Cristina Martin

Vicomtech · Digital Health & Biomedical Technologies

A rise in the number of EVs (electric vehicles) in Europe is putting pressure on power grids. At an urban scale, Positive Energy Districts (PEDs) are devised as archetypes of (small) urban districts managing a set of interconnected buildings and district elements (lighting system, vehicles, smart grid, etc.). This paper offers a comprehensive analy...

This article presents preliminary results that assess the effect of electromobility in an archetype Positive Energy District (PED). We present a PED modelling approach that represents renewable energy generation, an energy storage system, the consumption of residential and non-residential buildings, smart lighting services, and the inclusion of ele...

La urgencia del cambio climático está demandando nuevos procesos de transición energéti- ca que acelerarán el desarrollo soluciones innovadoras. Este artículo propone una nueva metodología en tres pasos que acompañará procesos de transición energética. En primer lu- gar, el diseño de espacios urbanos de acuerdo al concepto de Distrito de Energía Po...

The urgency of climate change is demanding new urban energy transition processes that will be accelerated by the implementation of innovative urban solutions. This paper propos- es a three-step methodology to encompass the energy transition in cities. Firstly, the design of urban spaces in accordance to Positive Energy District (PED) concept is def...

Este número cuenta con ocho artículos académicos, acompañados por dos policy letters, que tratan temas relevantes de la transición energética y que permiten tener una imagen más completa de las implicaciones del proceso de transición energética para el País Vasco. Además de analizar el impacto económico de la transición energética, se abordan aspec...

The daily analysis of loads is one of the most important activities for power utilities in order to be able to meet the energy demand. This analysis not only includes short-term forecasting but it also encompasses the completion of missing load data, known as imputation. In this work we show that adding information of attached or bordering primary...

In this work the kinetic modelling of the transformation of Bioethanol-To-Olefins (BTO) process over a HZSM-5 catalyst treated with alkali using Artificial Neural Networks (ANN) is presented. The main goal has been to obtain a BTO process neuronal model with the desired accuracy that allows the simplification and reduction of the computational cost...

This paper presents a study on dynamic optimization of the catalytic transformation of Bioethanol-To-Olefins process. The main objective is to maximize the total production of Olefins by calculating simultaneously the optimal control trajectories for the main operating variables of the process. Using Neural Networks trained with two different types...

Deployment and maintenance of Smart Homes and Smart Grids in real environments is an expensive and lengthy process. In this paradigm, simulations play an important role by providing means of emulating the behaviour of the aforementioned systems. However, these simulations may suffer from lack of accuracy due to the inability to properly reproduce t...

We present a methodology to improve the estimation of several Sustainability Indicators based on the measurement of walking distance to infrastructures combining Agent Based Simulation with Volunteer Geographic Information. Joining these two forces we construct a more realistic and accurate distribution of the infrastructures based on knowledge cre...

The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental conseque...

This paper presents a strategy for the optimisation of the operational conditions of the catalytic transformation of Bioethanol into Olefins (BTO) process. The variables to optimise are the main operating variables of the process (temperature, space-time and water content in the feed), and the objective function is to maximise the total production...

This paper makes a critical review of the available techniques for analysing, completing and generating influent data for WWTP modelling. The solutions found in literature are classified according to three different situations from engineering practice: 1) completing an incomplete dataset about the quantity and quality of the influent wastewater; 2...

The success of many modelling studies strongly depends on the availability of sufficiently long influent time series-the main disturbance of a typical wastewater treatment plant (WWTP)-representing the inherent natural variability at the plant inlet as accurately as possible. This is an important point since most modelling projects suffer from a la...

In this work we present a comparison of several Artificial Neural Networks weights initialization methods based on Evolutionary Algorithms. We have tested these methods on three datasets: KEEL regression problems, random synthetic dataset and a dataset of concentration of different chemical species from the Bioethanol To Olefins process. Results de...

While the general principles and modelling approaches for integrated management/modelling of urban water systems already present a decade ago still hold, in recent years aspects like model interfacing and wastewater treatment plant (WWTP) influent generation as complements to sewer modelling have been investigated and several new or improved system...

Dimensioning a wastewater treatment plant (WWTP) using design guidelines requires a set of input factors. However, the information regarding these input factors might be very scarce during the initial stage of design. Therefore these input factors are usually associated with significant uncertainty. In this study, global sensitivity analysis (GSA)...

This paper presents CalHidra 3.0, a new software package developed for dynamic simulation of water quality in rivers. CalHidra 3.0 combines a 1-D hydrodynamic model based on Saint Venant equations, a transport sub-model that incorporates the advection–dispersion terms, and a simplified version of the River Water Quality Model 1 (RWQM1) for the bioc...

The urban heat island (UHI) is a well-known effect of urbanisation and is particularly important in world megacities. Overheating in such cities is expected to be exacerbated in the future as a result of further urban growth and climate change. Demonstrating and quantifying the impact of individual design interventions on the UHI is currently diffi...

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the...

This paper presents a new model for the dynamic prediction of water quality in rivers using in-series continuously stirred tank reactors (CSTR) and process transformations based on the IWA RWQM1. The transport model introduces a new parameter f (fraction of solids that are not retained in the in-series reactors) that splits hydraulic and solids ret...

This paper presents the application of a robust non-diagonal multivariable control design method, based on the Quantitative Feedback Theory (QFT), to the control of a complex wastewater treatment plant (WWTP) with biological removal of nitrogen and phosphorus. The control objective is to simultaneously regulate the concentration of ammonia, nitrate...