Temperature control of a low-temperature district heating network with Model Predictive Control and Mixed-Integer Quadratically Constrained Programming

District heating networks transport thermal energy from one or more sources to a plurality of consumers. Lowering the operating temperatures of district heating networks is a key research topic to reduce energy losses and unlock the potential of low-temperature heat sources, such as waste heat. With...

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Vydané v:	Energy (Oxford) Ročník 224; s. 120140
Hlavní autori:	Hering, Dominik, Cansev, Mehmet Ege, Tamassia, Eugenio, Xhonneux, André, Müller, Dirk
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.06.2021 Elsevier BV
Predmet:	case studies Computers District heating electric power Energy conservation Energy consumption Heat Heat exchangers Heat pump Heat pumps Heat sources Heating Low temperature Low-temperature district heating Mixed integer Mixed-integer quadratically-constrained programming Model predictive control Networks Operating temperature Optimization Predictive control Software in the loop temperature Temperature control Temperature dependence Thermal energy Waste heat Model predictive control Low-temperature district heating Software in the loop Heat pump Mixed-integer quadratically-constrained programming
ISSN:	0360-5442, 1873-6785
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Abstract	District heating networks transport thermal energy from one or more sources to a plurality of consumers. Lowering the operating temperatures of district heating networks is a key research topic to reduce energy losses and unlock the potential of low-temperature heat sources, such as waste heat. With an increasing share of uncontrolled heat sources in district heating networks, control strategies to coordinate energy supply and network operation become more important. This paper focuses on the modeling, control, and optimization of a low-temperature district heating network, presenting a case study with a high share of waste heat from high-performance computers. The network consists of heat pumps with temperature-dependent characteristics. In this paper, quadratic correlations are used to model temperature characteristics. Thus, a mixed-integer quadratically-constrained program is presented that optimizes the operation of heat pumps in combination with thermal energy storages and the operating temperatures of a pipe network. The network operation is optimized for three sample days. The presented optimization model uses the flexibility of the thermal energy storages and thermal inertia of the network by controlling its flow and return temperatures. The results show savings of electrical energy consumption of 1.55%–5.49%, depending on heat and cool demand. •MIQCP optimization model of low-temperature district heating is presented.•MIQCP formulation allows to regard temperature characteristics.•Good fit between simulation and optimization.•MPC with simulation and optimization shows improved operation.
AbstractList	District heating networks transport thermal energy from one or more sources to a plurality of consumers. Lowering the operating temperatures of district heating networks is a key research topic to reduce energy losses and unlock the potential of low-temperature heat sources, such as waste heat. With an increasing share of uncontrolled heat sources in district heating networks, control strategies to coordinate energy supply and network operation become more important. This paper focuses on the modeling, control, and optimization of a low-temperature district heating network, presenting a case study with a high share of waste heat from high-performance computers. The network consists of heat pumps with temperature-dependent characteristics. In this paper, quadratic correlations are used to model temperature characteristics. Thus, a mixed-integer quadratically-constrained program is presented that optimizes the operation of heat pumps in combination with thermal energy storages and the operating temperatures of a pipe network. The network operation is optimized for three sample days. The presented optimization model uses the flexibility of the thermal energy storages and thermal inertia of the network by controlling its flow and return temperatures. The results show savings of electrical energy consumption of 1.55%–5.49%, depending on heat and cool demand. District heating networks transport thermal energy from one or more sources to a plurality of consumers. Lowering the operating temperatures of district heating networks is a key research topic to reduce energy losses and unlock the potential of low-temperature heat sources, such as waste heat. With an increasing share of uncontrolled heat sources in district heating networks, control strategies to coordinate energy supply and network operation become more important. This paper focuses on the modeling, control, and optimization of a low-temperature district heating network, presenting a case study with a high share of waste heat from high-performance computers. The network consists of heat pumps with temperature-dependent characteristics. In this paper, quadratic correlations are used to model temperature characteristics. Thus, a mixed-integer quadratically-constrained program is presented that optimizes the operation of heat pumps in combination with thermal energy storages and the operating temperatures of a pipe network. The network operation is optimized for three sample days. The presented optimization model uses the flexibility of the thermal energy storages and thermal inertia of the network by controlling its flow and return temperatures. The results show savings of electrical energy consumption of 1.55%–5.49%, depending on heat and cool demand. •MIQCP optimization model of low-temperature district heating is presented.•MIQCP formulation allows to regard temperature characteristics.•Good fit between simulation and optimization.•MPC with simulation and optimization shows improved operation.
ArticleNumber	120140
Author	Hering, Dominik Müller, Dirk Tamassia, Eugenio Xhonneux, André Cansev, Mehmet Ege
Author_xml	– sequence: 1 givenname: Dominik surname: Hering fullname: Hering, Dominik email: d.hering@fz-juelich.de organization: Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52425, Jülich, Germany – sequence: 2 givenname: Mehmet Ege surname: Cansev fullname: Cansev, Mehmet Ege organization: Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52425, Jülich, Germany – sequence: 3 givenname: Eugenio surname: Tamassia fullname: Tamassia, Eugenio organization: Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52425, Jülich, Germany – sequence: 4 givenname: André surname: Xhonneux fullname: Xhonneux, André organization: Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52425, Jülich, Germany – sequence: 5 givenname: Dirk surname: Müller fullname: Müller, Dirk organization: Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52425, Jülich, Germany
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Keywords	Model predictive control Low-temperature district heating Software in the loop Heat pump Mixed-integer quadratically-constrained programming
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Snippet	District heating networks transport thermal energy from one or more sources to a plurality of consumers. Lowering the operating temperatures of district...
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SubjectTerms	case studies Computers District heating electric power Energy conservation Energy consumption Heat Heat exchangers Heat pump Heat pumps Heat sources Heating Low temperature Low-temperature district heating Mixed integer Mixed-integer quadratically-constrained programming Model predictive control Networks Operating temperature Optimization Predictive control Software in the loop temperature Temperature control Temperature dependence Thermal energy Waste heat
Title	Temperature control of a low-temperature district heating network with Model Predictive Control and Mixed-Integer Quadratically Constrained Programming
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