1,721,049 research outputs found
Model predictive controls for residential buildings with heat pumps: Experimentally validated archetypes to simplify the large-scale application
No full textExploiting the energy flexibility resulting from thermal loads management in buildings is one of the most promising solutions to contribute to the energy transition targets. To offer energy flexibility to the grid, the building should meet the requirements: (i) it needs electrically powered generation (e.g., through Heat Pumps) and (ii) advanced control techniques (e.g., Model Predictive Controls) must be implemented. In recent years, the scientific community has produced many studies demonstrating the potential of Model Predictive Controls combined with Heat Pumps to exploit energy flexibility in buildings. However, a large-scale deployment of such control techniques is still far off, both because of the not yet widespread use of Heat Pumps and the computational challenges involved in implementing them. The aim of this study is to contribute to the deployment of advanced control techniques for Heat Pumps systems in buildings by simplifying their implementation. At this aim, validated archetypes of Model Predictive Controls for Heat Pumps in residential buildings are proposed. The availability of archetypes can greatly facilitate the practical application of Model Predictive Control. In fact, they are adaptable to the characteristics of different buildings and Heat Pump installations and their structure is designed to have an acceptable trade-off between calculation time and prediction reliability. The archetypes cover three different types of heating systems: low temperature radiators without (i) and with (ii) integrated heat storage devices and (iii) underfloor heating system. All archetypes are applied to a real Heat Pump and validated through experimental campaigns. During the experimental test all the archetypes proved to be effective in controlling the real system and the results showed good reliability of the prediction model in the control (for all archetypes a Root Mean Square Error lower than 0.44 degrees C was obtained) and an optimizer success rate in Model Predictive Controls greater than 91 %. The archetypes proposed are provided as open-source tools that can be reused for similar cases to facilitate Model Predictive Controls implementation in heat pump systems
Assessing the Contribution of District Heating to the Flexibility of the Italian Power System in High Renewables Penetration Scenarios
No full textIn compliance with Paris Agreement decarbonization targets, the EU goal is to reach carbon neutrality by 2050. This will put particular pressure on the power system, and will require enough flexibility to cope with high shares of renewable energy sources (RES) while ensuring the security and affordability of the service. In this regard,the penetration in the energy system of heat-electricity sector coupling technologies is considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. This would also enable the decarbonisation of the heating sector, responsible for around half of the energy consumption in EU 75% of which supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and in particular to the potential provision of operating reserves for energy systems with high RES penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large scale heat pumps (P2HT), is modelled and compared in terms of performance. The case study analysed is the Italian energy system, which is simulated through the open-source unit commitment and optimal dispatch model Dispa-SET. Results show that the large deployment of DH systems coupled with TES units can offer an important contribution to the power system flexibility and to the provision of operating reserves. In particular,the large deployment of DH supplied by P2HT technologies can bring significant benefits in terms of system costs (up to 50% reduction), renewables integration and greenhouse gases (GHG) emission reductions
Domestic demand-side management (DSM): Role of heat pumps and thermal energy storage (TES) systems
No full textHeat pumps to upgrade existing CHP-DHN systems towards new generation thermal networks
Full text linkDistrict heating networks with combined heat and power systems and renewable energies are one of the most promising solutions for efficient and sustainable energy supply. In many cases, however, especially for district heating networks prior to the 4th generation, significant renovations are required to meet decarbonization targets. In this paper a study is proposed to evaluate the integration of high temperature heat pumps in an existing combined heat and power - district heating plant to reduce fossil fuel consumption and increase the exploitation of renewable energy sources. The plant is currently operating in central Italy and connects more than 1250 users. The identified solution implies lowering the district heating networks operating temperature and supplying power peaks with a high temperature heat pump acting as a booster. Results showed significant improvements in system performance especially in the winter months, due to the greater impact of lowering the temperature level of the district heating network during these months. Overall, the updated scenario allows the overall demand and ground heat losses to be reduced annually by 5.3 % and 13.5 % respectively. This reduces natural gas consumption by 13.3 % and avoids the emission of about 836 tCO2. The analysis provides guidelines for the upgrade of 3rd generation district heating network that can be useful for planning improvements towards newest generation thermal networks
