crystals with multiple stop gaps require highly correlated structural arrangement such as multilayers of variable thicknesses, we demonstrate experimental realization of multiple stop gaps in completely randomized structures comprising inorganic oxide nanocrystals (Cu4O3 and CuO) randomly embedded in a randomly porous carbonaceous matrix. We report one step synthesis of such nanostructured films through the metalorganic chemical vapor deposition technique using a single source metalorganic precursor, Cu-4(deaH)(dea)(oAc)(5) a <...aEuro parts per thousand(CH3)(2)CO. The films displaying multiple (4/9/11) photonic band gaps with equal transmission losses in the infrared are promising materials to find applications as multiple channel photonic band gap based filter for WDM technology.

Process control of cantilever deflection for sensor application based on optical waveguides

This paper reports on the fabrication of cantilever silicon-on-insulator (SOI) optical waveguides and presents solutions to the challenges of using a very thin 260-nm active silicon layer in the SOI structure to enable single-transverse-mode operation of the waveguide with minimal optical transmission losses. In particular, to ameliorate the anchor effect caused by the mean stress difference between the active silicon layer and buried oxide layer, a cantilever flattening process based on Ar plasma treatment is developed and presented. Vertical deflections of 0.5 mu m for 70-mu m-long cantilevers are mitigated to within few nanometers. Experimental investigations of cantilever mechanical resonance characteristics confirm the absence of significant detrimental side effects. Optical and mechanical modeling is extensively used to supplement experimental observations. This approach can satisfy the requirements for on-chip simultaneous readout of many integrated cantilever sensors in which the displacement or resonant frequency changes induced by analyte absorption are measured using an optical-waveguide-based division multiplexed system.

Determination of the absorption for incident light propagating parallel through the guest-host polymer film waveguide

Guest host polymer thin films of polymethyl methacrylate (PMMA) incorporated with (4'-nitrobenzene)-3-azo-9-ethylcarbazole (NAEC) were fabricated by spin coating and then poled by the method of corona-onset poling at elevated temperature. The absorption mechanism of the polymeric film, which is very important for the optical transmission losses and directly relates to the orientation of chromophore NAEC in polymer PMMA, was investigated in detail. From the UV-visible absorption spectra for NAEC/PMMA film before and after being poled, we determined the change of absorption coefficient kappa with the wavelength and approximately calculated the maximum absorption A(parallel tomax) as 3.46 for incident light propagating parallel through the film, i.e. the ordinary polarized light, which cannot be directly measured in the spectro photometer. (C) 2002 Elsevier Science Ltd. All rights reserved.

Optimization and characterization of the guest-host polyetherketone polymer films for application in integrated optical devices

In order to optimize the loading of 3-(1, 1-dicyanothenyl)-1-phenyl-4, 5-dihydro-1H-pryazole (DCNP) in polyetherketone (PEK-c) guest-host polymer films, ten kinds of DCNP/PEK-c thin films, in which the weight per cent of DCNP changes from 5 to 50, were prepared. Their second-order nonlinear optical coefficients chi(33)((2)) at 1064 nm were measured by Using Maker fringe method after poling under the optimal poling condition. Their optical waveguide transmission losses were measured at 632.8 nm. Optimal weight per cent of the chromophore for the DCNP/PEK-c guest-host polymer system has been determined as about 20 for use in the integrated optical devices.

利用网络拓扑法计算网损微增率

本文提出一个计算网损微增率的新途径。应用网络拓扑方法得到的网损修正值的直接数学表达式,不仅可利用系统潮流进行直接计算,而且有明确的物理概念,可用于实时经济调度。文中给出了计算方法和实例。

Projeto de Sistema Fotovoltaico Para as Naves Industriais da Zona Econômica Especial de Luanda-Bengo

Com os preços do barril de petróleo a atingir níveis nunca antes atingidos, cada vez mais há uma maior sensibilização para a importância das fontes renováveis de energia, não só pelo seu baixo custo de exploração, mas também pela ausência de poluição ambiental. A integração de sistemas fotovoltaicos nas edificações, começa a ter uma expressão significativa especialmente por ser uma forma de produção renovável. Pelo seu carácter renovável, vai ao encontro de objetivos ambientais, e é também desejável pelo seu carácter distribuído, produção próxima do consumo, evitando perdas de transporte e utilizando o recurso disponível no consumidor. No presente projeto é feita uma breve descrição do atual sistema elétrico angolano, nomeadamente o seu potencial, capacidade instalada, e perspetivas futuras de desenvolvimento do mesmo. Com uma perspetiva introdutória são abordadas as energias renováveis especialmente a energia fotovoltaica, terminando com as diferentes formas de produção e tecnologias existentes. São apresentados diferentes equipamentos, que, com as inúmeras combinações poderão vir a constituir um sistema técnico e financeiramente viável. Devido aos vários cenários possíveis (combinações entre equipamentos), foram usadas como instrumentos de apoio ferramentas informáticas que permitem o dimensionamento de sistemas fotovoltaicos, análise de compatibilidades, e simulação do seu funcionamento. Foram dimensionadas quatro opções de sistemas fotovoltaicos, a instalar nas naves industriais da Zona Económica Especial Luanda-Bengo, para uma mesma área de cobertura, seguido de um estudo económico, onde é feito uma comparação custo/benefício dos vários sistemas.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

