Browsing by Keyword "Energy"
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Item Aggregation of thermostatically controlled loads for flexibility markets(AIM, 2019-06) Jimeno, Joseba; Ruiz, Nerea; Madina, CarlosThis paper presents a tool for an aggregator of thermostatically controlled loads (TCLs) to optimally combine their flexibilities into a few representative bids to be submitted to flexibility markets. The tool employs a “bottom-up” approach based on physical end-use load models, being the individual flexibility of each individual TCL simulated with a second-order thermal model describing the dynamics of the house. The approach is based on a direct load control (DLC) of thermostat temperature set-point by the aggregator. End-users receive an economic compensation in exchange for the loss of comfort. The applicability of the proposed model is demonstrated in a simulation case study based on an actual power system in Spain.Item Energy meters in District-Heating Substations for Heat Consumption Characterization and Prediction Using Machine-Learning Techniques(2020-11-20) Lumbreras, Mikel; Garay, Roberto; Marijuan, Antonio Garrido; Tecnalia Research & Innovation; EDIFICACIÓN DE ENERGÍA POSITIVAThe use of smart energy meters enables the monitoring of large quantity of data related to heat consumption patterns in buildings connected to DH networks. This information can be used to understand the interaction between building and the final users´ without accurate information about building characteristics and occupational rates. In this paper an intuitive and clarifier data-driven model is presented, which couples heat demand and weather variables. This model enables the disaggregation of Space-Heating & Domestic Hot water demand, characterization of the total heat demand and the forecasting for the next hours. Simulations for 53 building have been carried out, with satisfactory results for most of them, reaching R2 values above 0.9 in some of them.Item Material saving by a combination of rotary forging and conventional processes: Hybrid forging for net-shape gear: Hybrid forging for net-shape gear(American Institute of Physics Inc., 2019-07-02) Varela, Sonia; Valbuena, Oscar; Armentia, Jorge; Larrucea, Francisco; Manso, Virginia; Santos, Maite; Arrazola, Pedro; Saenz de Argandona, Eneko; Otegi, Nagore; Mendiguren, Joseba; Saez de Buruaga, Mikel; Madariaga, Aitor; Galdos, Lander; PROMETAL; INDUSTRY_THINGS; SGIncreasing efficiency in raw material and energy usage is vital, even more in sectors, such as the hot forging industry, where material accounts for 50% of component price and energy costs are continuously rising. One of the methods to achieve this is to minimize material waste. Traditionally, high-quality gears for the automotive sector are machined to shape from forged preforms which is wasteful of both materials and energy. Attention has now turned to the forging of tooth gears by conventional forging. However, this could require high forging loads and therefore huge press sizes. Some gears may also be difficult to form due to the placement of their teeth. Forging of tooth gears is thus not a straightforward task. In this context, rotary forging is a powerful alternative. It uses incremental deformation locally with the material to achieve near net shape results, minimizing machining. Due to the reduction in contact, it also allows the forging load to be decreased substantially, resulting in smaller presses. This paper shows the development of the rotary forging process in combination with conventional forging to obtain crown gear teeth as a demonstration case. First, the hot conventional forging is shown, based on obtaining the rotary preform by a closed die forging operation. Then rotary forging is defined as a semi-finished operation to achieve the forged teeth. The objective is to reduce the initial billet weight, checking that folds and filling defects do not appear. A thermomechanical chained model has been developed based on FEM and experimental tests carried out in a pre-industrial environment. The prototypes result in increased yield from raw material (around 15% saving compared to machining) and they can be manufactured with less than 50% of the load required by conventional forging processes. Quality and metallographic requirements are also fulfilled.Item A Multi-objective Harmony Search Algorithm for Optimal Energy and Environmental Refurbishment at District Level Scale(Springer Singapore, 2017) Manjarres, Diana; Mabe, Lara; Oregi, Xabat; Landa-Torres, Itziar; Arrizabalaga, Eneko; Del Ser, Javier; Tecnalia Research & Innovation; IA; PLANIFICACIÓN ENERGÉTICANowadays municipalities are facing an increasing commitment regarding the energy and environmental performance of cities and districts. The multiple factors that characterize a district scenario, such as: refurbishment strategies’ selection, combination of passive, active and control measures, the surface to be refurbished and the generation