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Raluca Suciu
Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland

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Journal article
Published: 31 July 2019 in Energies
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The residential sector accounts for a large share of worldwide energy consumption, yet is difficult to characterise, since consumption profiles depend on several factors from geographical location to individual building occupant behaviour. Given this difficulty, the fact that energy used in this sector is primarily derived from fossil fuels and the latest energy policies around the world (e.g., Europe 20-20-20), a method able to systematically integrate multi-energy networks and low carbon resources in urban systems is clearly required. This work proposes such a method, which uses process integration techniques and mixed integer linear programming to optimise energy systems at both the individual building and district levels. Parametric optimisation is applied as a systematic way to generate interesting solutions for all budgets (i.e., investment cost limits) and two approaches to temporal data treatment are evaluated: monthly average and hourly typical day resolution. The city center of Geneva is used as a first case study to compare the time resolutions and results highlight that implicit peak shaving occurs when data are reduced to monthly averages. Consequently, solutions reveal lower operating costs and higher self-sufficiency scenarios compared to using a finer resolution but with similar relative cost contributions. Therefore, monthly resolution is used for the second case study, the whole canton of Geneva, in the interest of reducing the data processing and computation time as a primary objective of the study is to discover the main cost contributors. The canton is used as a case study to analyse the penetration of low temperature, CO2-based, advanced fourth generation district energy networks with population density. The results reveal that only areas with a piping cost lower than 21.5 k/100 m2ERA connect to the low-temperature network in the intermediate scenarios, while all areas must connect to achieve the minimum operating cost result. Parallel coordinates are employed to better visualise the key performance indicators at canton and commune level together with the breakdown of energy (electricity and natural gas) imports/exports and investment cost to highlight the main contributors.

ACS Style

Raluca Suciu; Paul Stadler; Ivan Kantor; Luc Girardin; François Maréchal. Systematic Integration of Energy-Optimal Buildings With District Networks. Energies 2019, 12, 2945 .

AMA Style

Raluca Suciu, Paul Stadler, Ivan Kantor, Luc Girardin, François Maréchal. Systematic Integration of Energy-Optimal Buildings With District Networks. Energies. 2019; 12 (15):2945.

Chicago/Turabian Style

Raluca Suciu; Paul Stadler; Ivan Kantor; Luc Girardin; François Maréchal. 2019. "Systematic Integration of Energy-Optimal Buildings With District Networks." Energies 12, no. 15: 2945.

Original research article
Published: 30 July 2019 in Frontiers in Energy Research
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The large share of energy consumption in the residential sector has necessitated better understanding and evaluation of its energy needs, with the objective of identifying possible pathways for improvement. This work uses heat signature models and climate data to build a parameterized residential sector profile for different climatic zones in Europe. The sector profile is validated using Rotterdam, NL as a case study and the results show variations from the real energy demand profile of less than 10%, primarily caused by cultural and climatic differences between Rotterdam and the rest of Western Europe. The energy and service profile constructed herein is well-suited for exploring the best technologies for supplying residential requirements, drawing from the domain of process integration. This work demonstrates the usefulness of the residential profile by applying process integration techniques within a mixed integer linear programming formulation to evaluate optimal energy conversion technologies for different district energy networks and potential waste heat recovery from industrial plants located in the vicinity of the residential area. The results show that switching to a fully electric energy providing system can lead to operating cost savings of 48% and CO2 emission savings up to 100%, depending on the mix of electricity generation. The utilization of the sector profile is also exemplified using the city of Rotterdam, where it is shown that industrial waste heat recovery can lead to operating cost and environmental impact savings of 9% and 20%, respectively.

ACS Style

Raluca Suciu; Ivan Kantor; Hür Bütün; François Maréchal. Geographically Parameterized Residential Sector Energy and Service Profile. Frontiers in Energy Research 2019, 7, 1 .

AMA Style

Raluca Suciu, Ivan Kantor, Hür Bütün, François Maréchal. Geographically Parameterized Residential Sector Energy and Service Profile. Frontiers in Energy Research. 2019; 7 ():1.

