Control-oriented modeling of geothermal borefield thermal dynamics through Hammerstein-Wiener models

Atam, Ercan; Schulte, Daniel O.; Arteconi, Alessia; Sass, Ingo; Helsen, Lieve

doi:10.1016/j.renene.2017.12.105

Cited by 18 publications

(8 citation statements)

References 24 publications

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“…Differing from calibration approaches using the DST model, Atam et al [18] identified non-linear Hammerstein-Wiener models using simulation data from the BASIMO model [19]. Another approach found in the literature involves the use of artificial neural networks (ANNs) [20].…”

Section: Mpc In (Hybrid) Geothermal Systemsmentioning

confidence: 99%

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A Methodology for Long-Term Model Predictive Control of Hybrid Geothermal Systems: The Shadow-Cost Formulation

2020

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Model Predictive Control (MPC) predictive’s nature makes it attractive for controlling high-capacity structures such as thermally activated building systems (TABS). Using weather predictions in the order of days, the system is able to react in advance to changes in the building heating and cooling needs. However, this prediction horizon window may be sub-optimal when hybrid geothermal systems are used, since the ground dynamics are in the order of months and even years. This paper proposes a methodology that includes a shadow-cost in the objective function to take into account the long-term effects that appear in the borefield. The shadow-cost is computed for a given long-term horizon that is discretized over time using predictions of the building heating and cooling needs. The methodology is applied to a case with only heating and active regeneration of the ground thermal balance. Results show that the formulation with the shadow cost is able to optimally use the active regeneration, reducing the overall operational costs at the expenses of an increased computational time. The effects of the shadow cost long-term horizon and the predictions accuracy are also investigated.

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Section: Mpc In (Hybrid) Geothermal Systemsmentioning

confidence: 99%

“…Perfect state updates and perfect weather predictions are assumed, avoiding uncertainties from these aspects. The first strategy comprises a full MPC scenario that aims to minimize the operational costs of the installation according to the formulation given by Equation (18).…”

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confidence: 99%

A Methodology for Long-Term Model Predictive Control of Hybrid Geothermal Systems: The Shadow-Cost Formulation

2020

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“…This time scale limits its applicability to real-life systems. Atam et al (2018) used a Hammerstein-Wiener model to decouple the linear and non-linear dynamics, with parameters identified using appropriate excitation inputs with the BASIMO bore field simulation model (Schulte, 2016). Another approach with several examples in the literature is the use of artificial neural networks, as used for example by Esen et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Linear model predictive control for the reduction of auxiliary electric heating in residential self-assisted ground-source heat pump systems

Laferrière

Cimmino

2019

Science and Technology for the Built Environment

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This paper presents a linear model predictive control strategy for the operation of a "self-assisted" ground-source heat pump (GSHP) to reduce auxiliary electric heating in residential applications equipped with undersized boreholes. The self-assisted configuration uses an electric heating element at the heat pump outlet to inject heat into the bore field when approaching peak power demand. A linear controloriented model is proposed to account for both the source-side and load-side GSHP dynamics. The ground heat transfer is predicted using the bore field's ground-to-fluid thermal response factor, thus allowing for any bore field configuration while accounting for thermal capacity effects. Real historic ambient temperature forecasts and their corresponding historic recorded ambient temperatures from Montreal are used in this paper. The COP non-linearity is circumvented with an iterative approach. A Kalman filter is used to dynamically adjust the bias on the predicted returning fluid temperature. On a borehole undersized by 15%, the control strategy reduces auxiliary electric heating by 96% over 20 years at the cost of a 5.53% increase in total energy consumption. Due to the occasional simultaneous heat injection and auxiliary heating, the yearly peak power demand is increased.

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“…De Ridder et al [28] trained a first order model with data from the DST model to describe the dynamics of the underground storage by using the average temperature of the borefield as the unique state, with sampling periods of one week, and considering constant seasonal performance factors for the HP. Atam et al [29] identified non-linear Hammerstein-Wiener models for different configurations based on large simulation data from BASIMO [30]. Witte et al [31] developed a physics-based model, however axial heat transfer due to advection is not modeled and the fluid temperature is lumped by using the borehole thermal resistance R b .…”

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confidence: 99%

Short-term modeling of hybrid geothermal systems for Model Predictive Control

Figueroa

Picard

Helsen

2020

Energy and Buildings

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Model Predictive Control (MPC) has shown significant energy savings potential in the operation of building energy systems, yet it needs accurate and simple models for optimization. In hybrid geothermal systems the source-side temperatures affect the system efficiency and its operational feasibility. Since the ground dynamics are rather slow, simplifications such as considering a constant coefficient of performance (COP) are made. We evaluate the added value of including a short-term dynamic borefield model to the controller. Simulations are performed in a heating-dominated building equipped with a hybrid geothermal system for two winter weeks. We consider 4 different modeling strategies where the formulation of the COP and the return fluid temperature from the borefield is varied in complexity. Results show that using a constant COP results in a bang-bang behavior of the heat pump, while with an accurate prediction of the COP the operation is smoother, saving 0.46%, 1.86% and 2.71% for low, average and high electricity-to-gas price ratios respectively. Including a short-term borefield model avoids shutting down the heat pump due to safety constraints which saves up to 8.12% more money while the use of the groundsource is quintupled. Despite reducing the optimization iteration number by almost 18%, simulation time is increased.

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Control-oriented modeling of geothermal borefield thermal dynamics through Hammerstein-Wiener models

Cited by 18 publications

References 24 publications

A Methodology for Long-Term Model Predictive Control of Hybrid Geothermal Systems: The Shadow-Cost Formulation

A Methodology for Long-Term Model Predictive Control of Hybrid Geothermal Systems: The Shadow-Cost Formulation

Linear model predictive control for the reduction of auxiliary electric heating in residential self-assisted ground-source heat pump systems

Short-term modeling of hybrid geothermal systems for Model Predictive Control

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