A two-stage polynomial approach to stochastic optimization of district heating networks


METADATA ONLY
Loading...

Date

2019-03

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

In this paper we use stochastic polynomial optimization to derive high-performance operating strategies for heating networks with uncertain or variable demand. The heat flow in district heating networks can be regulated by varying the supply temperature, the mass flow rate, or both simultaneously, leading to different operating strategies. The task of choosing the set-points within each strategy that minimize the network losses for a range of demand conditions can be cast as a two-stage stochastic optimization problem with polynomial objective and polynomial constraints. We derive a generalized moment problem (GMP) equivalent to such a two-stage stochastic optimization problem, and describe a hierarchy of moment relaxations approximating the optimal solution of the GMP. Under various network design parameters, we use the method to compute (approximately) optimal strategies when one of, or both, the mass flow rate and supply temperature are varied for a benchmark heat network. We report that the performance of an optimally-parameterized fixed-temperature variable-mass-flow strategy can approach that of a fully variable strategy.

Publication status

published

Editor

Book title

Volume

17

Pages / Article No.

100177

Publisher

Elsevier

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

District heating; Operating strategies; Two-stage stochastic optimization; Generalized moment problem

Organisational unit

03751 - Lygeros, John / Lygeros, John check_circle

Notes

Funding

Related publications and datasets