DESIGN STRATEGIES FOR HARNESSING THE SOLAR ENERGY POTENTIAL FOR POSITIVE ENERGY DISTRICTS: AN OPTIMIZATION METHOD BASED ON EVOLUTIONARY ALGORITHMS

Date

2024-12-6

Author

Yılmaz, Ataberk

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Buildings account for a significant portion of energy consumption and greenhouse gas emissions worldwide, emphasizing the critical need for a transition to clean energy solutions. Positive Energy Districts (PEDs) have emerged as a transformative strategy to achieve energy-positive and climate-neutral urban environments. PEDs aim to locally generate more energy than they consume, primarily through renewable energy systems such as solar technologies, which are favored for their abundance and versatility. This thesis investigates the optimization of solar energy production by integrating photovoltaic (PV) systems and solar water heaters (SWH). A computational design method employing genetic optimization, specifically NSGA II, is proposed, which dynamically adjusts to varying energy demands, building roof areas, and orientations. As a foundation, simulation-based data generation is applied to artificial neighborhoods to simulate energy demands and calculate solar energy system output. The optimization framework is evaluated with two conflicting objectives: (1) minimizing the electricity demand gap and (2) minimizing the hot water demand gap, with results visualized through Pareto fronts incorporating cost considerations. The findings reveal that while all tested buildings successfully fulfilled their annual hot water demands, only 8% were able to meet their annual electricity requirements. This highlights the significant challenges in achieving positive energy goals, especially for electricity demands, within the limitations of spatial and architectural constraints. The research offers valuable insights into coupling solar technologies for PEDs and presents a scalable methodology that showcases their potential to mitigate solar radiation variability while ensuring a stable and sustainable energy supply in urban environments.

Subject Keywords

Genetic Optimization, Photovoltaics, Positive Energy Districts, Solar Energy Systems, Solar Water Heaters

URI

https://hdl.handle.net/11511/112975

Collections

Graduate School of Natural and Applied Sciences, Thesis