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

• Published in: Energy procedia Vol. 122; pp. 169 - 174
• Main Authors: Max Bittel, Henri, Perera, A.T.D., Mauree, Dasaraden, Scartezzini, Jean-Louis
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2017
• Subjects: distributed energy systems; energy-economic analysis; K-means clustering; thermal networks; urban energy systems; distributed energy systems; energy-economic analysis; urban energy systems; thermal networks; K-means clustering
• DOI: 10.1016/j.egypro.2017.07.341
• ISSN: 1876-6102

To determine the optimum location for non dispatchable renewable energy systems, this study comes up with an integrated tool to place energy systems considering distributed energy demand and renewable energy potential. The Citysim urban energy planning software is used to compute the hourly heating demand of 371 buildings in Jonction, a neighborhood in Geneva. Hourly solar irradiation on the roof tops of each building is computed using the Citysim model. The electricity demand profile for each building is generated using the hourly profile for Geneva using the databases of Swissgrid and Swiss building database. Subsequently, k-means algorithm is used to cluster the buildings based on spatial distribution. An energy economic model is used to evaluate the losses in the thermal and electrical distribution networks and initial investment. Sensitivity of cluster size is evaluated using the energy economic model to obtain an optimum number of clusters and the locations for the energy systems.