Optimal design of renewable energy solution sets for net zero energy buildings

• Main Authors: Harkouss, Fatima, Fardoun, Farouk, Biwole, Pascal Henry
• Format: Article in Journal/Newspaper
• Language: unknown
• Subjects: Tromso
• Online Access: http://www.sciencedirect.com/science/article/pii/S036054421930876X

Net-zero energy buildings (NZEBs) have been considered as an efficient solution to limit the growing energy consumption and pollution emissions from buildings. The configurations and the capacities of the implemented renewable energy systems in NZEBs should be wisely selected to ensure the intended performance objective. This study aims to optimize, investigate and compare six renewable energy solution sets for designing NZEBs in three different climates: Indore (cooling dominant), Tromso (heating dominant), and Beijing (mixed climate). The optimization is carried out using a multi-criteria decision-making methodology. The implemented methodology is composed of two phases. In the first phase, the optimal sizes of solution sets in each climate are derived and analyzed. The effectiveness of optimal solution sets is evaluated with respect to economy, environment, energy and grid stress. In the second phase, recommendations for each region are offered according to the overall performance evaluation results. The evaluation criteria include life cycle cost, payback period, levelized cost of energy, CO2eq emissions, grid interaction index, load matching index, and total energy consumption. The analyses show that, in Indore (hot climate), it is recommended to utilize the solution set composed of air source heat pump for cooling and flat plate solar collectors for domestic hot water (DHW) production. In Tromso (cold climate), the use of a biodiesel generator is promising to produce both electricity and hot steam for heating as well as DHW use. In Beijing (mixed climate), it is recommended to utilize electric chillers for cooling and natural gas condensing boiler for heating and DHW usage. Net zero energy building; Optimization; Climate; Grid stress; Pollution; Economy;