Integrating cities into the whole energy system


A specialist energy consultancy


Dr Colin Birchenall explores how to unlock the untapped potential of data to address the growing crisis of energy consumption in cities.


Cities are a geographic concentration of a “network of networks” consisting of transportation systems, built environment, gas and electrical supply, water supply, information and communications, telecommunications, industry, retail, commerce, and communities of people.


As a consequence these vast urban settlements are major sources of energy consumption, accounting for 75% of global primary energy consumption.With urban living expected to grow from 50% to 70% of the world’s population by 2050, finding innovative ways to rebalance energy consumption in cities is imperative. However, change is already afoot. New approaches are emerging to offset energy demand in real-time in the guise of demand-side response technology.


Also, renewable energy sources and district heating systems are being implemented so cities can actively harness, produce and distribute energy rather passively consume energy. The need to reduce the energy consumption of cities alongside the move towards whole-system approaches comes at a time of unprecedented digital innovation and explosion in data. Digital devices, with a diverse set of form factors, are becoming increasingly connected. And through the “Internet of Things”, digital is more and more embedded within everyday objects from smart thermostats to smart meters. What is clear, is that our physical and digital worlds are converging, creating new demands on engineers and requiring us to engineer cross-sectorial solutions.


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One of the major barriers to the whole-system approach is gaining access to data. Even before you reach the challenges of information security and the acquisition, storage, processing, analysis and visualisation of data, you need to know that data exists that is of value to you. Unfortunately data will have been created to support a specific process within an individual product or service. The creator of the data will regard themselves as the “data owner” and will not have necessarily recognised the value of the data to other potential stakeholders. Consequently, data isn’t advertised or promoted, and remains hidden within individual organisations as well as the networks of organisations spanning a city. Research by Forrester Group suggests that companies use just 12% of the data that is available to them. Meanwhile, a study from MIT indicated that companies, such as Apple, Netflix, Google and Amazon, with a culture of data-driven decision-making, are 4% more productive and have 6% higher profits than companies without this culture. However, if and when relevant datasets are identified for an engineering solution, the next challenge is to acquire the data. Unfortunately for most organisations, data is closed by default, and protected - quite rightly - for privacy or commercial reasons. But while organisations should adhere to the Data Protection Act, this should not be mis-used to prevent the opening and sharing of data that is not personally or commercially sensitive.


If the data represents a characteristic of the city that can be observed in the real-world, it is an asset of the city and should belong to everybody in the city. If it is about an individual, it should be an asset of the individual, and should belong to the individual. Indeed, a voluntary programme from UK government and industry, Midata, will, over time, give consumers increasing access to their personal data in a portable, electronic format.


Opening and sharing non-sensitive data across organisations can be empowering. It provides a wider range of stakeholders with new insight that can improve the quality of, and even automate, decision- making across different sectors.


These decisions range from everyday life “consumer” decisions through to operational decisions, planning decisions, and policy decisions, and enable a better understanding of the dependencies between cross-sectorial decisions that have consequences for the city overall. Historically, these decisions would historically have been left to subjective judgement; or worse, by chance. However, to turn multiple datasets into insight that can inform


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