Intra-day electro-thermal model predictive control for polygeneration systems in microgrids

Menon, Ramanunni Parakkal; Maréchal, François; Paolone, Mario

doi:10.1016/j.energy.2016.03.081

Cited by 19 publications

(9 citation statements)

References 13 publications

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“…Moreover, Zhang et al (2013a) presented a scenario-based MPC in order to minimise the energy consumption of a building, considering heat, ventilation and air conditioning systems. Menon et al (2016) proposed a mathematical formulation based on the exploitation of an MPC in order to manage the optimal control strategy for the electricity and heat within a multi-building network. Furthermore, microgrids can operate isolated or connected to the main power grid.…”

Section: Introductionmentioning

confidence: 99%

A rolling horizon approach for optimal management of microgrids under stochastic uncertainty

Silvente

Kopanos

Dua

et al. 2018

Chemical Engineering Research and Design

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This work presents a Mixed Integer Linear Programming (MILP) approach based on a combination of a rolling horizon and stochastic programming formulation. The objective of the proposed formulation is the optimal management of the supply and demand of energy and heat in microgrids under uncertainty, in order to minimise the operational cost. Delays in the starting time of energy demands are allowed within a predefined time windows to tackle flexible demand profiles. This approach uses a scenario-based stochastic programming formulation. These scenarios consider uncertainty in the wind speed forecast, the processing time of the energy tasks and the overall heat demand, to take into account all possible scenarios related to the generation and demand of energy and heat. Nevertheless, embracing all external scenarios associated with wind speed prediction makes their consideration computationally intractable. Thus, updating input information (e.g., wind speed forecast) is required to guarantee good quality and practical solutions. Hence, the two-stage stochastic MILP formulation is introduced into a rolling horizon approach that periodically updates input information.

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Section: Introductionmentioning

confidence: 99%

A rolling horizon approach for optimal management of microgrids under stochastic uncertainty

Silvente

Kopanos

Dua

et al. 2018

Chemical Engineering Research and Design

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“…The simulations are performed on an IEEE benchmark LV network (Figure 2) proposed by the CIGRE research group [15]. The different building and DER models developed by the authors of [3], [9], [17] and [18] have been implemented in the following simulations; each building represents an integrated set of energy conversion and storage units to satisfy the different services (i.e. domestic hot water preparation, space heating and power provision).…”

Section: A System Descriptionmentioning

confidence: 99%

“…[8], [9], [10], [11]). Nevertheless, a lack of communication between the different MPC units while defining the local strategies might cause critical grid operating conditions [3]. In order to face these issues, authors in [12] presented a distributed model predictive control (DMPC) architecture, coordinated through an independent system operator (ISO) in order to steer towards a global grid objective of peak-shaving.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, the integration of flexible deterministic energy systems combined with the strong penetration of uncontrollable and stochastic renewable energy sources (RESs) has pushed the gird to its operating limits [1]. Microgrids represent a promising concept to face the latter issue; by interconnecting and thus monitoring the different DERs, the aggregated operation strategy enables the provision of voltage support and other ancillary services to the local distribution system operator (DSO) [2], [3], [4], [5]. Nevertheless, the growing integration of polygeneration systems (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Distributed model predictive control of energy systems in microgrids

Stadler

Ashouri

Maréchal

2016

2016 Annual IEEE Systems Conference (SysCon)

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This paper presents a flexible and modular control scheme based on distributed model predictive control (DMPC) to achieve optimal operation of decentralized energy systems in smart grids. The proposed approach is used to coordinate multiple distributed energy resources (DERs) in a low voltage (LV) microgrid and therefore, allow virtual power plant (VPP) operation. A sequential and iterative DMPC formulation is shown which incorporates global grid targets along with the local comfort requirements and performance indices. The preliminary results generated by the simulation of a studied case proves the benefits of applying such a control scheme to a benchmark low voltage microgrid

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“…The building energy management system is based on model predictive control (MPC) which has been identified as an appropriate methodology for this problem formulation [13,14]. The building regulator hence computes the optimal input variable values for each time step, k of the defined control horizon, n k .…”

Section: System Modellingmentioning

confidence: 99%

Model-based optimization of distributed and renewable energy systems in buildings

Stadler

Ashouri

Maréchal

2016

Energy and Buildings

Self Cite

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In order to fully exploit the potential of renewable energy resources (RERs) for building applications, optimal design and control of the different energy systems is a compelling challenge to address. This paper presents a two-step multi-objective optimization approach to size both thermal and electrical energy systems in regard of thermo-economic performance indicators to suit consumer and grid operator interests. Several utilities such as storage, conversion systems, and RERs are hence modelled and formulated through mixed-integer linear programming. Simultaneously, the algorithm defines the optimal operation strategy, based on a model predictive control structure, for each deterministic unit embedded within the energy management system of the building to meet the different comfort and service requirements.The developed design framework is successfully applied on several energy systems configuration of typical Swiss building types. Different component sizes are analysed, regarding the present investment cost and the self-consumption share. In addition, this paper presents a novel optimal design criteria based on the maximum cost benefits in the view of both the consumer and the distribution network operator.Keywords: Multi-Objective Optimization, Optimal design and control, Distributed Energy System, System Modelling, Complete building simulation Highlights• K-medoids clustering of the input data to improve computational efforts • Advanced thermal modelling by applying discrete control-oriented models of thermo-electrical energy systems and heat cascading. * Corresponding author, Phone Number: +41 21 695 82 60

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Intra-day electro-thermal model predictive control for polygeneration systems in microgrids

Cited by 19 publications

References 13 publications

A rolling horizon approach for optimal management of microgrids under stochastic uncertainty

A rolling horizon approach for optimal management of microgrids under stochastic uncertainty

Distributed model predictive control of energy systems in microgrids

Model-based optimization of distributed and renewable energy systems in buildings

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