Controlling district heating and cooling networks to unlock flexibility: A review

Vandermeulen, Annelies; Heijde, Bram van der; Helsen, Lieve

doi:10.1016/j.energy.2018.03.034

Cited by 259 publications

(149 citation statements)

References 49 publications

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“…The omission of the building thermal flexibility from the model is expected to have a smaller influence, given the presence of seasonality in all storage SoC profiles, even for the solution with the highest share of primary energy import. Still, it would be interesting to see if the possibility of using the already available sources of energy flexibility (see Vandermeulen et al [37,38] for a comprehensive discussion of this topic) in thermal networks would influence the design choices made.…”

Section: Discussionmentioning

confidence: 99%

Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

et al. 2019

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In the quest to increase the share of renewable and residual energy sources in our energy system, and to reduce its greenhouse gas emissions, district heating networks and seasonal thermal energy storage have the potential to play a key role. Different studies prove the techno-economic potential of these technologies but, due to the added complexity, it is challenging to design and control such systems. This paper describes an integrated optimal design and control algorithm, which is applied to the design of a district heating network with solar thermal collectors, seasonal thermal energy storage and excess heat injection. The focus is mostly on the choice of the size and location of these technologies and less on the network layout optimisation. The algorithm uses a two-layer program, namely with a design optimisation layer implemented as a genetic algorithm and an optimal control evaluation layer implemented using the Python optimal control problem toolbox called modesto. This optimisation strategy is applied to the fictional district energy system case of the city of Genk in Belgium. We show that this algorithm can find optimal designs with respect to multiple objective functions and that even in the cheaper, less renewable solutions, seasonal thermal energy storage systems are installed in large quantities.

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Section: Discussionmentioning

confidence: 99%

Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

et al. 2019

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“…The work in [36] describes a decision support system based on a short-term optimal predictive control law considering the network's lifetime consumption. Comprehensive reviews of the most recent studies in control and optimisation for DHC systems can be found in [37,38], whereas the available software for production planning can be found in [39,40].…”

Section: Current Control Approaches In Dhc Systemsmentioning

confidence: 99%

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

et al. 2019

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This paper presents a holistic innovative solution for the transformation of the current district heating and cooling systems to automated more efficient systems. A variety of technological advancements have been developed and integrated to support the effective energy management of future district heating and cooling sector. First, we identify and discuss the main challenges and needs that are in line with the EU objectives and policy expectations. We give an overview of the main parts that our solution consists of, with emphasis on the forecasting tools and an advanced control system that addresses unit commitment and economic load dispatch problems. The proposed control approach employs distributed and scalable optimisation algorithms for optimising the short-term operations of a district heating and cooling plant subject to technical constraints and uncertainties in the energy demand. To test the performance and validate the proposed control system, a district heating plant with multiple energy generation units and real-life heat load data were used. Simulation experiments were also used to evaluate the benefits of using thermal storage units in district heating systems. The results show that the proposed method could achieve significant cost savings when energy storage is employed. The proposed control strategy can be applied for both operating optimally district heating plants with storage and supporting investment planning for new storage units.

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“…The control of district heating and cooling networks has a big impact on the operation and efficiency of a district energy system. Especially for the integration of renewable energies into conventional heating and cooling networks as well as into 4th generation heating and cooling networks (Lund et al, 2014), the control of these networks is important because generation and demand are temporally decoupled (Vandermeulen et al, 2018). Since these control strategies and the resulting network operations are becoming increasingly complex, dynamic system models are important for developing and testing these strategies.…”

Section: Control Strategiesmentioning

confidence: 99%

Automated model generation and simplification for district heating and cooling networks

Mans¹,

Blacha²,

Remmen³

et al. 2019

Linköping Electronic Conference Proceedings

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The current operation of district heating networks often relies on static analyses and control parameters. In the future, possible integration of renewable energy sources like solar or geothermal energy are getting more and more important. To investigate the impact of these new energy source in combination with new control strategies, dynamic simulation models for district heating and cooling systems are getting more important. However, these models are often large and therefore have large computation times and require manual effort to create and optimize them. Thus, this paper investigates in the simulation of a large and meshed district heating network. We present a workflow for automated generation and model simplification of simulation models based on GIS data. The validity of the model simplification is proven and the usability of the model is demonstrated by a Use Case with two different control strategies.

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Controlling district heating and cooling networks to unlock flexibility: A review

Cited by 259 publications

References 49 publications

Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

Automated model generation and simplification for district heating and cooling networks

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