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Costanzo Giuseppe

Professeur HES associé

Contrat principal

Professeur HES associé

Téléphone: +41 24 557 63 29

Bureau: C29

Haute école d'Ingénierie et de Gestion du Canton de Vaud
Route de Cheseaux 1, 1400 Yverdon-les-Bains, CH

BSc HES-SO en Microtechniques - Haute école d'Ingénierie et de Gestion du Canton de Vaud

Robotique et systèmes automatisés

BSc HES-SO en Génie électrique - Haute école d'Ingénierie et de Gestion du Canton de Vaud

Robotique et systèmes automatisés

2016

Experimental analysis of data-driven control for a building heating system

Article scientifique ArODES

Giuseppe Costanzo, S. Iacovella, F. Ruelens, T. Leurs, B. J. Claessens

Sustainable Energy, Grids and Networks, 6, 81-90

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Résumé:

Driven by the opportunity to harvest the flexibility related to building climate control for demand response applications, this work presents a data-driven control approach building upon recent advancements in reinforcement learning. More specifically, model-assisted batch reinforcement learning is applied to the setting of building climate control subjected to dynamic pricing. The underlying sequential decision making problem is cast into a Markov decision problem, after which the control algorithm is detailed. In this work, fitted Q-iteration is used to construct a policy from a batch of experimental tuples. In those regions of the state space where the experimental sample density is low, virtual support tuples are added using an artificial neural network. Finally, the resulting policy is shaped using domain knowledge. The control approach has been evaluated quantitatively using a simulation and qualitatively in a living lab. From the quantitative analysis it has been found that the control approach converges in approximately 20 days to obtain a control policy with a performance within 90% of the mathematical optimum. The experimental analysis confirms that within 10 to 20 days sensible policies are obtained that can be used for different outside temperature regimes.

Experimental analysis of data-driven control for a building heating system

Article scientifique

Costanzo Giuseppe, Sandro Iacovella, Frederik Ruelens, Tim Leurs, Bert J. Claessens

Sustainable Energy, Grids and Networks, 2016 , vol. 6, pp. 81-90

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2015

Grey-box modelling of a household refrigeration unit using time series data in application to demand side management

Article scientifique ArODES

Fabrizio Sossan, Venkatachalam Lakshmanan, Giuseppe Costanzo, Mattia Marinelli, Philip J. Douglas, Henrik Bindner

Sustainable Energy, Grids and Networks, 5, 2016, 1-12

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Résumé:

This paper describes the application of stochastic grey-box modelling to identify electrical power consumption-to-temperature models of a domestic freezer using experimental measurements. The models are formulated using stochastic differential equations (SDEs), estimated by maximum likelihood estimation (MLE), validated through the model residuals analysis and cross-validated to detect model over-fitting. A nonlinear model based on the reversed Carnot cycle is also presented and included in the modelling performance analysis. As an application of the models, we apply model predictive control (MPC) to shift the electricity consumption of a freezer in demand response experiments, thereby addressing the model selection problem also from the application point of view and showing in an experimental context the ability of MPC to exploit the freezer as a demand side resource (DSR).

Power admission control with predictive thermal management in smart buildings

Article scientifique ArODES

Jianguo Yao, Giuseppe Costanzo, Guchuan Zhu, Bin Wen

IEEE Transactions on Industrial Electronics, 62, 2015, 4, 2642-2650

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Résumé:

This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First, the power budget with a given thermal comfort constraint is optimized through budget-schedulability analysis which amounts to solving a constrained linear programming problem. Second, the effective peak power demand is reduced by means of the optimal scheduling and cooperative operation of multiple thermal appliances. The performance of the proposed control scheme is assessed by simulation based on the thermal dynamics of a real eight-room office building located at Danish Technical University.

Demand Side Management in the Smart Grid

Thèse de doctorat

Costanzo Giuseppe

2015, Copenhagen : DTU - Danish Technical University. 161 p.

