Metodología Demand Driven para mejora de servicio y reducción de costos

Actualmente, para la planeación de la cadena de suministro, las organizaciones utilizan métodos convencionales basados en modelos estadísticos que miran el pasado y no reconocen avances -- Con este estudio se busca proyectar el futuro estos procesos -- Para lograrlo se tiene en cuenta la metodología Demand Driven que, para cambiar esta situación, basa su teoría en la adaptación de la cadena logística para reaccionar ante la venta en tiempo real, mediante la organización de buffers o pequeñas cajas de inventario que según las características de la cadena tendrán distintas propiedades para garantizar siempre la disponibilidad de stock, al menor coste y cantidad posible -- Se pretende demostrar la metodología mediante un caso de empresa: la viabilidad del sistema para garantizar la reducción del capital invertido en inventarios, garantizando mayor flujo de capital para inversión en nuevos aspectos; se presupone mejora en servicio que se traduce en mayores ventas para la compañía y reducción de costos al tener menor nivel de inventarios -- Al realizar el ejemplo empresarial, este estudio entrega a los líderes de las organizaciones las herramientas necesarias para toma de decisiones sobre cambios estructurales en la forma de realizar su proceso de planeación y ventas operacionales en busca de adaptaciones a las necesidades del mercado cambiante y exigente en el que vivimos hoy, donde los consumidores buscan bajo costo, alta calidad y disponibilidad a la mano -- En este estudio se puede observar cómo se pueden incrementar los ingresos en un 20% con sólo mejorar el nivel de servicio y entregas a tiempo a los clientes

Síntese e caracterização de ferrita ni-zn pelo método dos precursores poliméricos calcinada por energia de microondas

Magnetic ceramics have been widely investigated, especially with respect to intrinsic and extrinsic characteristics of these materials. Among the magnetic ceramic materials of technological interest, there are the ferrites. On the other hand, the thermal treatment of ceramic materials by microwave energy has offered various advantages such as: optimization of production processes, high heat control, low consumption of time and energy among others. In this work were synthesized powders of Ni-Zn ferrite with compositions Ni1- xZnxFe2O4 (0.25 ≤ x ≤ 0.75 mols) by the polymeric precursor route in two heat treatment conditions, conventional oven and microwave energy at 500, 650, 800 and 950°C and its structural, and morphological imaging. The materials were characterized by thermal analysis (TG/ DSC), X-ray diffraction (XRD), absorption spectroscopy in the infrared (FTIR), scanning electron microscopy (SEM), X-ray spectroscopy and energy dispersive (EDS) and vibrating sample magnetometry (VSM). The results of X-ray diffraction confirmed the formation of ferrite with spinel-type cubic structure. The extrinsic characteristics of the powders obtained by microwave calcination and influence significantly the magnetic behavior of ferrites, showing particles ferrimagnéticas characterized as soft magnetic materials (soft), is of great technological interest. The results obtained led the potential application of microwave energy for calcining powders of Ni-Zn ferrite

Eficiencia energética en el sector residencial de la ciudad de Cuenca, Ecuador

El estudio se centra en el sector residencial de la ciudad de Cuenca, Ecuador. El objetivo es determinar hasta donde se puede reducir el consumo de energía a la vez que se obtengan óptimas condiciones de confort, estableciendo un indicador de eficiencia energética. Para ello se determina la demanda de energía eléctrica y los factores principales de consumo, mediante una metodología de investigación mixta tanto cualitativa como cuantitativa, pues el consumo energético se ve influenciado por diferentes elementos como la eficiencia de los equipos, diseño y hábitos de uso de los habitantes, entre otros. Se realizan encuestas a una muestra de 280 hogares del sector residencial de Cuenca y por otro lado se mide el consumo y calidad lumínica del ambiente interior de 6 viviendas mediante equipos, simulaciones y encuestas. Posteriormente se analizan los resultados obtenidos y se los compara con los estándares de eficiencia nacional e internacional, se proponen estrategias básicas para la reducción del consumo de energía eléctrica y finalmente el estudio define una clasificación de indicadores de consumo mínimo.

Novel Automotive Waste Heat Recovery Techniques

The United States transportation industry is predicted to consume approximately 13 million barrels of liquid fuel per day by 2025. If one percent of the fuel energy were salvaged through waste heat recovery, there would be a reduction of 130 thousand barrels of liquid fuel per day. This dissertation focuses on automotive waste heat recovery techniques with an emphasis on two novel techniques. The first technique investigated was a combination coolant and exhaust-based Rankine cycle system, which utilized a patented piston-in-piston engine technology. The research scope included a simulation of the maximum mass flow rate of steam (700 K and 5.5 MPa) from two heat exchangers, the potential power generation from the secondary piston steam chambers, and the resulting steam quality within the steam chamber. The secondary piston chamber provided supplemental steam power strokes during the engine's compression and exhaust strokes to reduce the pumping work of the engine. A Class-8 diesel engine, operating at 1,500 RPM at full load, had a maximum increase in the brake fuel conversion efficiency of 3.1%. The second technique investigated the implementation of thermoelectric generators on the outer cylinder walls of a liquid-cooled internal combustion engine. The research scope focused on the energy generation, fuel energy distribution, and cylinder wall temperatures. The analysis was conducted over a range of engine speeds and loads in a two cylinder, 19.4 kW, liquid-cooled, spark-ignition engine. The cylinder wall temperatures increased by 17% to 44% which correlated well to the 4.3% to 9.5% decrease in coolant heat transfer. Only 23.3% to 28.2% of the heat transfer to the coolant was transferred through the TEG and TEG surrogate material. The gross indicated work decreased by 0.4% to 1.0%. The exhaust gas energy decreased by 0.8% to 5.9%. Due to coolant contamination, the TEG output was not able to be obtained. TEG output was predicted from cylinder wall temperatures and manufacturer documentation, which was less than 0.1% of the cumulative heat release. Higher TEG conversion efficiencies, combined with greater control of heat transfer paths, would be needed to improve energy output and make this a viable waste heat recovery technique.