A Reinforcement Learning Approach to Economic Dispatch using Neural Networks

This paper presents a Reinforcement Learning (RL) approach to economic dispatch (ED) using Radial Basis Function neural network. We formulate the ED as an N stage decision making problem. We propose a novel architecture to store Qvalues and present a learning algorithm to learn the weights of the neural network. Even though many stochastic search techniques like simulated annealing, genetic algorithm and evolutionary programming have been applied to ED, they require searching for the optimal solution for each load demand. Also they find limitation in handling stochastic cost functions. In our approach once we learn the Q-values, we can find the dispatch for any load demand. We have recently proposed a RL approach to ED. In that approach, we could find only the optimum dispatch for a set of specified discrete values of power demand. The performance of the proposed algorithm is validated by taking IEEE 6 bus system, considering transmission losses

Comparação de propostas para alocação dos custos de perdas na transmissão

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Practical and prospective slow light Surface Nanoscale Axial Photonics (SNAP) devices

Miniature slow light Surface Nanoscale Axial Photonics (SNAP) devices are reviewed. The fabrication precision of these devices is two orders of magnitude higher and the transmission losses are two orders of magnitude smaller than for any of the previously reported technologies for fabrication of miniature photonic circuits. In the first part of the report, a SNAP bottle resonator with a few nm high radius variation is demonstrated as the record small, slow light, and low loss 2.6 ns dispersionless delay line of 100 ps pulses. Next, a record small SNAP bottle resonator exhibiting the 20 ns/nm dispersion compensation of 100 ps pulses is demonstrated. In the second part of the report, the prospects of the SNAP technology in applications to telecommunications, optical signal processing, quantum computing, and microfluidics are discussed. © 2014 IEEE.

Nanophotonics of optical fibers

This review is concerned with nanoscale effects in highly transparent dielectric photonic structures fabricated from optical fibers. In contrast to those in plasmonics, these structures do not contain metal particles, wires, or films with nanoscale dimensions. Nevertheless, a nanoscale perturbation of the fiber radius can significantly alter their performance. This paper consists of three parts. The first part considers propagation of light in thin optical fibers (microfibers) having the radius of the order of 100 nanometers to 1 micron. The fundamental mode propagating along a microfiber has an evanescent field which may be strongly expanded into the external area. Then, the cross-sectional dimensions of the mode and transmission losses are very sensitive to small variations of the microfiber radius. Under certain conditions, a change of just a few nanometers in the microfiber radius can significantly affect its transmission characteristics and, in particular, lead to the transition from the waveguiding to non-waveguiding regime. The second part of the review considers slow propagation of whispering gallery modes in fibers having the radius of the order of 10–100 microns. The propagation of these modes along the fiber axis is so slow that they can be governed by extremely small nanoscale changes of the optical fiber radius. This phenomenon is exploited in SNAP (surface nanoscale axial photonics), a new platform for fabrication of miniature super-low-loss photonic integrated circuits with unprecedented sub-angstrom precision. The SNAP theory and applications are overviewed. The third part of this review describes methods of characterization of the radius variation of microfibers and regular optical fibers with sub-nanometer precision.

Evaluation of Charges for Power Transmission and Losses in Bilateral Power Contracts

The paper presents a method for transmission loss charge allocation in deregulated power systems based on Relative Electrical Distance (RED) concept. Based on RED between the generator and load nodes and the predefined bilateral power contracts, charge evaluation is carried out. Generally through some power exchange mechanism a set of bilateral contracts are determined that facilitate bilateral agreements between the generation and distribution entities. In this paper the possible charges incurred in meeting loads like generation charge, transmission charge and charge due to losses are evaluated. Case studies have been carried out on a few practical equivalent systems. Due to space limitation results for a sample 5 bus system are presented considering ideal load/generation power contracts and deviated load/generation power contracts. Extensive numerical testing indicates that the proposed allocation scheme produces loss allocations that are appropriate and that behave in a physically reasonable manner.

On the Efficiency and Fairness of Transmission Control Loops: A Case for Exogenous Losses

We postulate that exogenous losses-which are typically regarded as introducing undesirable "noise" that needs to be filtered out or hidden from end points-can be surprisingly beneficial. In this paper we evaluate the effects of exogenous losses on transmission control loops, focusing primarily on efficiency and convergence to fairness properties. By analytically capturing the effects of exogenous losses, we are able to characterize the transient behavior of TCP. Our numerical results suggest that "noise" resulting from exogenous losses should not be filtered out blindly, and that a careful examination of the parameter space leads to better strategies regarding the treatment of exogenous losses inside the network. Specifically, we show that while low levels of exogenous losses do help connections converge to their fair share, higher levels of losses lead to inefficient network utilization. We draw the line between these two cases by determining whether or not it is advantageous to hide, or more interestingly introduce, exogenous losses. Our proposed approach is based on classifying the effects of exogenous losses into long-term and short-term effects. Such classification informs the extent to which we control exogenous losses, so as to operate in an efficient and fair region. We validate our results through simulations.