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The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

It is well known that the efficiency of PV modules decreases with increasing module temperatures. Many studies have paid attention to the development and validation of heuristic models to calculate the PV module temperature in higher latitudes, however only a few focus on the thermal behaviour of PV modules in tropical regions of the world, where constantly high temperatures prevail. Also, little is known about the effect of including wind speed in these thermal models. This study evaluates three of such models - one that excludes wind, and two others including the wind influence - using hourly data for two tropical locations. Results show that the average hourly wind speeds in Singapore and Jayapura (Indonesia) are low and therefore the influence of the wind on the PV module temperature is minor. The three evaluated models produce about the same results with RMSE between 1.5-3.8 °C during daytime, which corresponds to a deviation in power output in the range of 0.3-1.6 %, depending on the PV module technology.

beta-Carotene and six xanthophylls (lutein, neoxanthin, violaxanthin, luteoxanthin, cryptoxanthin, and echinenone) have been identified and semiquantitatively or quantitatively determined in musts and port wines for the first time. An HPLC method was developed and compared with that of one based on thin layer cromatography with scanning densitometry. The most abundant carotenoids present in red grape varieties are beta-carotene and lutein. In wines, significant quantities of violaxanthin, luteoxanthin, and neoxanthin were found. This study was done with berries (skin and pulp), musts, and fortified wines. Some experiments were performed to follow carotenoid content from grapes to wines. Although the levels of beta-carotene and lutein found in fortified wines were lower than those found in musts, other xanthophylls, such as neoxanthin, violaxanthin, and luteoxanthin, exist in appreciable amounts in young ports.

Artículos en revistas In this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented. info:eu-repo/semantics/publishedVersion

Artículos en revistas Liberalization policies, the challenges of integrating distributed generation resources, and the recent flattening of electricity demand due to the economic crisis and technological change have led to lower returns for European electricity suppliers. Innovative and sustainable business models are needed to serve electricity customers while reflecting the operational needs of the system and maintaining supplier financial viability. This paper describes a novel model of Integrated Energy Services that encompasses distributed generation (DG) and demand response (DR) resources for industrial customers. We further reflect on some of the market opportunities and regulatory drivers for the development of similar schemes across Europe. info:eu-repo/semantics/publishedVersion

North Sea fisheries are managed by the European Union (EU) through a system of annual quota. Due to uncertainty about future fish stocks, yearly revisions of these policies lead to fluctuation in quota, which in turn affects harvest and investment decisions of fishermen. Determination of quota requires high management costs in terms of obtaining information and negotiations between experts and policy makers. To reduce both quota fluctuation and management costs, the EU has proposed a system of multiannual quota. In this paper we study the effect of multiannual quota on quota volatility and resource rents, while accounting for management costs. We develop a bi-level stochastic dynamic programming model, where at level one, the EU determines the quota that maximizes resource rents. At level two, fishermen decide myopically on their harvest and investment levels, subject to the quota. Results show that policy makers can reduce quota volatility and improve resource rents from the fishery with multiannual quota. Important trade-offs are involved in the accomplishment of these objectives: fish stock and investments become more volatile, which leads to more overcapacity.

Abstract A Gas–Solid Vortex Reactor (GSVR), in literature also referred to as Rotating Fluidized Bed in Static Geometry (RFB-SG), is a promising reactor type for Process Intensification (PI) with respect to reactor volume reduction. Although replacing gravitational by centrifugal force has been considered since the seventies, the hydrodynamics of the reactor flow and the bed behavior remain largely unknown. In the present work experiments have been carried out in a cold flow GSVR with diameter of 0.54 m, length of 0.1 m and 36 inlet slots of 2 mm. Gas injection velocities of 55–111 m/s and particles with densities of 950–1800 kg/m 3 and diameters of 1–2 mm have been applied. Depending on solids density, particle diameter and gas injection velocity the bed behavior can be considered as stable, semi-stable or unstable. For semi-stable and stable flow regimes the effect of the above process conditions on the maximum solids capacity was investigated. With increasing solids density, the bed stability considerably decreases, while the maximum solids capacity increases. By increasing the gas injection velocity, both the bed stability and the maximum solids capacity increase. Once bed stability is accomplished, a further increase of the gas injection velocity does not affect the maximum solids capacity. With increasing particle diameter, the bed stability decreases while the maximum solids capacity increases.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.