Adaptive edge analytics for distributed networked control of water systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

Stellar mass loss from the Fornax dwarf spheroidal galaxy

Dwarf galaxies often experience gravitational interactions from more massive companions. These interactions can deform galaxies, turn star formation on or off, or give rise to mass loss phenomena. In this thesis work we propose to study, through N-body simulations, the stellar mass loss suffered by the dwarf spheroid galaxy (dSph) Fornax orbiting in the Milky Way gravitational potential. Which is a key phenomenon to explain the mass budget problem: the Fornax globular clusters together have a stellar mass comparable to that of Fornax itself. If we look at the stellar populations which they are made of and we apply the scenarios of stellar population formation we find that, originally, they must have been >= 5 times more massive. For this reason, they must have lost or ejected stars through dynamic interactions. However, as presented in Larsen et al (2012), field stars alone are not sufficient to explain this scenario. We may assume that some of those stars fell into Fornax, and later were stripped by Milky Way. In order to study this solution we built several illustrative single component simulations, with a tabulated density model using the P07ecc orbit studied from Battaglia et al (2015). To divide the single component into stellar and dark matter components we have defined a posterior the probability function P(E), where E is the initial energy distribution of the particles. By associating each particle with a fraction of stellar mass and dark matter. In this way we built stellar density profiles without repeating simulations. We applied the method to Fornax using the profile density tables obtained in Pascale et al (2018) as observational constraints and to build the model. The results confirm the results previously obtained with less flexible models by Battaglia et al (2015). They show a stellar mass loss < 4% within 1.6 kpc and negligible within 3 kpc, too small to solve the mass budget problem.

Electric transmission of energy : and its transformation, subdivision, and distribution ; a practical handbook /

Mode of access: Internet.

Relationship Between Surface Topography and Energy Density Distribution of Er,Cr:YSGG Beam on Irradiated Dentin: An Atomic Force Microscopy Study

Objective: The aim of this study was to assess by atomic force microscopy (AFM) the effect of Er,Cr:YSGG laser application on the surface microtopography of radicular dentin. Background: Lasers have been used for various purposes in dentistry, where they are clinically effective when used in an appropriate manner. The Er, Cr: YSGG laser can be used for caries prevention when settings are below the ablation threshold. Materials and Methods: Four specimens of bovine dentin were irradiated using an Er, Cr:YSGG laser (lambda = 2.78 mu m), at a repetition rate of 20 Hz, with a 750-mu m-diameter sapphire tip and energy density of 2.8 J/cm(2) (12.5 mJ/pulse). After irradiation, surface topography was analyzed by AFM using a Si probe in tapping mode. Quantitative and qualitative information concerning the arithmetic average roughness (Ra) and power spectral density analyses were obtained from central, intermediate, and peripheral areas of laser pulses and compared with data from nonirradiated samples. Results: Dentin Ra for different areas were as follows: central, 261.26 (+/- 21.65) nm; intermediate, 83.48 (+/- 6.34) nm; peripheral, 45.8 (+/- 13.47) nm; and nonirradiated, 35.18 (+/- 2.9) nm. The central region of laser pulses presented higher ablation of intertubular dentin, with about 340-760 nm height, while intermediate, peripheral, and nonirradiated regions presented no difference in height of peritubular and interperitubular dentin. Conclusion: According to these results, we can assume that even when used at a low-energy density parameter, Er, Cr: YSGG laser can significantly alter the microtopography of radicular dentin, which is an important characteristic to be considered when laser is used for clinical applications.

Superior electric double layer capacitors using ordered mesoporous carbons

This paper reports for the first time superior electric double layer capacitive properties of ordered mesoporous carbon (OMCs) with varying ordered pore symmetries and mesopore structure. Compared to commercially used activated carbon electrode, Maxsorb, these OMC carbons have superior capacitive behavior, power output and high-frequency performance in EDLCs due to the unique structure of their mesopore network, which is more favorable for fast ionic transport than the pore networks in disordered microporous carbons. As evidenced by N-2 sorption, cyclic voltammetry and frequency response measurements, OMC carbons with large mesopores, and especially with 2-D pore symmetry, show superior capacitive behaviors (exhibiting a high capacitance of over 180 F/g even at very high sweep rate of 50 mV/s, as compared to much reduced capacitance of 73 F/g for Maxsorb at the same sweep rate). OMC carbons can provide much higher power density while still maintaining good energy density. OMC carbons demonstrate excellent high-frequency performances due to its higher surface area in pores larger than 3 nm. Such ordered mesoporous carbons (OMCs) offer a great potential in EDLC capacitors, particularly for applications where high power output and good high-frequency capacitive performances are required. (C) 2005 Elsevier Ltd. All rights reserved.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.