Direct characterisation of the annual performance of solar thermal and heat pump systems using a six-day whole system test

Menegon, Diego; Persson, Tomas; Haberl, Robert; Bales, Chris; Haller, Michel

doi:10.1016/j.renene.2019.07.031

Cited by 9 publications

(2 citation statements)

References 33 publications

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“…Nevertheless, all three algorithms would be further investigated in the perspective of a full year and with different buildings and energy system configurations. In the future, the simulation model is planned to be investigated for its annual performance with an adapted fast six-day sequence dynamic testing procedure similar to [61].…”

Section: Discussionmentioning

confidence: 99%

Development of a Coupled TRNSYS-MATLAB Simulation Framework for Model Predictive Control of Integrated Electrical and Thermal Residential Renewable Energy System

Narayanan

Lima²,

Dantas³

et al. 2020

Energies

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An integrated electrical and thermal residential renewable energy system consisting of solar thermal collectors, gas boiler, fuel cell combined heat and power, a photovoltaic system with battery, inverter, and thermal storage for a single-family house of Sonnenhaus standard is investigated with a model predictive controller (MPC). The main focus of this article is to define a multi-objective mathematical function, develop a coupled simulation framework for the nonlinear time-varying deterministic discrete-time problem of the energy system using TRNSYS and MATLAB. With the developed methodology, a sensitivity analysis of maximum optimization time, swarm (or population or mesh) size of a typical spring day and a typical summer day assuming a 100% accurate weather and load forecast with three different algorithms: particle swarm optimization (PSO), genetic algorithm (GA) and global pattern search (GPS) are analyzed. Finally, the obtained results are compared with a status quo controller. Results show that the PSO algorithm optimizer performs the best in this MPC for such a complex and time-consuming MPC model in both the spring day and the summer day. The obtained results show that the PSO with swarm size 50 in the selected typical spring day and the PSO with swarm size 40 in the selected summer day reduces the objective function’s fitness value from 413 to −177 within 6 h optimization time and from 1396 to 1090 in 4 h optimization time respectively.

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Section: Discussionmentioning

confidence: 99%

Development of a Coupled TRNSYS-MATLAB Simulation Framework for Model Predictive Control of Integrated Electrical and Thermal Residential Renewable Energy System

Narayanan

Lima²,

Dantas³

et al. 2020

Energies

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“…In his PhD thesis work, (Sayegh, 2020) developed a new approach and automated tool called TYPSS to define a climate sequence short enough to determine with the full dynamic models the real-time tested system performances that are then extrapolated to the full year. This approach came after previous works following similar philosophy around the elaboration of short sequence test for dynamic thermal system test as in (Albaric et al, 2010), (Chèze et al, 2018) or (Menegon et al, 2020). In the SunHorizon work, the TYPSS tool was used together with the TP2 and TP4 TRNSYS simulations to elaborate short test sequences that are relevant with respect to the two different demonstration sites and environments.…”

Section: Concepts Test Methods and Setupmentioning

confidence: 99%

Semi-Virtual Dynamic Tests of Hybrid Systems Coupling Solar Thermal and PV Panels with Heat Pumps

Chèze¹,

Leconte²

2021

Proceedings of the ISES Solar World Congress 2021

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Despite the huge primary energy consumption associated with heating and cooling (H&C) demand in EU building stock, the share of installed renewable H&C solutions is still marginal (i.e. 5%). In order to speed up a transition towards the widespread application of renewable H&C in buildings, innovative solutions must be designed to compete against traditional solutions. SunHorizon project aims to unlock the potential for a userfriendly and cost-effective solution based on an optimized design and combination of commercial innovative solar technologies (thermal or/and PV) and Heat Pumps (HP). This paper aims to present how are performing experimentally two hybrid concepts, out of four in the whole project, that are coupling solar thermal and PV panels with heat pumps to satisfy thermal and electricity energy demand of residential buildings in Riga (Latvia) and Piera (Spain). Following hardware-in-the-loop approach, specific short test sequences are developed first for each of the two Technology Packages (TP) that allow for extrapolation of the measurements to annual seasonal performance figures including electricity self-consumption in addition to renewable heating and cooling indicators.

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Adaptiveness of a model predictive controller for a thermal-electrical renewable energy system in four different German single-family house energy standards

Narayanan

Mengedoht

Commerell

2021

Case Studies in Thermal Engineering

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Direct characterisation of the annual performance of solar thermal and heat pump systems using a six-day whole system test

Cited by 9 publications

References 33 publications

Development of a Coupled TRNSYS-MATLAB Simulation Framework for Model Predictive Control of Integrated Electrical and Thermal Residential Renewable Energy System

Development of a Coupled TRNSYS-MATLAB Simulation Framework for Model Predictive Control of Integrated Electrical and Thermal Residential Renewable Energy System

Semi-Virtual Dynamic Tests of Hybrid Systems Coupling Solar Thermal and PV Panels with Heat Pumps

Adaptiveness of a model predictive controller for a thermal-electrical renewable energy system in four different German single-family house energy standards

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