A5076610331- Water resources management and optimization
- Water Systems and Optimization
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Flood Risk Assessment and Management
- Water-Energy-Food Nexus Studies
- Smart Grid Energy Management
- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Hydraulic and Pneumatic Systems
- Energy Load and Power Forecasting
- Advanced Multi-Objective Optimization Algorithms
- Electric Power System Optimization
- Smart Grid Security and Resilience
- Hydrological Forecasting Using AI
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Soil Moisture and Remote Sensing
- Power Systems and Technologies
- Infrastructure Resilience and Vulnerability Analysis
- Financial Risk and Volatility Modeling
- Integrated Energy Systems Optimization
- Child Nutrition and Water Access
- Water Quality Monitoring Technologies
- Spatial and Panel Data Analysis
National Technical University of Athens
2016-2025
City University of New York
2014
An operational framework for flood risk assessment in ungauged urban areas is developed within the implementation of EU Floods Directive Greece, and demonstrated Volos metropolitan area, central which frequently affected by intense storms causing fluvial flash floods. A scenario-based approach applied, accounting uncertainties key modeling aspects. This comprises extreme rainfall analysis, resulting spatially-distributed Intensity-Duration-Frequency (IDF) relationships their confidence...
As the share of renewable energy resources rapidly increases in electricity mix, recognition, representation, quantification, and eventually interpretation their uncertainties become important. In this vein, we propose a generic stochastic simulation-optimization framework tailored to systems (RES), able address multiple facets uncertainty, external internal. These involve system's drivers (hydrometeorological inputs) states (by means fuel-to-energy conversion model parameters market price),...
The development of accurate precipitation products with wide spatio-temporal coverage is crucial for a range applications. In this context, data merging (PDM) that entails the blending satellite-based estimates ground-based measurements holds prominent position, while currently there an increasing trend in deployment machine learning (ML) algorithms such endeavors. light recent advances field, work discusses key aspects PDM problem associated with: a) conceptual formulation problem, closely...
Accurate water level prediction is essential for flood risk management, resources inland transportation and climate resilience. Traditional statistical methods, such as autoregressive models, physically-based hydrological simulations, have been widely used in forecasting. However, these approaches often struggle to capture complex, dynamic, nonlinear interactions a system, particularly those affected by change. In recent years, machine learning models emerged promising alternative, offering...
Flood nowcasting at detailed, fine spatiotemporal scales is crucial for the deployment of reliable warning systems, especially in built-up environments where majority socio-economic activity concentrated. These are also characterized by significant complexities that require sufficient detail, up to street level. The derivation flood maps early systems can be organized via three main pillars: a) rainfall high resolution, typically obtained from weather radars; b) physics-based mechanistic...
Residential water demand consists one of the most uncertain factors posing extra difficulties in efficient planning and management urban systems. Currently, high resolution data from smart meters provide means for a better understanding modelling this variable at household level fine temporal scales. Having mind, paper examines statistical distributional properties residential 15-minute hourly scale, which are scales interest majority modeling applications. Towards this, we investigate large...
Stochastic simulation has a prominent position in variety of scientific domains including those environmental and water resources sciences. This is due to the numerous applications that can benefit from it, such as risk-related studies. In domains, stochastic models are typically used generate synthetic weather data with desired properties, often resembling hydrometeorological observations, which then drive deterministic understudy system. However, generating properties not an easy task....
Uncertainty-aware design and management of urban water systems lies on the generation synthetic series that should precisely reproduce distributional dependence properties residential demand process (i.e., significant deviation from Gaussianity, intermittent behaviour, high spatial temporal variability a variety structures) at various scales operational interest. This is importance since these govern dynamics overall system, while prominent simulation methods, such as pulse-based schemes,...
Complex environmental optimization problems often require computationally expensive simulation models to assess candidate solutions. However, the complexity of response surfaces necessitates multiple such assessments and thus renders search procedure too laborious. Surrogate-based is a powerful approach for accelerating convergence towards promising Here we introduce Adaptive Multi-Surrogate Enhanced Evolutionary Annealing Simplex (AMSEEAS) algorithm, as an extension its precursor SEEAS,...
Fluvial floods are one of the primary natural hazards to our society, and associated flood risk should always be evaluated for present future conditions. The European Union’s (EU) Floods Directive highlights importance mapping as a key stage detecting vulnerable areas, assessing floods’ impacts, identifying damages compensation plans. implementation EU Flood in Greece is challenging because its geophysical climatic variability diverse hydrologic hydraulic This study addressed this challenge...
We propose a novel probabilistic approach to flood hazard assessment, aiming address the major shortcomings of everyday deterministic engineering practices in computationally efficient manner. In this context, principal sources uncertainty are defined across overall modeling procedure, namely, statistical inferring annual rainfall maxima through distribution models that fitted empirical data, and inherently stochastic nature underlying hydrometeorological hydrodynamic processes. Our work...
Efficient water and energy use in distribution systems is being limited by the lack of sufficient data about related consumption. Therefore, it crucial to provide updated continuous feedback information users. This paper describes relevant cases improve efficient consumption utilities consumers through smart metering technologies. A systematic approach was established obtain a comprehensive list possible functionalities, using concept case. For consumer domain, six high-level 18...
Optimizing the design and operation of an Urban Water System (UWS) faces significant challenges over its lifespan to account for uncertainties important stressors that arise from population growth rates, climate change factors, or shifting demand patterns. The analysis a UWS’s performance across interdependent subsystems benefits multi-model approach where different designs are tested against variety metrics in times scales each subsystem. In this work, we present stress-testing framework...
Abstract. Motivated by the challenges induced so-called Target Model and associated changes to current structure of energy market, we revisit problem day-ahead prediction power production from Small Hydropower Plants (SHPPs) without storage capacity. Using as an example a typical run-of-river SHPP in Western Greece, test alternative forecasting schemes (from regression-based machine learning) that take advantage different levels information. In this respect, investigate whether it is...
The advent of ICT services on water sector offers new perspective towards sustainable management. This paper presents an innovative web-based platform, targeting primarily the household end-users. platform enables consumers to monitor and control, real-time basis, energy consumption their providing valuable information feedback. At same time, further supports end-users modify improve profile via interactive educational process that comprises a variety on-line tools applications. discusses...
The increase of available data on household water consumption is expected to bring a new awareness practices. Such needs be further supported by customized advice the household. This paper presents development Moodle-based eLearning platform that aims support end-users understand, manage and hopefully change their energy profile. structure components platform, including, inter alia, FAQ's, quizzes tips whereas more focus given two most advanced web application for exploration domestic demand...
Abstract Water smart metering enables the measurement and reporting of water consumption at sub-daily intervals. However, assuming that increased availability information will necessarily result in changed behaviour is simplistic. The main scientific challenges for iWIDGET project are management extraction useful from vast amounts high-resolution data, development customized to influence awareness support behavioral change, integration concepts into a set decision-support tools utilities...
This paper presents the set-up and application of Bartlett-Lewis clustering mechanism to simulate residential water demand at fine, i.e. sub-hourly, time scales. Two different variants model, i.e., original random-parameter are examined. The models assessed in terms preserving main statistical characteristics temporal properties series a range fine scales, from 1-min up 15-min. comparison against typical Poisson rectangular pulse model showed that enables better reproduction levels...