Henrik Madsen

Henrik Madsen
Technical University of Denmark | DTU · Department of Applied Mathematics and Computer Science

Professor, PhD

About

785
Publications
148,525
Reads
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17,302
Citations
Introduction
Professor in Stochastic Dynamical Systems, Technical University of Denmark. Head of a National Strategic Research Centre: Centre for IT-Intelligent Energy Systems (CITIES). Main interests related to analysis and modeling of stochastic dynamical systems including time series analysis, model building, estimation, grey box modeling, probabilistic forecasting and control. Applications related to energy systems, informatics, environmental systems, pharmaceutical systems, biostatistics, and finance.
Additional affiliations
January 1998 - present
Novo Nordisk
Description
  • Research Collaboration, Pharmaceutical Modelling
January 1980 - December 2012
Technical University of Denmark
Description
  • Time series analysis, forecasting, modelling, stochastic differential equations modelling, grey-box modelling, wind power forecasting, smart cities, modelling heat dynamics of buildings, PK/PD modellen, pharmaceutical modelling, stochastic control

Publications

Publications (785)
Article
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The Kluzniak & Abramowicz model explains high frequency, double peak, "3:2" QPOs observed in neutron star and black hole sources in terms of a non-linear parametric resonance between radial and vertical epicyclic oscillations of an almost Keplerian accretion disk. The 3:2 ratio of epicyclic frequencies occurs only in strong gravity. Rebusco (2004)...
Article
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: Neglecting the non-constant variance, if any, of the residuals of a linear regression model may lead to an arbitrarily large loss of asymptotic e#ciency and, subsequently, low power of statistical tests, i.e. model diagnostics tests. A number of models of conditional variance of the Generalized AutoRegressive Conditional Heteroscedasticity (GARCH...
Article
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The prediction-based estimating functions proposed by (Srensen, 1999) are generalized to facilitate parameter estimation in discretely observed stochastic differential equations, where the observations are corrupted by additive white noise. The new class of estimating functions has most of the nice properties of martingale estimating functions. How...
Article
Demand-side flexibility will play a key role in reaching high levels of renewable generation and making the transition to a more sustainable energy system. Indeed, end users can actively contribute to grid balancing and management, if equipped with energy management systems and communication infrastructure. Demand response programmes encompass a br...
Article
Flexible and responsive demand is key to the decarbonising of energy systems. In this paper, an economic dispatch model of a district heating system, modelled as a linear program, is soft-linked to a so-called flexibility function of end-consumer responses to time-varying heat prices, modelled generically as a set of ordinary differential equations...
Article
Low-cost sensors (LCS) are becoming ubiquitous in the market; however, calibration is needed before reliable use. An evaluation of the calibration of eight identical pre-calibrated formaldehyde LCS is presented here. The LCS and a reference instrument were exposed to a pollutant source(s) for the calibration measurements. After one year, some tests...
Article
Building archetypes are a common solution to study the energy demand of cities and districts. These are generally based on building information such as construction year and function. However, there can be large differences in the energy demand of buildings of the same archetype due to factors such as the preferences of occupants, quality of the bu...
Article
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This paper proposes non-linear autoregressive models with exogenous inputs to model the air temperature in each room of a Danish school building connected to the local district heating network. To obtain satisfactory models, the authors find it necessary to estimate the solar radiation effect as a function of the time of the day using a B-spline ba...
Article
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To reach the carbon emission reduction targets set by the European Union, the building sector has embraced multiple strategies such as building retrofit, demand side management, model predictive control and building load forecasting. All of which require knowledge of the building dynamics in order to effectively perform. However, the scaling-up of...
Preprint
Full-text available
In many applications, e.g. fault diagnostics and optimized control of supermarket refrigeration systems, it is important to determine the heat demand of the cabinets. This can easily be achieved by measuring the mass flow through each cabinet, however, that is expensive and not feasible in large-scale deployments. Therefore it is important to be ab...
