未来城市的人工智能：能源

AI for Future Cities 02: EnergyIssue 02 AI for Future Cities Energy ArupMay 2025 AI for Future Cities Series The rapid evolution of artificial intelligence (AI) promises to enhanceefficiency, speed and innovation. But what does this mean for cities:for how they are planned, designed, built and managed? What arethe opportunities and what are the risks? Amongst the hype andspeculation, how do we ensure that these technologies support us inachieving our shared goal of creating cities that are better for peopleand the planet? Compiled by Arup’s Foresight team,AI for Future Cities is a seriesof critical reflections and expert insights on the uses and impacts ofartificial intelligence across all aspects of our cities– from planningthrough to running them, from infrastructure through to the flows ofresources. Rather than an in-depth and comprehensive report, the issuesare designed to be read as expertise-led explorations and provocations.It will give you a rich understanding of how AI already operates in theurban context today, what trends are shaping its use tomorrow, andinformed speculation on the long-term possibilities. Explore other issueshere. AI for Future Cities 02: Energy Contents This second issue in the series focuses onenergy: How is AI changingthe way that energy is consumed and produced in our cities? Howmight new, AI-enabled energy systems change the physical fabricof our cities and the lived experience of their residents? What newcompetencies may future designers require for creating and workingwith energy systems that have been augmented by AI? And how do weensure that AI remains a tool we use intelligently? Meeting our energy challenges with AIForeword We face huge sustainability andresilience challenges alongsidethe ever-pressing need to deliverinfrastructure and prosperity atpace for communities around theworld. It’s difficult to imaginehow we can meet these demandssuccessfully without the power ofAI to enhance human innovation,creativity, and productivity. learning to reduce energy consumption in buildings atscale. Our work on the UK’s Virtual Energy SystemProgramme and datasharing infrastructure is layingthe foundations to implement AI into our grids and, inso doing, helping to incorporate renewable energy andthe large amounts of storage they require to balancethe grid. In transport, AI enables the vast quantities ofbatteries in our electric vehicles and bus fleets to beused as back-up energy storage for our urban energysystems, while supporting better transport demandmanagement, passenger flows and transport networkoperation and maintenance. Nearly three years have passed since the explosionof excitement around AI, sparked by the emergenceof ChatGPT. Since then, surging investment hastriggered a proliferation of different AI models thatcan improve how we work and what we deliver. Applying AI to the real world is theopportunityThis series by Arup University’s Foresight team explicitly focuses on applications of AI thathave tangible, real-world benefits in acceleratingdecarbonisation and supporting climate resilience.This issue focuses on urban energy, a topic at the cruxof two trends shaping our future world, electrificationand urbanisation. AI can play a significant role in newap-proaches to energy generation and distributionin cities, and we are already using it to plan, site,and operate energy infrastructure. We’ve workedon feasibility studies that prepare the UK’s gridfor the integration of AI, and we’ve used machine Foresight Perspective:How can AI help us manage the rapidly changing shape ofthe grid and the needs of the city? AI is already transforming urban energyAI is emerging as the thread connecting these Now, this is changing with the energy transition to netzero well underway in some areas of the world, andjust beginning in others. Modern cities are unimaginable without electricity.Abundant and affordable energy has enabled usto build upwards and outwards. Electric lifts haveshaped our skylines; electrified mass transit systemsallow millions (if not billions) of people to livemiles away from where they work and play, andabundant lighting has enhanced urban nightlife andsafety. new energy assets and needs at multiple scales,transforming energy into a flexible, dynamic layerof the urban fabric rather than rigid infrastructure.At the national scale, AI can help to plan where bestto install energy generation and forecast with greateraccuracy how much electricity can be produced onany given day, helping to balance the grid overall.At the urban scale, AI turns cities and residentsinto active nodes in the electricity grid rather thandestinations. The management of fluctuations throughdistributed, dynamic storage and generation in homesand workplaces is made manageable with AI: it helpsto integrate buildings’ BESS (battery energy storagesystems) and EV (electrical vehicle) batteries into thegrid, control rooftop solar panels, optimise heatingand cooling networks. Tec