Henrik W. Bindner

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2014

Experimental validation of energy resources integration in microgrids via distributed predictive control

Article scientifique ArODES

Giancarlo Mantovani, Giuseppe Costanzo, Mattia Marinelli, Luca Ferrarini

IEEE Transactions on Energy Conversion, 29, 2014, 4, 1018-1025

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Résumé:

This paper presents an innovative control scheme for the management of energy consumption in commercial buildings with local energy production, such as photovoltaic panels or wind turbine and an energy storage unit. The presented scheme is based on distributed model predictive controllers, which manage the storage system and the building space heating and cooling. The proposed approach is implemented and tested in SYSLAB, the experimental facility for distributed energy systems at the Technical University of Denmark, Risø Campus. The experimental setup consists of wind and solar renewable sources, a vanadium redox battery system, resistive load, and a point of common coupling to the national grid. Several experiments are carried to assess the performance of the control scheme in managing local energy production and consumption.

Testing of a predictive control strategy for balancing renewable sources in a microgrid

Article scientifique ArODES

Mattia Marinelli, Fabrizio Sossan, Giuseppe Costanzo, Henrik W. Bindner

IEEE Transactions on Sustainable Energy, 5, 2014, 4, 1426-1433

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This paper presents the design of a control strategy for the energy management of a grid-connected microgrid with local distributed energy resources as: 10-kW photovoltaic plant, 11-kW wind turbine, and 15-kW–190-kWh vanadium-based electric storage system. According to future regulations, the renewable energy producers will also have to provide a day-ahead hourly production plan. The overall idea is, by knowing the meteorological forecasts for the next 24 h, to dispatch the microgrid in order to be able to grant the scheduled hourly production by means of proper management of the storage system. The usage of the storage system is, however, minimized by the energy management strategy. The system design is validated by experimental testing carried out in SYSLAB, a distributed power system test facility at Risø Campus, Technical University of Denmark.

Testing of a Predictive Control Strategy for Balancing Renewable Sources in a Microgrid

Article scientifique

Costanzo Giuseppe

IEEE Transactions on Sustainable Energy, 2014 , vol. 5, no 4, pp. 1426-1433

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2013

A hardware-in-the-loop simulation architecture for integration of smart buildings and distributed energy resources in micro grids

Article scientifique ArODES

Giuseppe Costanzo, Luca Ferrarini, Giancarlo Mantovani, Anastassia Krusteva, Metody Georgiev, Mihail Antchev

Information Technologies and Control, 11, 2013, 2, 7-13

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Résumé:

This paper presents the design, implementation and test of hardware in the loop simulation architecture for integration of Smart Buildings and distributed energy resources in Micro Grids. The rationale for this work is the integration of off-the-shelves devices in a HIL simulation setup within software development. The architecture and preliminary results are presented, together with a case study for integrating flexible units, such as a space heating system and Electric Vehicles in a Smart Building equipped with local solar energy production.

2012

A system architecture for autonomous demand side load management in smart buildings

Article scientifique ArODES

Giuseppe Costanzo, Guchuan Zhu, Miguel F. Anjos, Gilles Savard

IEEE Transactions on Smart Grid, 3, 4, 2157-2165

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Résumé:

This paper presents a system architecture for load management in smart buildings which enables autonomous demand side load management in the smart grid. Being of a layered structure composed of three main modules for admission control, load balancing, and demand response management, this architecture can encapsulate the system functionality, assure the interoperability between various components, allow the integration of different energy sources, and ease maintenance and upgrading. Hence it is capable of handling autonomous energy consumption management for systems with heterogeneous dynamics in multiple time-scales and allows seamless integration of diverse techniques for online operation control, optimal scheduling, and dynamic pricing. The design of a home energy manager based on this architecture is illustrated and the simulation results with Matlab/Simulink confirm the viability and efficiency of the proposed framework.

