Price and carbon-based energy flexibility of residential heating and cooling loads using model predictive control

District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.

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Residential heating and cooling loads and costs for the South

10.2172/5387430 ◽

1982 ◽

Author(s):

A. S. Lau ◽

T. D. Hyatt

Keyword(s):

The South ◽

Heating And Cooling ◽

Residential Heating ◽

Cooling Loads

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Management of a district heating network using model predictive control with and without thermal storage

Optimization and Engineering ◽

10.1007/s11081-021-09644-w ◽

2021 ◽

Author(s):

Davide Quaggiotto ◽

Jacopo Vivian ◽

Angelo Zarrella

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Heat Production ◽

Heat Supply ◽

Waste Heat ◽

Thermal Inertia ◽

District Heating ◽

Heating And Cooling ◽

Look Ahead ◽

The Cost

AbstractDistrict heating and cooling networks are a key infrastructure to decarbonise the heating and cooling sector. Besides the design of new networks according to the principles of the 4th and 5th generation, operational aspects may significantly contribute to improve the efficiency of existing networks from both economic and environmental standpoints. This article is the second step of a work that aims to exploit the flexibility of existing networks and improve their economic and environmental performance, using the district heating network of Verona as a case study. In particular, the first part of the research demonstrated through numerical simulations that the thermal inertia of the water contained in the pipes can be used to shift the heat production of the generators over time by acting on the flow rate circulating in the network. This article shifts the focus from the heat distribution side to the heat supply. A model predictive control strategy was formulated as a MILP optimization problem to schedule the heat supply of the cogeneration plants, heat pump and gas boilers as a function of heat load, waste heat production and electricity price forecasts. Computer simulations of considered district heating network were carried out executing the optimization with a rolling-horizon scheme over two typical weeks. Results show that the proposed look-ahead control achieves a reduction in the operational costs of about 12.5% and 5.8%, respectively in a middle season and a winter representative week. Increasing the flexibility of the system with a centralized heat storage tank connected to the CHP and HP units, these percentage rise to respectively 20% and 6.3%. In the warmest periods, when the total installed power of the CHP and HP plants is sufficient to supply the entire heat demand during the peak, and the modulation of these plants has a higher impact, the cost reduction related to the additional thermal energy storage is more relevant.

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Model Predictive Control of Smart Districts with Fifth Generation Heating and Cooling Networks

IEEE Transactions on Energy Conversion ◽

10.1109/tec.2021.3082405 ◽

2021 ◽

pp. 1-1

Author(s):

Michael Taylor ◽

Sebastian Long ◽

Ognjen Marjanovic ◽

Alessandra Parisio

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Heating And Cooling ◽

Fifth Generation

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

Energies ◽

10.3390/en13236203 ◽

2020 ◽

Vol 13 (23) ◽

pp. 6203

Author(s):

Iago Cupeiro Figueroa ◽

Massimo Cimmino ◽

Lieve Helsen

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

High Capacity ◽

Computational Time ◽

Geothermal Systems ◽

Long Term Effects ◽

Heating And Cooling ◽

Shadow Cost ◽

Active Regeneration

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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