Article
The increasing proportion of renewable energy sources in power grids leads to challenges concerning balancing production and consumption. One solution to this grid challenge is to utilize demand-side flexibility. To use the full potential of demand-side flexibility, dynamical models and optimal control methods must be used. This paper demonstrates...
Article
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CO2 is customarily used to control ventilation as it is a proxy for bio-effluents and pollutants related to the presence and activity of people in the room. However, CO2 could not be a satisfactory indicator for pollutants that do not have a metabolic origin, i.e., emissions from building materials or emissions from traffic. A methodology to select...
Conference Paper
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The rapid growth of machine learning (black-box) techniques and computing capacity has started to transform many research domains, including building performance analysis. However, physical interpretation of these models remains a challenge due to their opaque nature. This paper outlines an experiment to unveil analytical expressions from an open-s...
Article
In this paper, an extensive study of Renewable Energy Communities and their potential impact on the electric distribution grid has been carried out. For that purpose, a Linear Programming optimization model sizing the energy community’s Photo-Voltaic and Battery Energy Storage System was developed. The linear programming model was soft coupled with...
Conference Paper
Full-text available
Zero-emission ships (ZE-ships) concept has been introduced as a promising solution in reducing the greenhouse gases (GHG) emission in marine shipping industry. Among different solutions, Fuel cells (FCs) are introduced as one of the most efficient technologies for providing the propulsion force of the ZE-ships. Energy storage systems (ESSs) are als...
Article
Smart meters implemented at the end-user in the energy sector create the opportunity to develop data-intelligent methods for district heating systems by using a large amount of fine-granular heat consumption time series from end-users. The current state-of-the-art methods for temperature control in district heating systems rely on predefined critic...
Preprint
Full-text available
Systems that rely on forecasts to make decisions, e.g. control or energy trading systems, require frequent updates of the forecasts. Usually, the forecasts are updated whenever new observations become available, hence in an online setting. We present the R package onlineforecast that provides a generalized setup of data and models for online foreca...
Article
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This paper introduces a non-linear grey-box (GB) model based on stochastic differential equations that describes the heat dynamics of a school building in Denmark, equipped with a water-based heating system. The building is connected to a local district heating network through a heat exchanger. The heat is delivered to the rooms mainly through radi...
Article
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Real-time fault monitoring and control of the Vacuum Assisted Resin Transfer Moulding production process requires knowledge of the position of the epoxy flow-front inside the mould. Therefore, a fast and accurate flow-front tracking system is highly prized. Physics-informed grey-box models deliver a good trade-off between high fidelity and data-dri...
Article
Despite the simplicity of the Duffing oscillator, its dynamical behaviour is extremely rich. Hence, the Duffing equations are used to describe the dynamic behaviour of many real-world nonlinear systems for a wide range of frequency bands and amplitude of the excitation signal in basic sciences and engineering. For example, the Duffing oscillator ha...
Article
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Due to the carbon neutral goals in many countries, a shift from traditional fuels to biomass is currently taking place in the energy sector. In this publication, we are looking at the long-term biomass contracting decisions for combined heat and power plants and power producers. A major share of biomass contracts are long-term contracts with runtim...
Article
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We describe a method for embedding advanced weather disturbance models in model predictive control (MPC) of energy consumption and climate management in buildings. The performance of certainty-equivalent controllers such as conventional MPC for smart energy systems depends critically on accurate disturbance forecasts. Commonly, meteorological forec...
Article
Heat load forecasts are crucial for energy operators in order to optimize the energy production at district heating plants for the coming hours. Furthermore, forecasts of heat load are needed for optimized control of the district heating network since a lower temperature reduces the heat loss, but the required heat supply at the end-users puts a lo...
Article
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The wide spread of district heating in Denmark offers a massive potential for flexibility in an energy system with intermittent renewable energy production. To leverage this potential, a cost-efficient power market integration of combined heat and power (CHP) units in district heating systems is important. We propose a stochastic program optimizing...
Article
In future smart energy systems, consumers are expected to change their load patterns as they become a significant source of flexibility. To ensure reliable load profile forecasts for long-term energy planning, conventional classification approaches will not hold and more advanced solutions are required. In this article, we propose an automatic, dat...