Chicago/Turabian Style

Raluca Suciu; Ivan Kantor; Hür Bütün; François Maréchal. 2019. "Geographically Parameterized Residential Sector Energy and Service Profile." Frontiers in Energy Research 7, no. : 1.

Book chapter
Published: 02 August 2018 in 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering
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Taking into account the high efficiency of solar thermal collectors and the fact that heating demands represent around 80 % of the total energy needs in residential buildings, it is of interest to integrate solar thermal systems to supply HVAC services. However, both solar energy and HVAC needs have strong daily and seasonal variations, and require an efficient long term storage solution. The underground represents an efficient storage medium, which can compensate the latter mismatch; in winter, surplus heat can be extracted to satisfy the strong demand, while in summer, the rejected heat from cooling systems – in addition to the heat produced from the solar thermal collectors can be reinjected in the ground, therefore achieving long term energy storage. Low temperature district energy networks do not only supply heating and cooling to districts, but they also have the ability to harvest heat from renewable or low temperature waste heat sources and to integrate with long term heat storage systems, such as ground storage. This work looks at the integration of low temperature CO2 networks with solar thermal and geothermal storage to provide energy services. Solar thermal collector areas of 12.5 m2/cap are required for typical urban centers to close yearly energy balance in the ground.

ACS Style

Raluca-Ancuta Suciu; Paul Stadlera; Luc Girardin; Francois Marechal. Solar thermal and geothermal integration with low temperature CO 2 DENs. 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering 2018, 44, 1849 -1854.

AMA Style

Raluca-Ancuta Suciu, Paul Stadlera, Luc Girardin, Francois Marechal. Solar thermal and geothermal integration with low temperature CO 2 DENs. 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering. 2018; 44 ():1849-1854.

Chicago/Turabian Style

Raluca-Ancuta Suciu; Paul Stadlera; Luc Girardin; Francois Marechal. 2018. "Solar thermal and geothermal integration with low temperature CO 2 DENs." 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering 44, no. : 1849-1854.

Book chapter
Published: 04 July 2018 in 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering
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Energy system design should take into account the hourly, daily and seasonal variations of both the energy demand and the considered utilities, and therefore requires a multi-time-resolution problem formulation. Multi-period / multi-time optimization is needed when a multi-time (e.g. hourly) optimization is performed inside another multi-period (e.g. typical day) optimization. However, optimizations over large temporal or spatial horizons tend to become computationally expensive, due to the large number of variables and constraints indexed over the times and over the periods. Employing typical operating periods (e.g. a number of typical operating days during the year) offers an interesting solution for problem size reduction. A variety of data clustering algorithms have been proposed in literature in order to select the best typical periods for different applications. This work uses a MILP formulation of a k-medoids based algorithm (PAM) in order to obtain typical operating periods which pass energy from one period to another, in view of performing long term energy storage. The algorithm is used coupled with an optimization of a CO2 based district energy network in a typical urban center. The intra-daily resolution allows the exploration of short term energy storage in the form of batteries located in the medium and low voltage grid. Coupled with the seasonal resolution, it offers a better understanding of the impact of daily storage on the long term storage and on the total energy requirement. The results show that implementing short-term energy storage leads to reductions of 2% in the size of the long term storage tank and 7.5 - 7.8% in the size of the main energy providers (PV panels).

ACS Style

Raluca Suciu; Paul Stadler; Luc Girardin; François Maréchal. Multi-period multi-time optimisation of CO2 based district energy systems. 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering 2018, 43, 1057 -1062.

AMA Style

Raluca Suciu, Paul Stadler, Luc Girardin, François Maréchal. Multi-period multi-time optimisation of CO2 based district energy systems. 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering. 2018; 43 ():1057-1062.

Chicago/Turabian Style

Raluca Suciu; Paul Stadler; Luc Girardin; François Maréchal. 2018. "Multi-period multi-time optimisation of CO2 based district energy systems." 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering 43, no. : 1057-1062.