Guaranteeing Input Tracking For Constrained Systems: Theory and Application to Demand Response

A method for certifying exact input trackability for constrained discrete time linear systems is introduced in this paper. A signal is assumed to be drawn from a reference set and the system must track this signal with a linear combination of its inputs. Using methods inspired from robust model predictive control, the proposed approach certifies the ability of a system to track any reference drawn from a polytopic set on a finite time horizon by solving a linear program. Optimization over a parameterization of the set of reference signals is discussed, and particular instances of parameterization of this set that result in a convex program are identified, allowing one to find the largest set of trackable signals of some class. Infinite horizon feasibility of the methods proposed is obtained through use of invariant sets, and an implicit description of such an invariant set is proposed. These results are tailored for the application of power consumption tracking for loads, where the operator of the load needs to certify in advance his ability to fulfill some requirement set by the network operator. An example of a building heating system illustrates the results.Comment: Technical Not

Predictive Control methods for Building Control and Demand Response

This thesis studies advanced control techniques for the control of building heating and cooling systems to provide demand response services to the power network. It is divided in three parts. The first one introduces the MATLAB toolbox OpenBuild which aims at facilitating the design and validation of predictive controllers for building systems. In particular, the toolbox constructs models of building that are appropriate for use in predictive controllers, based on standard building description data files. It can also generate input data for these models that allows to test controllers in a variety of weather and usage scenarios. Finally, it offers co-simulation capability between MATLAB and EnergyPlus in order to test the controllers in a trusted simulation environment, making it a useful tool for control engineers and researchers who want to design and test building controllers in realistic simulation scenarios. In the second part, the problem of robust tracking commitment is formulated: it consists of a multi-stage robust optimization problem for systems subject to uncertainty where the set where the uncertainty lies is part of the decision variables. This problem formulation is inspired by the need to characterize how an energy system can modify its electric power consumption over time in order to procure a service to the power network, for example Demand Response or Reserve Provision. A method is proposed to solve this problem where the key idea is to modulate the uncertainty set as the image of a fixed uncertainty set by a modifier function, which allows to embed the modifier function in the controller and by doing so convert the problem into a standard robust optimization problem. The applicability of this framework is demonstrated in simulation on a problem of reserve provision by a building. We finally detail how to derive infinite horizon guarantees for the robust tracking commitment problem. The third part of thesis reports the experimental works that have been conducted on the Laboratoire d'Automatique Demand Response (LADR) platform, a living lab equipped with sensors and a controllable heating system. These experiments implement the algorithms developed in the second part of the thesis to characterize the LADR platform flexibility and demonstrate the closed-loop control of a building heating system providing secondary frequency control to the Swiss power network. In the experiments, we highlight the importance of being able to adjust the power consumption baseline around which the flexibility is offered in the intraday market and show how flexibility and comfort trade off

Constrained bundle methods with inexact minimization applied to the energy regulation provision problem

We consider a class of large scale robust optimization problems. While the robust optimization literature often relies on structural assumptions to reformulate the problem in a tractable form using duality, this method is not always applicable and can result in problems which are very large. We propose an alternative way of solving such problems by applying a constrained bundle method. The originality of the method lies in the fact that the minimization steps in the bundle method are solved approximately using the alternating direction method of multipliers. Numerical results from a power grid regulation problem are presented and support the relevance of the approach

Economic study of the participation of multiple energy resources in grid services markets

This paper presents a method to analyze the technical and economic potential of combining different types of resources to provide grid services, with a particular focus on battery systems. The paper proposes a modelling paradigm where resources are described with few key operational parameters and describes a control architecture to co-operate the combination of resources to offer fast grid services, taking as an example the provision of secondary frequency control in the Swiss market. A sensitivity analysis is reported that highlights the ability of the combination of energy resources to provide grid services as a function of their technical characteristics