A System Architecture for Autonomous Demand Side Load Management in Smart Buildings

Article scientifique

Costanzo Giuseppe, Zhu Guchuan, Miguel Anjos, Gilles Savard,

IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 4, DECEMBER 2012, 2012 , vol. 3, no 4

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Résumé:

2014

Performance assessment of aggregation control services for demand response

Conférence ArODES

Daniel Esteban Morales Bondy, Giuseppe Costanzo, Kai Heussen, Henrik W. Bindner

Proceedings of the IEEE PES Innovative Smart Grid Technologies, Europe

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Résumé:

Aggregation algorithms that provide services to the grid via demand side management are moving from research ideas to the market. With the diversity of the technology delivering such services, it becomes essential to establish transparent performance standards from a service delivery perspective. This paper formulates performance measures and an index to evaluate in hindsight the quality of service delivery by an aggregator, both with respect to ancillary service and asset management service. The index is based on requirements formulated in service contracts and provides an overall assessment of the quality of service provided by an aggregation control algorithm. By a detailed case study we present and an application of the index, comparing the performance of two different control architectures for demand side management delivering a distribution grid service.

Electric space heating scheduling for real-time explicit power control in active distribution networks

Conférence ArODES

Giuseppe Costanzo, Andrey Bernstein, Lorenzo Reyes Chamorro, Henrik W. Bindner, Jean-Yves Leboudec, Mario Paolone

Proceedings of the IEEE PES Innovative Smart Grid Technologies, Europe

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Résumé:

This paper presents a systematic approach for abstracting the flexibility of a building space heating system and using it within a composable framework for real-time explicit power control of microgrids and, more in general, active distribution networks. In particular, the proposed approach is developed within the context of a previously defined microgrid control framework, called COMMELEC, conceived for the explicit and real-time control of these specific networks. The designed control algorithm is totally independent from the need of a building model and allows exploiting the intrinsic thermal inertia for real-time control. The paper first discusses the general approach, then it proves its validity via dedicated simulations performed on specific case study composed by the CIGRE LV microgrid benchmark proposed by the Cigré TF C6.04.02.

A distributed model predictive control approach for the integration of flexible loads, storage and renewables

Conférence ArODES

Luca Ferrarini, Giancarlo Mantovani, Giuseppe Costanzo

Proceedings of the IEEE 23rd International Symposium on Industrial Electronics (ISIE)

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Résumé:

This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to auto-produce part of the energy he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics.

Day-ahead scheduling of a photovoltaic plant by the energy management of a storage system

Conférence ArODES

Mattia Marinelli, Fabrizio Sossan, Fridrik Rafn Isleifsson, Giuseppe Costanzo, Henrik Bindner

Proceedings of the 48th International Universities' Power Engineering Conference (UPEC)

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Résumé:

The paper discusses and describes a system for energy management of a 10 kW PV plant coupled with a 15 kW-190 kWh storage system. The overall idea is, by knowing the meteorological forecast for the next 24h, to dispatch the PV system and to be able to grant the scheduled hourly energy profile by a proper management of the storage. Due to forecast inaccuracies, the energy manager controls the storage in order to ensure that the plan for hourly energy production is respected, minimizing the storage itself usage. The experimental study is carried out in SYSLAB, a distributed power system test facility at DTU Riso Campus and part of PowerLabDK. Both the PV and the storage are connected to the local network and are fully controllable through the SCADA system. The control management and the models are implemented in Matlab-Simulink, which can be interfaced with SYSLAB.

An overview of demand side management control schemes for buildings in smart grids

Conférence ArODES

Anna Magdalena Kosek, Giuseppe Costanzo, Henrik W. Bindner, Oliver Gehrke

Proceedings of the IEEE International Conference on Smart Energy Grid Engineering (SEGE)

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Résumé:

The increasing share of distributed energy resources and renewable energy in power systems results in a highly variable and less controllable energy production. Therefore, in order to ensure stability and to reduce the infrastructure and operation cost of the power grid, flexible and controllable demand is needed. The research area of demand side management is still very much in flux and several options are being presented which can all be used to manage loads in order to achieve a flexible and more responsive demand. These different control schemes are developed with different organization of the power sector in mind and thus can differ significantly in their architecture, their integration into the various markets, their integration into distribution network operation and several other aspects. This paper proposes a classification of load control policies for demand side management in smart buildings, based on external behavior: direct, indirect, transactional and autonomous control; internal operation: decision support system scope, control strategy, failure handling and architecture. This classification assists in providing an overview of the control schemes as well as different ways of representing a building.

