An energy management approach in which a residential neighbourhood is operated for different purpose functions, taking into account different scenarios for the number of electric vehicles and renewable energy capacity at different scales Değişik ölçekteki elektrik araç sayısı ve yenilenebilir enerji kapasitesi senaryoları dikkate alınarak bir konut bölgesinin farklı amaç fonksiyonları doğrultusunda işletildiği bir enerji yönetimi yaklaşımı

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Zaimoğlu A., İşcan E., ŞAFAK B., ÇİÇEK A.

Gumushane Universitesi Fen Bilimleri Dergisi, cilt.15, sa.3, ss.697-710, 2025 (Scopus, TRDizin)

Özet

In the coming years, electricity demand is expected to continuously increase. This rise poses a significant obstacle to the decarbonization of energy systems due to the heavy reliance on fossil fuels. Furthermore, residences account for a considerable percentage of global electricity consumption and carbon emissions. Given this, enhancing renewable energy utilization and implementing effective energy management in residential areas offer a promising solution for sustainability. Specifically, the varying numbers of electric vehicles (EVs) and diverse capacities of renewable energy sources (RES) within a residential area must also be meticulously considered in energy management strategies. This study aims to develop an optimal energy management model for a residential area, taking into account different numbers of electric vehicles and various capacities of renewable energy sources. The model is designed to ensure the economic operation of the residential area, maximize solar energy utilization, and optimize the load factor. Power generated from renewable energy sources can be directly utilized within the residential area, or, in instances of surplus production, sold to the electricity grid. Similarly, power supplied by discharging electric vehicle batteries can also be sold to the electricity grid or used within the residential area. This optimization strategy is modeled using a mixed-integer linear programming (MILP) approach. Within the scope of this study, detailed case analyses were conducted considering different numbers of electric vehicles and various renewable energy capacities, and the obtained results were compared. For test cases, real load data from a residential area in Edirne, Türkiye, were utilized. The results demonstrate that the developed model successfully achieves the desired performance in terms of profit and load factor maximization objectives.