District Heating System Flexibility Studies Using Thermal Inertia of Buildings

Kozadajevs, Jevgenijs; Boreiko, Dmitrijs

doi:10.1109/rtucon51174.2020.9316600

Cited by 4 publications

(3 citation statements)

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“…In order to integrate flexibility of buildings, solutions such as cosimulation ( [5], [7], [8]) or aggregation ( [6], [8], [11], [12]) have been explored. The main issue is the complexity of the model that can be: ▪ Physical model, with different levels of complexity ( [5], [6], [7], [10], [11], [12]) ▪ Data-based model driven from physical simulation ( [8], [9]) Considering the aggregated approach, despite solid results and processes, it seems lacking some level of fineness in the study of flexibility of each building at district scale. On the cosimulation side, a classic control is applied which have proven its robustness but is not perfectly adapted to flexibility.…”

Section: State Of the Artmentioning

confidence: 99%

Method for Building's Thermal Flexibility in a Multi Energy Vector District

Brugeron,

Vallée,

Foucquier

et al. 2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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This article describes thermal flexibility of building methods at a district level considering different level of details of building models, illustrated by a case study in a newly built district in Grenoble. Heat represents a huge part of final consumption (81% for the residential sector, 60% for the industry), so district heat networks represents a major action lever towards energy transition. In previous work, a mix thermal and electric architecture has been designed and described at district level. This architecture has been upgraded to simulate the thermal building flexibility and integrate model-predictive controllers. Therefore, this upgrade considers a tool for co-simulation between an optimization problem modeler and several simulation models (an electric model and a set of models for the thermal simulation). On the optimization side, we considered one to eight buildings to be flexible in the district, and assess the impact of its flexibility on the system. A refinement of their flexibility potential is one difficult key aspect of this study, considering a complex multivector MILP model. The calibration process has been developed in order to identify the optimization model of this flexible equivalent building. On the simulation side, the simulation models are divided into: the production, the heat network, the heat distribution at building level and the building.

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Section: State Of the Artmentioning

confidence: 99%

Method for Building's Thermal Flexibility in a Multi Energy Vector District

Brugeron,

Vallée,

Foucquier

et al. 2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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“…The physical characteristics of different energy carriers lead to different transfer processes in time and space. These differences will be reflected on the demand sides, such as the inertia of the thermal buildings [21][22]. More specifically, in the power system, changes in demand are instant and obvious, while changes in demand in heating and gas systems take a certain time to be noticed because the water flow is relatively slow and gas is compressible.…”

Section: Integration Of Energy Systemsmentioning

confidence: 99%

“…20), Equation(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) and Equations (3-16)-(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17), respectively.…”

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confidence: 99%

Optimal Management of Flexible Resources in Multi-Energy Systems

Xi¹

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