A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Effects on district heating networks by introducing demand side economic model predictive control
https://orcid.org/0009-0002-0558-9953
https://orcid.org/0000-0002-5067-704X
https://orcid.org/0000-0002-6612-8037
Abstract Using economic model predictive control in space heating systems, the heat demand can flexibly be adapted to varying scenarios of conflicting objectives such as thermal comfort, energy consumption, and peak demand. With a controller that minimizes the heating costs subject to thermal comfort constraints within occupancy hours, the resulting heat demand will depend on the cost mechanism. In the context of Swedish district heating networks, optimal demand side control is a multi-objective problem due to variable costs based on both energy consumption and peak demand. By simulating heat demand control using a gray-box model estimated from a Swedish space heating system, we investigate how the established price structures influence the heat load of a population of buildings with economic model predictive control. Our results suggest that by adjusting the incentives from the type of price structures commonly used today, the peak demand can often be reduced by 10-20% with a minor increase in consumption of 1-2%. We also show that by charging the peak demand for multiple buildings collectively, it is financially beneficial to cooperatively control buildings which can reduce the combined consumption and peak demand even further.
Highlights Simulating optimal control of a building population with district heating prices. Multi-objective optimization of consumption and the peak demand. Buildings with varying occupancy may largely impact the heat load. High peak demand cost incentivizes load shifting. Charging multiple buildings together incentive cooperatively improved operation.
Effects on district heating networks by introducing demand side economic model predictive control
https://orcid.org/0009-0002-0558-9953
https://orcid.org/0000-0002-5067-704X
https://orcid.org/0000-0002-6612-8037
Abstract Using economic model predictive control in space heating systems, the heat demand can flexibly be adapted to varying scenarios of conflicting objectives such as thermal comfort, energy consumption, and peak demand. With a controller that minimizes the heating costs subject to thermal comfort constraints within occupancy hours, the resulting heat demand will depend on the cost mechanism. In the context of Swedish district heating networks, optimal demand side control is a multi-objective problem due to variable costs based on both energy consumption and peak demand. By simulating heat demand control using a gray-box model estimated from a Swedish space heating system, we investigate how the established price structures influence the heat load of a population of buildings with economic model predictive control. Our results suggest that by adjusting the incentives from the type of price structures commonly used today, the peak demand can often be reduced by 10-20% with a minor increase in consumption of 1-2%. We also show that by charging the peak demand for multiple buildings collectively, it is financially beneficial to cooperatively control buildings which can reduce the combined consumption and peak demand even further.
Highlights Simulating optimal control of a building population with district heating prices. Multi-objective optimization of consumption and the peak demand. Buildings with varying occupancy may largely impact the heat load. High peak demand cost incentivizes load shifting. Charging multiple buildings together incentive cooperatively improved operation.
Effects on district heating networks by introducing demand side economic model predictive control
https://orcid.org/0009-0002-0558-9953
https://orcid.org/0000-0002-5067-704X
https://orcid.org/0000-0002-6612-8037
Abstract Using economic model predictive control in space heating systems, the heat demand can flexibly be adapted to varying scenarios of conflicting objectives such as thermal comfort, energy consumption, and peak demand. With a controller that minimizes the heating costs subject to thermal comfort constraints within occupancy hours, the resulting heat demand will depend on the cost mechanism. In the context of Swedish district heating networks, optimal demand side control is a multi-objective problem due to variable costs based on both energy consumption and peak demand. By simulating heat demand control using a gray-box model estimated from a Swedish space heating system, we investigate how the established price structures influence the heat load of a population of buildings with economic model predictive control. Our results suggest that by adjusting the incentives from the type of price structures commonly used today, the peak demand can often be reduced by 10-20% with a minor increase in consumption of 1-2%. We also show that by charging the peak demand for multiple buildings collectively, it is financially beneficial to cooperatively control buildings which can reduce the combined consumption and peak demand even further.
Highlights Simulating optimal control of a building population with district heating prices. Multi-objective optimization of consumption and the peak demand. Buildings with varying occupancy may largely impact the heat load. High peak demand cost incentivizes load shifting. Charging multiple buildings together incentive cooperatively improved operation.
Effects on district heating networks by introducing demand side economic model predictive control
Håkansson, Henrik (author) / Önnheim, Magnus (author) / Gustavsson, Emil (author) / Jirstrand, Mats (author)
Energy and Buildings ; 309
2024-03-03
Article (Journal)
Electronic Resource
English
Domestic demand-side response on district heating networks
| Taylor & Francis Verlag | 2019
Domestic demand-side response on district heating networks
| British Library Online Contents | 2019