2013

A coordination scheme for distributed model predictive control :

Conférence ArODES

integration of flexible DERs

Giuseppe Costanzo, Oliver Gehrke, Daniel Esteban Morales Bondy, Fabrizio Sossan, Henrik Bindner, Jacopo Parvizi, Henrik Madsen

Proceedings of 4th IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)

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Résumé:

This paper presents a control scheme based on distributed model predictive control (DMPC) for coordinating flexible distributed energy resources (DER) of heterogeneous type in the Smart Grid with minimum system integration effort. This approach can be used for reducing the peak power exchange between the grid and a cluster of units in the same feeder in price-driven demand response applications. Preliminary simulations prove that the proposed coordination scheme for DMPC succeeds in coordinating flexible DER unit, achieving significant peak shaving when required. The rationale of this approach consists in coordinating independent units equipped with local MPC controller via simple information passing and hiding in the local controllers the units' dynamics.

Grey-box modeling for system identification of household refrigerators :

Conférence ArODES

a step toward smart appliances

Giuseppe Costanzo, Fabrizio Sossan, Mattia Marinelli, Peder Bacher, Henrik Madsen

Proceedings of the 4th International Youth Conference on Energy (IYCE)

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Résumé:

This paper presents the grey-box modeling of a vapor-compression refrigeration system for residential applications based on maximum likelihood estimation of parameters in stochastic differential equations. Models obtained are useful in the view of controlling refrigerators as flexible consumption units, which operation can be shifted within temperature and operational constraints. Even if the refrigerators are not intended to be used as smart loads, validated models are useful in predicting units consumption. This information can increase the optimality of the management of other flexible units, such as heat pumps for space heating, in order to smooth the load factor during peak hours, enhance reliability and efficiency in power networks and reduce operational costs.

An experimental study on load-peak shaving in smart homes by means of online admission control

Conférence ArODES

Giuseppe Costanzo, Anna Magdalena Kosek, Guchuan Zhu, Luca Ferrarini, Miguel F. Anjos, Gilles Savard

Proceedings of the 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 14-17 October 2012, Berlin, Germany

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Résumé:

This paper presents the design, implementation, and experimental results of an architecture for autonomous demand-side load management (ADSM) system for Smart Buildings in view of influencing the energy demand in the Smart Grid. In such an architecture, the management system has a layered structure and appliances' operation is modeled as a finite state machine, which enables an efficient load control using scheduling techniques borrowed from real-time computing systems. In this study the Admission Control, which is the bottom layer of the presented architecture interacting in real-time with physical equipments, is addressed and the real-time power consumption management in a residential dwelling is implemented and tested in a real office building. The experimental results provide a proof of concept for the proposed architecture and demonstrate the applicability of the on-line scheduling approach for ADSM systems for smart buildings.

2011

Peak-load shaving in smart homes via online scheduling

Conférence ArODES

Giuseppe Costanzo, Jan Kheir, Guchuan Zhu

Proceedings of the IEEE International Symposium on Industrial Electronics

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Résumé:

This paper addresses the problem of load-shaving in Smart Homes in view of improving energy efficiency in Smart Grids. An architecture of home power management systems, allowing the separation of domestic power load control from grid dynamics, is introduced. In this framework, the operation of appliances is modeled as a finite state machine which enables the implementation of online scheduling borrowed from the techniques developed in real-time computing systems. A scheduling algorithm is developed for peak-load shaving and the simulation results confirm the effectiveness and the efficiency of the proposed approach.

Réalisations

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Costanzo Giuseppe

Professeur HES associé

Professeur HES associé

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