Article
Full-text available
Probabilistic forecasting is becoming increasingly important for a wide range of applications, especially for energy systems such as forecasting wind power production. A need for proper evaluation of probabilistic forecasts follows naturally with this, because evaluation is the key to improving the forecasts. Although plenty of excellent reviews an...
Article
This study presents a general model predictive control (MPC) algorithm for optimizing wastewater aeration in Water Resource Recovery Facilities (WRRF) under different management objectives. The flexibility of the MPC is demonstrated by controlling a WRRF under four management objectives, aiming at minimizing: (A) effluent concentrations, (B) electr...
Article
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Combining forecasts from multiple temporal aggregation levels exploits information differences and mitigates model uncertainty, while reconciliation ensures a unified prediction that supports aligned decisions at different horizons. It can be challenging to estimate the full cross-covariance matrix for a temporal hierarchy, which can easily be of v...
Article
Full-text available
Smart and flexible operation of components in district heating systems can play a crucial role in integrating larger shares of renewable energy sources in energy systems. Buildings are one of the crucial components that will enable flexibility in the district heating by using intelligent operation. Recent work suggests that such improved operation...
Article
Full-text available
The focus on energy conservation in buildings is increasing. Despite that, the yearly building renovation rate is only at around 1 %. To increase the renovation rate, new and time-efficient methods used for screening of large building portfolios’ energy saving potential are needed. In this paper, a re-engineered take on the classical energy signatu...
Chapter
Full-text available
The future energy system is weather-driven. To take full and effective advantage of the renewable energy production, we need to make the demand flexible, such that it better coincides with the weather-driven energy production. We argue that this disruption of the energy system implies a need for new planning and control methodologies for the energy...
Article
Full-text available
A key aspect for achieving a high-accuracy Photovoltaic (PV) power simulation, and reliable digital twins, is a detailed description of the PV system itself. However, such information is not always accurate, complete, or even available. This work presents a novel approach to learn features of unknown PV systems or subsystems using genetic algorithm...
Article
To accommodate the increasing amount of renewable energy sources in electricity grids it is crucial to utilize the flexibility of all electricity consumers. Municipal wastewater treatment plants consume approximately 1 % of the electricity consumption of a country’s total electricity consumption, to reduce nutrient concentrations from the incoming...
Article
Full-text available
Due to the new carbon neutral policies, many district heating operators start operating their combined heat and power plants using different types of biomass instead of fossil fuel. The contracts with the biomass suppliers are negotiated months in advance and involve many uncertainties from the energy producer’s side. The demand for biomass is unce...
Article
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We propose a bidding method for the participation of combined heat and power (CHP) units in the day-ahead electricity market. More specifically, we consider a district heating system where heat can be produced by CHP units or heat-only units, e.g., gas or wood chip boilers. We use a mixed-integer linear program to determine the optimal operation of...
Article
With the aim of enabling effective flexible electricity demand, a machine learning algorithm is developed to forecast the CO2 emission intensities in European electrical power grids distinguishing between average and marginal emissions. The analysis focuses on Danish bidding zone DK2 and was done on a data set comprised of a large number (473) of e...
Article
Full-text available
Buildings account for a large portion of the total energy consumption and they might serve as a significant thermal storage capacity that can be advantageous for the future energy grid. To utilise this capacity, it is necessary to characterise the thermal dynamics in buildings using methods that are general enough to be applicable to a significant...
Article
Full-text available
If CO2-emissions are to be reduced, the shares of renewable energy sources will have to be significantly increased. However, energy flexibility is required to cope with the increased share of renewable energy. Utilising it necessitates mathematical models of the operational response of energy flexible consumers. In this paper we present an accurate...
Article
Renewable energy integration in power systems and increasing electri cation of energy demand create new challenges to which energy exibility can provide effective solutions. Trough an innovative use of cumulative energy consumption curves, which represent the maximum and minimum energy limits, as well as the associated exible energy consumption, th...
Article
Full-text available
In Europe, more and more data on building energy use will be collected in the future as a result of the energy performance of buildings directive (EPBD), issued by the European Union. Moreover, both at European level and globally it became evident that the real energy performance of new buildings and the existing building stock needs to be document...
