District Heating Network Design and Configuration Optimization with Genetic Algorithm

Li, Hongwei; Svendsen, Svend

doi:10.13044/j.sdewes..2013.01.22

Cited by 4 publications

(3 citation statements)

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“…As this is a non-linear problem, a Genetic Algorithm and fmincon were used in MatlabÓ. The Genetic Algorithm has been recently applied in several papers for the optimization of the energy systems, such as in optimization of low-temperature district heating network [39]. It is a useful optimization method, which approaches to a global optimum very fast because it generates a population of points at each iteration, instead of a single point at each iteration in a classical algorithm [40].…”

Section: Optimization Methodsmentioning

confidence: 99%

A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage

Dominković

Ćosić

Medić

et al. 2015

Energy Conversion and Management

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a b s t r a c tThis paper provides a solution for managing excess heat production in trigeneration and thus, increases the power plant yearly efficiency. An optimization model for combining biomass trigeneration energy system and pit thermal energy storage has been developed. Furthermore, double piping district heating and cooling network in the residential area without industry consumers was assumed, thus allowing simultaneous flow of the heating and cooling energy. As a consequence, the model is easy to adopt in different regions. Degree-hour method was used for calculation of hourly heating and cooling energy demand. The system covers all the yearly heating and cooling energy needs, while it is assumed that all the electricity can be transferred to the grid due to its renewable origin. The system was modeled in MatlabÓ on hourly basis and hybrid optimization model was used to maximize the net present value (NPV), which was the objective function of the optimization. Economic figures become favorable if the economy-of-scale of both power plant and pit thermal energy storage can be utilized. The results show that the pit thermal energy storage was an excellent option for storing energy and shaving peaks in energy demand. Finally, possible switch from feed-in tariffs to feed-in premiums was assessed and possible subsidy savings have been calculated. The savings are potentially large and can be used for supporting other renewable energy projects.

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Section: Optimization Methodsmentioning

confidence: 99%

A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage

Dominković

Ćosić

Medić

et al. 2015

Energy Conversion and Management

View full text Add to dashboard Cite

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“…The configuration of the peak boiler related to its capacity and location is evaluated using a GA by Sakawa et al Other researchers, such as Li and Svendsen, optimised the DH network configuration using a GA that connects a single HP and the end‐users. Using a GA, Fang and Lahdelma also optimised the supply temperatures of multiple CHP plants at different locations of the system and calculated the optimal heat load distribution between the HPs to minimise the combined production and distribution costs based on a DH network model in steady state.…”

Section: Optimisation Techniquesmentioning

confidence: 99%

A review of modelling and optimisation techniques for district heating systems

2019

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Summary This article provides an extensive survey on the modelling and optimisation of district heating systems (DHSs) focused on the heat distribution network. For this purpose, the major components of a DHS have been described and discussed, and their modelling has been briefly reviewed, including numerical simulation models for heat sources, end‐users, and especially the distribution network. The main deterministic and heuristic optimisation techniques are briefly described. Additionally, a single‐objective and multiobjective optimisation problem is generally formulated, and the main optimisation criteria for the design and operation of the distribution network are synthesised and analysed. The state of the art in DHS optimisation has been also reviewed and categorised. Finally, some recommendations for future developments were included.

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“…We can also see how the changes in the direction of flow dominate at it. According to the definition of one-dimensional fluid flow, through the cross-section of the pipe, all physical magnitudes are a function of the longitudinal coordinate [1], [2], [3], [4], [5], [6], [7]. The flow of the fluid through technical pipes, with high precision, can be considered one-dimensional if the following conditions are satisfied [8], [9]: -The changes of the physical sizes of the fluid as per the cross-section of the pipe are negligible against those along the direction of the flow; -The profiles of all physical characteristic sizes in the cross-section differ very little in the direction of the flow; -The relative change in cross-section in the direction of flow is small; -The radius of the pipe's curve is big enough against the liner characteristic dimension of the cross-section.…”

Section: Introductionmentioning

confidence: 99%

Determining the Optimal Flow Velocity in Networks for District Heating

2017

IJMTER

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Abstract-A district heating system is comprised of three parts: a heating production plant, an exchanger unit, and a pipe network of the district heating. In this paper, we will analyze the flow of the fluid through technical pipes, which will be considered as one-dimensional. The optimal velocity of the flow and its analysis will be determined according to the size of mechanical power losses between 0 Pa/m up to over 200 Pa/m, based on the dependence of the velocity of the flow v=f (,l,d,h f ), according to which we have managed to do the calculation for the approved model with pipe length from l=1 m. The pipe used for this study is from PREMANT (Pre-insulated Steel Pipe System German Pipe Brugg) manufacturer. In the paper, we will conduct an analysis to determine the optimal velocity of the flow of the fluid, for the approved model, by using the equations related to energy losses.

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District Heating Network Design and Configuration Optimization with Genetic Algorithm

Cited by 4 publications

References 0 publications

A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage

A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage

A review of modelling and optimisation techniques for district heating systems

Determining the Optimal Flow Velocity in Networks for District Heating

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