Henrik Madsen

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

Professor, PhD

About

854
Publications
195,972
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
21,844
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 (854)
Article
Full-text available
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
Full-text available
: 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
Full-text available
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
Full-text available
District heating (DH) systems are an important component in the EU strategy to reach the emission goals, since they allow an efficient supply of heat while using the advantages of sector coupling between different energy carriers such as power, heat, gas and biomass. Most DH systems use several different types of units to produce heat for hundreds...
Preprint
Full-text available
Renewable Energy Sources play a key role in smart energy systems. To achieve 100% renewable energy, utilizing the flexibility potential on the demand side becomes the cost-efficient option to balance the grid. However, it is not trivial to exploit these available capacities and flexibility options profitably. The amount of available flexibility is...
Article
A novel data-driven model for forecasting the sludge blanket height in secondary clarifiers is presented. The model is trained on sensor measurements of the sludge blanket height and used as inputs such as (1) the clarifier feed flow rate, (2) feed suspended solids concentration, and (3) the clarifier recycle flow rate. The model’s prediction accur...
Preprint
Full-text available
This paper proposes an adaptive mechanism for price signal generation using a piecewise linear approximation of a flexibility function with unknown parameters. In this adaptive approach, the price signal is parameterized and the parameters are changed adaptively such that the output of the flexibility function follows the reference demand signal pr...
Preprint
Full-text available
Demand-side management provides a great potential for improving the efficiency and reliability of energy systems. This requires a mechanism to connect the market level and the demand side. The flexibility function is a novel approach that bridges the gap between the markets and the dynamics of physical assets at the lower levels of the energy syste...
Article
Full-text available
Weather forecasts are essential for district heating (DH) utility operations as they prepare the utility for future consumption, thus ensuring optimal operation by supplying sufficient heat while keeping costs low. Weather forecasts are usually converted into heat demand forecasts, which are used for production planning and control of the temperatu...
Article
Model predictive controllers are becoming widespread in building thermal dynamic control and energy management systems. Decreasing building energy consumption, load shifting, cost reduction, and indoor air quality improvement are some of the topics that these controllers have been shown to be efficient. However, they rely on accurate models that ar...
Article
Full-text available
To meet carbon emission reduction goals in line with the Paris agreement, planning resilient and sustainable energy systems has never been more important. In the building sector, particularly, strategic urban energy planning engenders large optimization problems across multiple spatiotemporal scales leading to necessary system scope simplifications...
Article
Full-text available
Within the field of statistical modelling and data-driven characterisation of buildings’ energy performance, the focus is typically on parameter estimation of the building envelope and the energy systems. Less focus has been put on the stochastic human effect on energy consumption. We propose a new method for estimating the thermal building propert...
Article
Full-text available
Optimal decision-making compels us to anticipate the future at different horizons. However, in many domains connecting together predictions from multiple time horizons and abstractions levels across their organization becomes all the more important, else decision-makers would be planning using separate and possibly conflicting views of the future....
Article
Full-text available
Accurately predicting and balancing energy generation and consumption are crucial for grid operators and asset managers in a market where renewable energy is increasing. To speed up the process, these predictions should ideally be performed based only on on-site measured data and data available within the monitoring platforms, data which are scarce...
Article
Full-text available
Increasing levels of distributed generation (DG), as well as changes in electricity consumption behavior, are reshaping power distribution systems. These changes might place particular stress on the secondary low-voltage (LV) distribution systems not originally designed for bi-directional power flows. Voltage violations, reverse power flow, and con...
Article
Full-text available
We consider reconciliation of wind power forecasts in a spatial hierarchy with three aggregation levels. We produce base forecasts for the bottom level consisting of 407 substations (connection points for local groups of wind turbines). State‐of‐the‐art forecasts from a commercial forecast provider are available for the middle and top levels, which...
Preprint
Full-text available
To meet carbon emission reduction goals in line with the Paris agreement, planning resilient and sustainable energy systems has never been more important. In the building sector, particularly, strategic urban energy planning engenders large optimization problems across multiple spatiotemporal scales leading to necessary system scope simplifications...
Chapter
Data quality has a strong effect on the design, validation and testing of decision-making systems. New paradigms of future models in the knowledge society need to analyze clean, complete, consistent, and high-quality data. This paper presents three case studies from different fields in which models are constructed using machine learning strategies....
Preprint
Full-text available
Many sectors nowadays require accurate and coherent predictions across their organization to effectively operate. Otherwise, decision-makers would be planning using disparate views of the future, resulting in inconsistent decisions across their sectors. To secure coherency across hierarchies, recent research has put forward hierarchical learning, a...
