Optimising High-Rise Buildings for Self-Sufficiency in Energy Consumption and Food Production Using Artificial Intelligence: Case of Europoint Complex in Rotterdam

The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, integrate (electricity) generation efficient usage of resources with dense habitation, can be a solution for future urbanisation. This paper focuses on transforming Europoint Towers Rotterdam into self-sufficient buildings considering consumption food production (lettuce crops) using artificial intelligence. Design parameters consist the number farming floors, shape, properties proposed façade skin that includes shading devices. Nine thousand samples are collected from various floor levels to predict self-sufficiency criteria neural networks (ANN). Optimisation problems 117 decision variables formulated 45 ANN models have very high prediction accuracies. 13 optimisation algorithms used an in-detail investigation at building scale, potential sufficiency neighbourhood scale. Results indicate 100% 43.7% self-sufficiencies could reached lettuce crops electricity, respectively, three 1800 residents. At sufficient 27,000 people decrease terms use up 11.6%. Consequently, this discusses potentials improvements buildings.