systems to be substituted will highly influence the final impacts of the refurbishment solution. In order to answer this increasing demand and consider all above-mentioned district factors, municipalities need optimisation methods supporting the decision making process at district level scale when defining cost-effective refurbishment scenarios. Furthermore, the optimisation process should enable the evaluation of feasible solutions at district scale taking into account that each district and building has specific boundaries and barriers. Considering these needs, this paper presents a multi-objective approach allowing a simultaneous environmental and economic assessment of refurbishment scenarios at district scale. With the aim at demonstrating the effectiveness of the proposed approach, a real scenario of Gros district in the city of Donostia-San Sebastian (North of Spain) is presented. After analysing the baseline scenario in terms of energy performance, environmental and economic impacts, the multi-objective Harmony Search algorithm has been employed to assess the goal of reducing the environmental impacts in terms of Global Warming Potential (GWP) and minimizing the investment cost obtaining the best ranking of economic and environmental refurbishment scenarios for the Gros district.Item A new era in the energy performance of buildings(2017-11-01) de Agustin-Camacho, Pablo; Romero-Amorrortu, Ander; Krysinski, Dawid; Tecnalia Research & InnovationImproving energy efficiency in buildings is a major priority for the European Union, yet current modelling processes do not accurately reflect consumption. The MOEEBIUS framework will provide the basis for more accurate energy performance assessment, underpinning efforts to improve efficiency and opening up new commercial opportunities, as Dawid Krysiński explainsItem Rapid simulation models for aluminium furnaces design(2017-07-04) Anglada, Eva; Vicario, Iban; de Landia, Leonor; Mendizabal, Gorka; Toledo, Nagore; CIRMETAL; PROMETALThe minimisation of energy consumption in aluminium metal casting industries requires an appropriate design of the furnaces to reduce as possible the heat losses through the walls. Detailed simulation models have been developed that allow the in-depth study of furnace behaviour, but these models are too complex and slow for some industrial necessities. To make possible a fast evaluation during preliminary phases more agile models are needed. This agility may be achieved by simplified models, but the results could be affected by a lack of accuracy. The work presented hereafter shows how the steady state analysis of the furnace walls with simplified models of finite elements may give sufficiently accurate and fast results. The simulation models have been validated against experimental results, thus confirming their ability to adequately reproduce the thermal behaviour of the walls of several furnaces regardless of their composition or heating system.Item Reducing variability in the cost of energy of ocean energy arrays(2019-09) Topper, Mathew B.R.; Nava, Vincenzo; Collin, Adam J.; Bould, David; Ferri, Francesco; Olson, Sterling S.; Dallman, Ann R.; Roberts, Jesse D.; Ruiz-Minguela, Pablo; Jeffrey, Henry F.; Tecnalia Research & Innovation; RENOVABLES OFFSHOREVariability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.Item Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level(2019) Manjarres, Diana; Mabe, Lara; Oregi, Xabat; Landa-Torres, Itziar; Tecnalia Research & Innovation; IA; PLANIFICACIÓN ENERGÉTICAEnergy efficiency and environmental performance optimization at the district level are following an upward trend mostly triggered by minimizing the Global Warming Potential (GWP) to 20% by 2020 and 40% by 2030 settled by the European Union (EU) compared with 1990 levels. This paper advances over the state of the art by proposing two novel multi-objective algorithms, named Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Harmony Search (MOHS), aimed at achieving cost-effective energy refurbishment scenarios and allowing at district level the decision-making procedure. This challenge is not trivial since the optimisation process must provide feasible solutions for a simultaneous environmental and economic assessment at district scale taking into consideration highly demanding real-based constraints regarding district and buildings’ specific requirements. Consequently, in this paper, a two-stage optimization methodology is proposed in order to reduce the energy demand and fossil fuel consumption with an affordable investment cost at building level and minimize the total payback time while minimizing the GWP at district level. Aimed at demonstrating the effectiveness of the proposed two-stage multi-objective approaches, this work presents simulation results at two real district case studies in Donostia-San Sebastian (Spain) for which up to a 30% of reduction of GWP at district level is obtained for a Payback Time (PT) of 2–3 years.