Representative cycle for heat pump energy flexibility evaluations – A comparative simulation study of existing day selection procedures to a new consecutive day procedure
Full text linkHeat pumps allow to decarbonise the heating sector and to provide energy flexibility services. Hence, flexible heat pump control strategies are being developed. When testing these strategies, hardware-in-the-loop experiments using representative test cycles allow to evaluate the real heat pump behaviour. While several works investigated the representative cycle composition for retrieving the yearly energy performance, it is unclear if they can still be used for energy flexibility analysis. This paper investigates the performance of the three mainly used representative day selection procedures available in literature in presence of seven heat pump control strategies. A new approach, in which only consecutive days are used, was also evaluated. Two hydraulic configurations, i.e. with and without an energy storage between heat pump and building, and three climatic zones spread over the European Union were used in order to reach a general conclusion. Simulation results showed that approaches using consecutive days or approaches which select days based on their energy consumption can be used for the energy flexibility analysis. Though, only approaches with consecutive days were able to closely follow the operative room temperature profiles when compared to a full winter simulation due to the avoidance of abrupt temperature variations between the different days
Energy flexible buildings: A methodology for rating the flexibility performance of buildings with electric heating and cooling systems
Full text link© 2019 In the present energy scenario, buildings are playing more and more as energy prosumers. They can use and produce energy and also actively manage their energy demand. The energy flexibility quantifies their potential to adjust the energy demand on the basis of external requests. The objective of this paper is to propose a method for buildings energy flexibility labelling at design conditions in the same fashion as the energy performance label. The flexibility quantification is based on the calculation of four flexibility parameters, which contribute to the definition of the Flexibility Performance Indicator. In order to assess the Flexibility Performance Indicator, buildings dynamic simulations are necessary and the boundary conditions (i.e. demand response event, representative day, comfort constraints)to be considered during the evaluation are provided as part of the proposed methodology. The method was applied to different Italian buildings, which differ for geographic location and design specifications and, in particular, the effects of building structure, heating/cooling systems and energy storage systems were compared. Results show that the climatic conditions affect the flexibility performance, while the building feature more relevant is the thermal mass of the building envelope, more than that provided by the distribution system. A sensitivity analysis to evaluate how the results are influenced by the proposed boundary conditions was also performed. Their choice confirms to have a relevant impact on flexibility quantification, then their unique definition has a paramount importance within this methodology.sponsorship: This work has been supported by MIUR of Italy in the framework of PRIN2015 project: "Clean heating and cooling technologies for an energy efficient smart grid", Prot. 2015M8S2PA. (MIUR of Italy in the framework of PRIN2015 project: "Clean heating and cooling technologies for an energy efficient smart grid"|2015M8S2PA)status: Publishe
Day-ahead optimal scheduling of smart electric storage heaters: A real quantification of uncertainty factors
Full text linkOptimized controls are particularly promising for flexible and efficient management of space heating and cooling systems in buildings. However, when controls are based on predictive models, their effectiveness is affected by the reliability of the models used. In this paper we propose a quantification analysis of some of the main uncertainty factors that can be observed in an optimal control really implemented in a building. A day-ahead optimal scheduling was applied to the heating system (composed of smart electric heaters with thermal storage) of a single room in an office building located in Osimo (Italy). The control algorithm is formulated to determine the charging periods of the heaters with the objective of minimizing the withdrawal of energy from the grid. The control takes into account the electricity produced by a photovoltaic plant and must maintain the internal air temperature close to an imposed setpoint.
Firstly, the actual application of the control is shown during two selected days. Secondly, the analysis is extended to quantify the impact on the control performance of the prediction uncertainty of the input variables. The variable that has the greatest impact is the weather forecast and, specifically, the cloudiness index, which determines the solar gains. The different moment in time in which the weather forecast is predicted has proved to have a significant impact on the charging periods of the heaters (expected variation ranges from -50% to + 100%) and on the prediction of the indoor air temperature (variations observed up to 40%)
Thermofluid Modelling of Large-Scale Orchards for Optimal Design and Control of Active Frost Prevention Systems
Full text linksponsorship: The first author would like to thank TUBITAK for funding (through the TUBITAK 1512 program) his project entitled "Development of tools for solar-energy assisted frost prevention systems in large-scale orchards." (TUBITAK through the TUBITAK 1512 program)status: Publishe
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