Article
Full-text available
Swimming pool heating systems are known as one of the best flexible resources in buildings. However, they can be flexible only for a certain number of hours throughout a day due to the comfort constraints of the users. In this study, a new approach is proposed to determine a group of contract hour sets to procure maximum flexibility of swimming poo...
Preprint
Full-text available
Optimal decision-making compels us to anticipate the future at different horizons. However, in many domains connecting together predictions from multiple time horizons and abstractions levels across their organization becomes all the more important, else decision-makers would be planning using separate and possibly conflicting views of the future....
Conference Paper
Full-text available
Building thermal modeling is the founding stone upon which numerous carbon reduction strategies in the building sector are built. Yet, as of today, little to no interpretable and calibrated models founded on real-world measurements have been open-sourced. This work attempts to remedy this deficiency and renders public improved results of a recentl...
Article
The future of electricity markets is envisioned to be heavily based on renewable generation and distributed flexibility. Yet, integrating existing distributed flexibility into market decisions poses a major challenge, given the diversity of consumers' modeling frameworks and controllers. Moreover, in such a system, the market's decisions need to be...
Preprint
Full-text available
This paper presents models for renewable energy systems with storage, and considers its optimal operation. We model and simulate wind and solar power production using stochastic differential equations as well as storage of the produced power using batteries, thermal storage, and water electrolysis. We formulate an economic optimal control problem,...
Article
This paper introduces a linear quadratic control scheme for a continuous-time system with observations taken at discrete times. Particular attention is given to the derivation of the disturbance terms in the model. Control performance may depend critical on accurate disturbance forecasts. This is the case for building climate control, where solar r...
Article
Full-text available
The paper presents the learnings from designing and running a model predictive control (MPC) of the heating system in a school building. Several real-life applications of MPC controlled heating have been presented in the literature. Most of them work by controlling the room temperature usingn a heating system and thus need a reference measured temp...
Article
Full-text available
Identifying the parameters of grey-box models requires enough data collected from sensors installed inside and outside of the building for long enough period of time. Consequently, this process is time consuming, costly especially in large buildings that require more sensors, and can only be conducted after the building is constructed. This paper i...
Preprint
District heating is an important component in the EU strategy to reach the set emission goals, since it allows an efficient supply of heat while using the advantages of sector coupling between different energy carriers such as power, heat, gas and biomass. Most district heating systems use several different types of units to produce heat for hundre...
Article
Smart meters at consumers create opportunities to improve operation of the district heating sector using data-driven methods. Information from these meter measurements carries the potential to increase the energy efficiency of both individual houses and the utility network, for example by identifying buildings with too high return temperature, or b...
Article
The intermittency of renewable energy sources, such as wind and solar, means that they require reliable and accurate forecasts to integrate properly into energy systems. This review introduces and examines a selection of state‐of‐the‐art methods that are applied for multivariate forecasting of wind and solar power production. Methods such as condit...
Article
Aiming to enable robust large-scale fault diagnostics and optimized control for supermarket refrigeration systems, a data-driven grey box model for an evaporator and its surrounding cooling cabinet (or room) is presented. It is a non-linear model with two states: the cabinet temperature and the refrigerant mass in the evaporator. To demonstrate its...
Article
Full-text available
Membrane-based separations are proven and useful industrial-scale technologies, suitable for automation. Digital twins are models of physical dynamical systems which continuously couple with data from a real world system to help understand and control performance. However, ultrafiltration and microfiltration membrane separation techniques lack a ri...
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
Demand side energy flexibility is increasingly being viewed as an essential enabler for the swift transition to a low-carbon energy system that displaces conventional fossil fuels with renewable energy sources while maintaining, if not improving, the operation of the energy system. Building energy flexibility may address several challenges facing e...
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
Full-text available
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
Sustainable urban drainage is an economically expensive necessity, partially due to the operation of water pumps. Reliable forecasting of stormwater response following a rainfall event has the potential to reduce those expenses, because it can be used in model predictive control schemes that optimize the energy consumption of pumps significantly be...
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
Full-text available
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
Full-text available
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
Full-text available
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
Full-text available
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...
Article
Full-text available
The landscape of buildings is a diverse one and long-term energy system planning requires simulation tools that can capture such diversity. This work proposes a model for simulating the space-heating consumption of buildings using a linear mixed-effects model. This modelling framework captures the noise caused by the differences that are not being...