# Advancing Smart Zero-Carbon Cities: High-Resolution Wind Energy Forecasting to 36 Hours Ahead
###### Abstract  
Accurate wind speed and power forecasting are key to optimizing renewable wind station management, which is essential for smart and zero-energy cities. This paper presents a novel integrated wind speed-power forecasting system (WSPFS) that operates across various time horizons, demonstrated through a case study in a high-wind area within the Middle East. The WSPFS leverages 12 AI algorithms both individual and ensemble models to forecast wind speed (WSF) and wind power (WPF) at intervals of 10 min to 36 h. A multi-horizon prediction approach is proposed, using WSF model outputs as inputs for WPF modeling. Predictive accuracy was evaluated using mean absolute percentage error (MAPE) and mean square error (MSE). Additionally, WSPFS advances the smart wind energy deep decarbonization (SWEDD) framework by calculating the carbon city index (CCI) to define the carbon-city transformation curve (CCTC). Findings from this study have broad implications, from enabling zero-energy urban projects and mega-developments like NEOM and the Suez Canal to advancing global energy trading and supply management. s mart wind farm management; smart and zero-carbon cities; real-time AI; urban deep decarbonization; wind power forecasting; sustainability +
Footnote †: journal: Applied sciences  
Smart cities can adapt constantly to changing conditions and optimize parameters to meet different demands. By integrating the Internet of Things (IoTs), Big Data, and artificial intelligence in city-scale resource management, cities can become sustainable through modeling, monitoring, and managing the city's infrastructure and resources. On the other hand, a net zero-carbon city is dedicated to achieving some other decarbonization objective, such as reducing GHG emissions by at least 80% [7; 8; 9]. Moreover, a low-carbon city does not mean a net zero city. Cities must make major structural adjustments to reach net zero such as a decarbonization objective or a reduction target of 80% or more in GHG emissions by a specified year (2050) from baseline. A zero-carbon city uses renewable energy sources to minimize its carbon footprint, ideally 0 or negative; it reduces all forms of carbon emissions through efficient urban design, technology use, and lifestyle changes [10; 11; 12]. Table 1 summarizes the fundamental concepts of smart and carbon cities. A city's deep decarbonization strategy focuses on reducing greenhouse gas emissions to near-zero levels through the implementation of clean energy solutions, sustainable infrastructure, and policy-driven climate actions [11; 12]. This strategy incorporates advanced approaches including green energy conversion, carbon valorization, vehicle electrification, and efficient heating, which achieve beyond conventional methods that cities have adopted for low-carbon development to reduce GHG emissions by 80% or even 100% by 2050 [25; 26; 27]. A core requirement for deep decarbonization is the transformation of energy systems, starting with the creation of a net-zero-carbon electricity grid. This grid will form the foundation of supply-side strategies to deliver carbon-free energy and materials to buildings, transportation, and light industries, which can easily transition to electric power. In addition, vital urban functions such as cooking, heating, and transportation must shift from fossil fuel dependency to electric power, which will necessitate a near doubling of electricity