Techno−Economic Analysis and Multi‐Objective Optimization of Cross‐Flow Wind Turbines for Smart Building Energy Systems

This work reports a technical, economic, and environmental investigation of the possibility of using a recently developed smallscale crossflow wind turbine (CFWT) to supply the energy demand of buildings for different integration scenarios. For this purpose, three CFWT‐assisted building energy system configurations with heat pumps, with and without batteries, and two‐way interaction with the local grid in two residential building models in Iran and Germany are investigated. Triobjective optimization with a Nondominated Sorting Genetic Algorithm (NSGA‐II) is performed for finding the optimal configuration of the energy system in different configurations. For economic assessment, the Capital Budgeting Analysis method is used with four indicators, namely, payback period (PP), net present value (NPV), internal rate of return (IRR), and profitability index (PI). The results show that due to different energy market regulations and prices, different integration scenarios and system configurations can outperform others in Germany and Iran. Overall, due to the exchange rate instability and low energy tariff in Iran, in order for the project to be feasible, either the CFWT cost must fall to below 30% of its current cost or the local electricity price should increase significantly to get a Levelized cost of energy of as low as 0.6 $ kWh(−1).