Short term optimization of district heating network supply temperatures

Ikonen, Enso; Selek, Istvan; Kovács, Jenö; Neuvonen, Markus; Szabo, Zador; Bene, József Gergely; Peurasaari, Jani

doi:10.1109/energycon.2014.6850547

Cited by 14 publications

(10 citation statements)

References 11 publications

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“…For example in [11] a simplified model has been derived that is used together with sequential quadratic programming. In [30] approximate dynamic programming [31] has been used taking advantage of permutational symmetries of the DHN dynamics. A model-based approach using fuzzy direct matrix control to mitigate non-linearities of the DHN dynamics can be found in [32].…”

Section: Model-based Dhn Controlmentioning

confidence: 99%

“…A scalable model-free solution solution is presented in [34], here a market-based multi-agent system is used to match thermal and electric demand and supply. Although this approach is scalable, it does not take into account the DHN dynamics and follows a myopic control strategy.…”

Section: Model-based Dhn Controlmentioning

confidence: 99%

“…When an accurate model is available, typical techniques to find near-optimal policies in an MDP framework are value iteration, policy iteration, direct policy search [40] and tree search algorithms such as optimistic planning [41]. In [30] for example, an approximated value iteration approach is followed to determine a control policy for the control of a DHN. In this work, a model-free approach is explored.…”

Section: Cost Signalmentioning

confidence: 99%

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Model-free control of thermostatically controlled loads connected to a district heating network

Claessens

Vanhoudt

Desmedt

et al. 2018

Energy and Buildings

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Optimal control of thermostatically controlled loads connected to a district heating network is considered a sequential decisionmaking problem under uncertainty. The practicality of a direct model-based approach is compromised by two challenges, namely scalability due to the large dimensionality of the problem and the system identification required to identify an accurate model. To help in mitigating these problems, this paper leverages on recent developments in reinforcement learning in combination with a market-based multi-agent system to obtain a scalable solution that obtains a significant performance improvement in a practical learning time. The control approach is applied on a scenario comprising 100 thermostatically controlled loads connected to a radial district heating network supplied by a central combined heat and power plant. Both for an energy arbitrage and a peak shaving objective, the control approach requires 60 days to obtain a performance within 65% of a theoretical lower bound on the cost.

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Section: Model-based Dhn Controlmentioning

confidence: 99%

Section: Model-based Dhn Controlmentioning

confidence: 99%

Section: Cost Signalmentioning

confidence: 99%

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Model-free control of thermostatically controlled loads connected to a district heating network

Claessens

Vanhoudt

Desmedt

et al. 2018

Energy and Buildings

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show abstract

“…However, both studies only consider cost optimization. Ikonen et al, [28] use physical models and multi integer programming to optimize the supply temperature of a district heating network; they propose to extend their work in the future using forecasting models to implement near real time optimization. Pini Prato et al, [10] look into thermo-economic optimization of CHP systems using MILP techniques.…”

Section: Related Workmentioning

confidence: 99%

An Analytical Optimization Model for Holistic Multiobjective District Energy Management - A Case Study Approach

Jayan¹,

Li²,

Rezgui³

et al. 2016

IJMO

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Abstract-Efficient management during the operational phase of district energy systems has become increasingly complex due to the various static and dynamic factors involved. Existing deterministic algorithms which are largely based on human experience acquired from specific domains, normally fail to consider the overall efficiency of district energy systems in a holistic way. This paper looks into taking a black box approach by using genetic algorithms (GA) to solve a multiobjectiveoptimization problem conforming to economic, environmental and efficiency standards. This holistic optimization model, takes into account both heat and electricity demand profiles, and was applied in Ebbw Vale district, in Wales. The model helps compute optimized daily schedules for the generation mix in the district and different operational strategies are analyzed using deterministic and genetic algorithm (GA) based combined optimization methods. The results evidence that GA can be used to define an optimum strategy behind heat production leading to an increase in profit by 32% and reduction in CO 2 emissions by 36% in the 24 hour period analyzed. This research fits in well with future district energy systems which give priority to integrated and systematic management.Index Terms-Analytical model, district energy management, energy efficiency, genetic algorithms, multiobjective optimization.

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“…Huang et al [12] assumed the mass flow rates of the network to be known in advance, leading to a mixed integer linear optimization of the supply temperature profile. Ikonen et al [13] use dynamic programming with permutational invariance to simplify the optimization.…”

Section: Including Time Delays In Thermal Network Controlmentioning

confidence: 99%

A theoretical benchmark for bypass controllers in a residential district heating network

Vandermeulen

Heijde

Patteeuw

et al. 2018

Energy

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Bypass valves in district heating substations are a compromise between efficiency and quality of service. On the one hand, they are required to ensure that each building (no matter the distance to the heat source) has warm water within an acceptable time. On the other hand, they form a short-circuit between the warm supply and cold return line and their use can increase the return temperature substantially. Therefore, a good control of these bypass valves is critical to limit the drawback of their use. In this context, this paper compares two commonly used control strategies (manual control and thermostat control) to a new theoretical benchmark that provides an upper boundary for the performance of bypass controllers. This theoretical benchmark ensures a justin-time delivery of warm water by taking into account time delays in the network. In a simulation case study of a small neighbourhood in Genk, Belgium, the benchmark shows that substantial improvement regarding bypass control is possible.

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Short term optimization of district heating network supply temperatures

Cited by 14 publications

References 11 publications

Model-free control of thermostatically controlled loads connected to a district heating network

Model-free control of thermostatically controlled loads connected to a district heating network

An Analytical Optimization Model for Holistic Multiobjective District Energy Management - A Case Study Approach

A theoretical benchmark for bypass controllers in a residential district heating network

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