美国如何通过AI迅速启动智慧城市

INATION TECHNOLOGY and smart electric vehicles EVs shift their charging times to off-peak hours. At the same time, cities are increasingly making their own climate commitments and looking for ways to reduce their own emissionsand the emissions of businesses and residents who live in cities. Alliances such as Climate Mayors, a network of 465 U.S. mayors, and the Global Covenant of Mayors for Climate and Energy, which includes 172 U.S. cities, represent the growing movement toward local action on climate change. 2 By embedding smart technologies in the grid, buildings, and transportation systems, cities can reduce their energy use and emissions. A 2018 McKinsey report finds that a city deploying smart city applications “to the best reasonable extent” could reduce its total emissions by 10 to 15 percent. 3 Similarly, Microsoft and PwC found that AI-enabled decarbonization technologies could reduce the carbon intensity of the global economy figure 1. 4 These applications help cities plan and govern more efficiently, reduce their energy use and emissions, attract and support businesses, and discover new sources of revenue. Figure 1 Carbon emissions intensity in a “business as usual” scenario compared with AI-enabled decarbonization 5 But cities are facing revenue shortfalls as a result of the COVID-19 pandemic, which is stalling smart city investments. Even the most capable cities struggle to evolve into smart cities, because cities are ill-equipped to overcome the key challenges limiting smart city development. The first INATION TECHNOLOGY and in the future, cities could use AI or machine learning to run similar algorithms. 20 Finally, cities can turn to smart charging to minimize the stress EVs put on the electric grid. Increased adoption of EVs will lead to increased electricity demand. Given that many drivers would plug their vehicles in to charge at around the same time of dayfor example, in the evening after getting home from a typical 9-to-5 workdaythe demand for electricity would skyrocket during those times. But through smart charging stations, which enable EVs to communicate with the grid much like connected vehicles communicate with the roadway, cities could manage EV charging to improve grid operations by shifting charging times to off-peak hours. Smart Grid Traditionally, the United States electricity distribution system has only worked in one direction Electricity flows from power plants through power lines and substations to customers figure 2. But the rise of smart grid technologiesthe digital hardware and software embedded within the energy system, including sensors, controls, intelligent appliances, and moreis changing the way consumers and businesses distribute and consume electricity, and allows for greater inational awareness and control of energy flows. Smart grids enable decreased reliance on fossil fuels and increased use of cleaner energy sources, as well as increased energy efficiency, reliability, and security. They also provide opportunities for consumers to lower their energy bills and for cities to reduce their overall environmental footprint. For the more than 2,000 U.S. towns and cities served by a public power utility, city governments have a direct role in grid modernization and transitioning to the smart grid. The American Public Power Association in 2018 released its smart city roadmap for public utilities, noting that public utilities are well positioned to lead in smart city programs and integrate with other city services such as transportation. 21 Cities served by investor-owned utilities have less direct control over grid operations but can work with the local utility and regulators to pilot smart grid applications. INATION TECHNOLOGY can in heating, cooling, and lighting needs; and guide decisions on how to increase occupants comfort while reducing energy use. Building automation uses insights from sensor data to connect and control buildings HVAC, lighting, security, plumbing, emergency alarms, elevators, and more. When integrated with building automation systems, AI can optimize a buildings energy use and perance. AI software can also identify where energy is being wasted and generate recommendations for building managers to reduce their overall energy use and shift their electrical load to off-peak times. The use of AI and building automation can lead to myriad benefits, from reduced energy consumption and costs to increased security and comfort. A McKinsey 2018 report finds that building automation systems alone can lower emissions by approximately 3 percent if most commercial buildings adopt them, and by an additional 3 percent if most homes adopt them. 43 The DOE Pacific Northwest National Laboratory PNNL in 2017 considered a broader set of smart energy efficiency measures, finding that integrating smart sensors and controls throughout the commercial building stock has the potential to save as much as 29 percent of building energy consumption through high-perance sequencing of operations, optimizing settings based on occupancy patterns, and detecting and diagnosing inadequate equipment operation and installation problems. 44 Grid-Interactive Efficient Buildings Grid-interactive efficient buildings GEBs use smart technologies and on-site DERs to provide demand flexibility and better integration with the electric grid. GEBs have the ability to dynamically manage their electricity loads to help meet grid needs and minimize electricity system costs, while also co-optimizing DERs such as rooftop solar, battery and thermal energy storage, and combined heat and power with building energy systems. AI can optimize building energy systems to meet occupants comfort and productivity requirements, while also responding to signals from the grid to provide ancillary services e.g., frequency modulation or demand response. By communicating with the grid, AI-enabled smart buildings can engage in automated demand response, which enables adaptive algorithms to keep track of energy prices and automatically run INATION TECHNOLOGY and higher levels of maturity correspond with an ability to achieve desired outcomes more consistently. 90 For example, in these early stages of AI maturity, organization are exploring the technology, whereas more-mature organizations are using AI to trans their operations. Government leaders should think about AI adoption in smart cities in a similar fashion. Right now, most AI in smart cities is in the exploring or experimenting stage, and the goal of city leaders should be to fully integrate AI into their processes. To successfully utilize AI, cities need a strategy defining how they will drive the widespread and rapid adoption of AI and identifying areas to focus attention and resources; data to support specific AI technologies and applications; technology and access to technical infrastructure to train, deliver, and manage AI models across their lifecycle, such as access to TensorFlow, a machine learning library that helps developers better train neural networks; people with the expertise to successfully build and work with AI systems; and governance processes to ensure AI solutions are safe and reliable, and operators of AI systems are held accountable for harms. In the United States, the city of Peachtree Corners in Georgia has invested in Curiosity Lab, a 25,000-square-foot test bed center that provides established companies and start-ups with free access to the resources they need to test and demonstrate new AI technologies, including a 1.5- mile AV test track. 91 The city has also recently partnered with IoT provider IPGallery to build a INATION TECHNOLOGY the office of Cybersecurity, Energy Security, and Energy Resilience CESER; Fossil Energy FE; Energy Efficiency and Renewable Energy EERE; and Nuclear Energy NE. That same year, DOE, the national laboratories, and utility partners again collaborated to develop the Grid Modernization Multi-Year Program Plan MYPP, a multiyear R damage assessment; search and rescue; and hurricanes and tornadoes. 121 So far, AITO has focused on coordinating DOE AI research around disaster mitigation and hazard response, and does not appear to be exploring AI applications in energy systems. 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