Article
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Smart grid operation schemes can integrate prosumers by offering economic rewards in exchange for the desired response. In order to activate prosumers appropriately, such operation schemes require models of the dynamic uncertain price-response relationships. In this study, we combine the system identification of nonlinear dynamics with control (SIN...
Article
Full-text available
An integrated Model Predictive Control (MPC) strategy to control the power consumption and the effluent quality of a Water Resource Recovery Facility (WRRF) by utilizing the storage capacity from the sewer system was implemented and put into operation for a 7 days trial period. This price-based MPC reacted to electricity prices and forecasted pollu...
Article
Full-text available
An optimized heat pump control for building heating was developed for minimizing CO 2 emissions from related electrical power generation. The control is using weather and CO 2 emission forecasts as inputs to a Model Predictive Control (MPC)—a multivariate control algorithm using a dynamic process model, constraints and a cost function to be minimiz...
Preprint
Full-text available
An optimized heat pump control for building heating was developed for minimizing CO2 emissions from related electrical power generation. The control is using weather and CO2 emission forecasts as input to a Model Predictive Control (MPC) - a multivariate control algorithm using a dynamic process model, constraints and a cost function to be minimize...
Chapter
Obtaining reliable, secure and efficient software under optimal resource allocation is an important objective of software engineering science. This work investigates the usage of classical and recent development paradigms of computational intelligence (CI) to fulfill this objective. The main software engineering steps asking for CI tools are: produ...
Preprint
A machine learning algorithm is developed to forecast the CO2 emission intensities in electrical power grids in the Danish bidding zone DK2, distinguishing between average and marginal emissions. The analysis was done on data set comprised of a large number (473) of explanatory variables such as power production, demand, import, weather conditions...
Article
Full-text available
The operation of electric and heat grids alike is complicated due to the dynamic demand, with the increasing penetration of renewable energy sources adding to the problem. In order to improve the integration of variable renewable energy sources, the flexibility of the system needs to be improved. This paper proposed a novel characterization of the...
Article
Hidden Markov models are applied in many expert and intelligent systems to detect an underlying sequence of persistent states. When the model is misspecified or misestimated, however, it often leads to unrealistically rapid switching dynamics. To address this issue, we propose a novel estimation approach based on clustering temporal features while...
Article
Full-text available
In order to integrate large shares of variable renewable energy sources, district heating can play an important role. Furthermore, in order to increase the efficiency of district heating systems, interconnecting adjacent system could be socio-economically justified. In order to assess the economic and environmental consequences of the latter, a mix...
Chapter
The deployment of technological pilots is of paramount importance for testing and demonstrating the technical feasibility of the concepts described in this book for two main reasons. On the one hand, there are few real-life experiences in the application of these concepts, as TSO-DSO coordination is a relatively new topic. On the other hand, there...
Article
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Model predictive control (MPC) has been applied in multiple ways to the load–frequency control problem. In this study, the authors illustrate and compare a target‐adjusted MPC to a classical MPC formulation. The target‐adjusted approach is also posed as optimal control law. The target‐adjusted MPC is an alternative formulation that incorporates the...
Article
Full-text available
Modelling the effects of solar irradiation plays an important role in various applications. This paper describes a semi-parametric (combined grey-box and spline-based), data-driven technique that can be used to model systems in which the solar gain depends on the sun position. The solar gain factor is introduced, i.e. the absorbed fraction of measu...
Article
Full-text available
In this article, model predictive control is used to dynamically optimize an investment portfolio and control drawdowns. The control is based on multi-period forecasts of the mean and covariance of financial returns from a multivariate hidden Markov model with time-varying parameters. There are computational advantages to using model predictive con...
Article
Full-text available
This work presents a novel occupancy simulation model for residential buildings. The main contribution is that occupancy is simulated at room level, as opposed to more course spatial resolutions in previous studies. The model is based on a time-use survey conducted in Denmark including several thousand households. It is formulated as an inhomogeneo...