Locating Multi Energy Systems for A Neighborhood In Geneva Using K-Means Clustering

Bittel, Henri Max; Perera, A.T.D.; Mauree, Dasaraden; Scartezzini, Jean-Louis

doi:10.1016/j.egypro.2017.07.341

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…For instance, linear discriminant analysis and factor analysis approaches have been used, e.g., in finance (Awh and Waters, 1974), sociology (McKennell, 1970) and applied economics (Nunes, 2002;Below et al, 2012;Kim et al, 2014). For classification problems, the literature has barely scratched the surface with only a few examples that have used exploratory methods like K-means clustering (Dudeni-Tlhone et al, 2013;Max Bittel et al, 2017).…”

Section: Model-based Clusteringmentioning

confidence: 99%

A Model-based Clustering Approach for Analyzing Energy-related Financial Literacy and Its Determinants

Kumar

2019

SSRN Journal

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Recent research highlights the role of consumer's energy-related financial literacy in adoption of energy efficient household appliances in order to reduce the energy-efficiency gap within the household sector. The computation of an indicator for such a literacy measure has followed a somewhat less refined approach though. This paper demonstrates the use of a model-based clustering strategy in order to differentiate the population based on the level of energy-related financial literacy. Using a Swiss data with 6, 722 respondents, we are able to identify three latent groups that represent low, mid and high levels of literacy. We use this new measure within an ordered logit setting with the goal of explaining the determinants of the level of energy-related financial literacy and compare empirical results using classical indicators and approaches. The empirical findings suggest a significant gender-gap among the Swiss population, i.e. females, even those with university education, are less likely to possess a high level of energy-related financial literacy. Individuals who display strong concern for free-riding on their own energy reduction behavior, are also found to have higher odds of belonging to the low literacy group. The results show that it is possible to identify latent classes that have a general and intuitive meaning and provides support to the model-based clustering approach as a sophisticated alternative. This could be a useful approach when empirical researchers are interested in (attribute-based) latent groups of consumers. The identification of latent classes also provides a possibility to target consumers belonging to these classes with specific policy measures in order to increase their level of literacy.

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Section: Model-based Clusteringmentioning

confidence: 99%

A Model-based Clustering Approach for Analyzing Energy-related Financial Literacy and Its Determinants

Kumar

2019

SSRN Journal

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“…A neighbourhood containing approximately 800 buildings in the Junction district in Geneva, Switzerland is considered for this study. In a previous study, the electricity demand, the heating demand and the solar generation of each building were simulated using CitySim [57] for every hour (8760 time steps) over one typical meteorological year [58] using the Meteonorm dataset [59]. Depending on the location and occupations, some buildings had a higher electricity demand than other buildings.…”

Section: Junction District In Genevamentioning

confidence: 99%

“…The PV electricity generation in kWh is obtained by using the available irradiation (obtained from the CitySim software) in hourly resolution for a specific cluster in the Junction District of Geneva. In a different study, we used the CitySim software to evaluate the generation from installed PV on top of individual buildings [58]. Since this is outside the scope of this paper, as we are working at the neighbourhood level, we only consider inefficiencies in the PV system, such as inversion losses, to calculate the solar PV generation and hence the irradiation is multiplied with a solar cell efficiency of 15% [63].…”

Section: Energy Generation and Demandmentioning

confidence: 99%

Eco-Sim: A Parametric Tool to Evaluate the Environmental and Economic Feasibility of Decentralized Energy Systems

et al. 2019

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Due to climate change and the need to decrease the carbon footprint of urban areas, there is an increasing pressure to integrate renewable energy and other components in urban energy systems. Most of the models or available tools do not provide both an economic and environmental assessment of the energy systems and thus lead to the design of systems that are sub-optimal. A flexible and modular simulation tool, Eco-Sim, is thus developed in the current study to conduct a comprehensive techno-economic and environmental assessment of a distributed energy system considering different configuration scenarios. Subsequently, an intermodel comparison is conducted with the Hybrid Optimization Model for Electric Renewable (HOMER) Pro as well as with a state-of-the-art industrial tool. Eco-Sim is then extended by including the heating demand, thermal conversion (by using heat pumps and solar thermal) methods and thermal storage. A parametric analysis is conducted by considering different capacities of solar photovoltaics (PV), solar thermal panels and energy storage technologies. The levelized cost of electricity, the autonomy level and the CO 2 emissions are used as the key performance indicators. Based on the analysis of a study case conducted in a neighbourhood in Geneva, Switzerland, the study reveals that, with the present market prices for batteries and seasonal changes in solar energy potential, the combination of solar PV with battery storage doesn’t bring a significant autonomy to the system and increases the CO 2 emissions of the system. However, the integration of thermal storage and solar thermal generation is shown to considerably increase the autonomy of the neighbourhood. Finally, multiple scenarios are also run in order to evaluate the sensitivity of economic parameters on the performance indicators of the system. Under the assumptions of the model, to foster investments in solar PV and battery installations, falling installation costs or stronger policies in favor of renewable energy seem necessary for the future.

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“…In a previous study, 175 the electricity demand, the heating demand as well as the solar generation of each building were simulated using CitySim [43] for every hour (8,760 time steps) over one typical year [12] using the Meteonorm dataset [42]. The annual net electricity consumption variation of the district is modeled in the Figure 4 Depending on the location, some buildings have a higher electricity demand 180 than other buildings.…”

Section: Junction District In Genevamentioning

confidence: 99%

A parametric tool to evaluate the environmental and economic feasibility of decentralized energy systems.

Siraganyan¹,

Mauree²,

Perera³

et al. 2018

Preprint

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A simulation tool is developed to make a comprehensive techno-economic and environmental assessment of a case study under different scenarios. Different capacity of solar and storage technologies are considered. The model calculates the levelized cost of electricity, the autonomy level and the CO 2 emissions. We demonstrate that the economic profitability of solar and battery system is in very good agreement with HOMER and the autonomy level is validated by using a simulation tool created by SI-REN. We show that combining solar PV with battery system doesn't bring additional autonomy to the model for Geneva considering the present market prices for batteries and seasonal changes in solar energy potential. The validated tool is then extended to include the thermal demand and generation by adding heat pumps and solar thermal. The availability of thermal storage at a large scale and the generation over a neighbourhood are shown to increase the autonomy of the neighbourhood. Finally, multiple scenarios are also run by changing the input parameters to perform a sensitivity analysis of these parameters on the performance of the model. Under the assumptions of the model, to foster investments in solar PV and battery installations, falling investments costs seem necessary for the future.

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Locating Multi Energy Systems for A Neighborhood In Geneva Using K-Means Clustering

Cited by 9 publications

References 5 publications

A Model-based Clustering Approach for Analyzing Energy-related Financial Literacy and Its Determinants

A Model-based Clustering Approach for Analyzing Energy-related Financial Literacy and Its Determinants

Eco-Sim: A Parametric Tool to Evaluate the Environmental and Economic Feasibility of Decentralized Energy Systems

A parametric tool to evaluate the environmental and economic feasibility of decentralized energy systems.

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