### Abstract

In areas with large shares of Combined Heat and Power (CHP) production, significant introduction of intermittent renewable power production may lead to an increased number of operational constraints. As the operation pattern of each utility plant is determined by optimization of economics, possibilities for decoupling production constraints may be valuable. Introduction of heat pumps in the district heating network may pose this ability. In order to evaluate if the introduction of heat pumps is economically viable, we develop calculation methods for the operation patterns of each of the used energy technologies. In the paper, three frequently used operation optimization methods are examined with respect to their impact on operation management of the combined technologies.

One of the investigated approaches utilises linear programming for optimisation, one uses linear programming with binary operation constraints, while the third approach uses nonlinear programming. In the present case the non-linearity occurs in the boiler efficiency of power plants and the cv-value of an extraction plant. The linear programming model is used as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. For the heat pump, the linear optimization yields the lowest amount of operation hours. Using binary integer variables, heat pump operation is increased by 23 %, while for a non-linear approach the increase is more than 39 %. In terms of the total amount of heat produced by heat pumps, the two approaches exceed the reference by approx. 23 % and 32 % respectively. The results indicate a higher coherence between the two latter approaches, and that the MIP optimisation is most appropriate from a viewpoint of accuracy and runtime.

One of the investigated approaches utilises linear programming for optimisation, one uses linear programming with binary operation constraints, while the third approach uses nonlinear programming. In the present case the non-linearity occurs in the boiler efficiency of power plants and the cv-value of an extraction plant. The linear programming model is used as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. For the heat pump, the linear optimization yields the lowest amount of operation hours. Using binary integer variables, heat pump operation is increased by 23 %, while for a non-linear approach the increase is more than 39 %. In terms of the total amount of heat produced by heat pumps, the two approaches exceed the reference by approx. 23 % and 32 % respectively. The results indicate a higher coherence between the two latter approaches, and that the MIP optimisation is most appropriate from a viewpoint of accuracy and runtime.

Original language | English |
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Title of host publication | Proceedings of ECOS 2013 - The 26th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems |

Number of pages | 14 |

Publisher | Chinese Society of Engineering Thermophysics |

Publication date | 2013 |

Publication status | Published - 2013 |

Event | 26th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - Guilin, China Duration: 16 Jul 2013 → 19 Jul 2013 Conference number: 26 |

### Conference

Conference | 26th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems |
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Number | 26 |

Country | China |

City | Guilin |

Period | 16/07/2013 → 19/07/2013 |

## Cite this

Ommen, T. S., Markussen, W. B., & Elmegaard, B. (2013). Comparison of operation optimization methods in energy system modelling. In

*Proceedings of ECOS 2013 - The 26th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems*Chinese Society of Engineering Thermophysics.