Fluorescence spectroscopy for characterization and differentiation of beers

Total luminescence and synchronous scanning fluorescence spectroscopic techniques were applied for characterization of the intrinsic fluorescence of eight different beers. Spectra were measured using different geometries to reveal the presence of similar fluorescent components. The total luminescence and synchronous fluorescence spectra exhibit a relatively intense short-wavelength emission ascribed to aromatic amino acids and less intense emission in the long-wavelength region, which may originate from B vitamins. Classification of beers based on their synchronous fluorescence spectra was performed using non-parametrical k nearest neighbours method and linear discriminant analysis. Very good discrimination was obtained in both methods with a low classification error. The results demonstrate the potential of fluorescence techniques to characterize and differentiate beers

Robust Tracking Commitment with Application to Demand Response

Many engineering problems that involve hierarchical control applications, such as demand side ancillary service provision to the power grid, can be posed as an optimal tracking commitment problem. In this setting, the lower- level controller commits a set of possible reference trajectories over a finite horizon to an external entity, which requires guaranteed tracking of any reference trajectory that can be sampled from the committed set, with an allowed deviation, in exchange for a payment corresponding to the size of the reference set. This paper presents a method to solve the optimal tracking commitment problem for constrained linear systems subject to uncertain disturbance and reference signals. The proposed method allows tractable computations via convex optimization for conic representable reference sets and lends itself to distributed solution methods. We demonstrate the proposed method in a simulation based case study with a commercial building that offers a frequency regulation service to the power grid

The impact of the Covid-19 pandemic on the resilience of the labour market in the Polish-German borderland

The COVID-19 pandemic, as an external factor, quite strongly disrupted the existing trends in the evolution of employment in the Polish-German borderland. The objective of the article is to analyse how resilient Polish and German municipalities are to the COVID-19 pandemic. Border regions, due to their specificities, are characterized by weaker resilience to negative external factors, which meant that the COVID-19 pandemic had a detrimental effect and caused an upturn in unemployment. The empirical part of the study concerns the Polish-German borderland as a clear example of the described tendencies. The study uses the counterfactual before-after comparison method. The novelty in this approach to the study of this hypothetical rate of unemployment involves filling the gap in the literature regarding research of cross border regions, while also developing the existing approaches in the research method used. The results of the survey indicate that the unemployment rate in the Polish-German borderland area has risen (after and due to the pandemic). There are some major differences in how the pandemic has impacted the labour market. Considering the counterfactual approach used, this difference can be described as the impact of the COVID-19 pandemic

OpenBuild : An Integrated Simulation Environment for Building Control

This paper introduces the OpenBuild toolbox for MATLAB. OpenBuild is a toolbox for advanced controller design for buildings heating ventilation and air conditioning systems, with emphasis on Model Predictive Control. It pro- vides researchers in the control community the ability to test algorithms on a wide range of realistic simulation scenarios, by providing most of the data needed to perform simulation and optimization. It combines the convenience of controller design in MATLAB with the simulation capabilities of the building simulation software EnergyPlus. It includes a building modeling tool to construct linear state-space models of building thermodynamics based on building description data, making it useful for design of optimal controllers requiring a good prediction model, as well as providing the input data necessary for simulation such as weather, occupancy and internal gains data. The ability to co-simulate the building between MATLAB and EnergyPlus enables fast prototyping and validation of the models and controllers. This paper presents the working principles and functionality of OpenBuild

Robust Tracking Commitment

Many engineering problems that involve hierarchical control applications, such as demand side ancillary service provision to the power grid, can be posed as a robust tracking commitment problem. In this setting, the lower-level controller commits a set of possible reference trajectories over a finite horizon to an external entity in exchange for a reward corresponding to the size of the reference set and the allowed margin of tracking error. If the commitment is accepted, the lower-level system is required to track any reference trajectory that can be sampled from the committed set. This paper presents the framework of robust tracking commitment and a method to solve the optimal commitment problem for constrained linear systems subject to uncertain disturbance and reference signals. The proposed method allows tractable computations via convex optimization for conic representable uncertainty sets and lends itself to distributed solution methods. We demonstrate the proposed method in a simulation based case study with a commercial building that offers frequency regulation service to the power grid