How AI Can Reduce Energy Costs

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    Contents

    Guide Author

    James Longley

    Managing Director

    min read
    Last Updated May 13, 2024

    How AI Can Reduce Energy Costs for Businesses & Consumers

    Rising energy costs are stretching budgets for both businesses and consumers. This places a significant financial and environmental burden on us all.

    Fortunately, Artificial Intelligence (AI) is emerging as a powerful tool in this fight.

    AI optimisation techniques can reduce energy consumption, allowing both businesses and domestic consumers to cut down on energy bills.

    In this article, we will dive into various AI optimisation strategies, from smart home technologies to the future impact AI has on renewable energy sources.

    By harnessing the power of artificial intelligence, we can reduce energy consumption, lower energy costs, and promote sustainability one business and household at a time.

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    Using AI to Reduce Energy Costs for Businesses

    The average energy consumption for small UK businesses is between 15,000 and 25,000 kWh per year, with larger enterprises reaching 55,000 kWh and more.

    Studies show that hospitals and manufacturing plants account for around 30% of the UK’s commercial energy waste. This equates to roughly £33.9 billion of wasted resources annually.

    For businesses to align with the UK Government’s Net Zero Strategy – and benefit from energy cost reduction – they can leverage AI for business energy optimisation in several ways:

    Smart Building & Facility Management

    AI-powered systems transform traditional solutions into smart answers. Industrial AI gathers real-time data on businesses’ energy consumption patterns. These can be integrated with various Internet of Things (IoT) devices, such as smart meters and thermostats to optimise lighting, heating, cooling and ventilation.

    The advantage of smart building technology is that it provides personalised energy insights. AI highlights peak energy consumption periods and pinpoints areas of energy wastage and inefficiencies. By leveraging this automation, companies can control their energy usage and install sustainable energy management systems for maximum efficiency.

    Example: Octopus Energy, the UK’s largest investor in solar generation, uses AI data-based platforms to balance loads around the grid.

    Personalised Energy Management

    As mentioned, smart building technology analyses a business’s energy demand and distribution. It provides customised recommendations for energy savings. AI algorithms read historical energy data, weather patterns, and other factors to predict future consumption.

    Businesses using AI can adjust their operations – translating to lower energy costs and reduced carbon emissions.

    For instance, EMMA AI is a cloud-based energy management platform that monitors your energy consumption. It’s used to pinpoint areas where energy is wasted and offers advice on how to fix it. Its innovative machine-learning technology analyses half-hour meter readings and uses this information – coupled with advanced algorithms – to process your energy consumption data in real time.

    The Future of AI-Powered Energy Optimisation

    AI advancements for energy savings are impacting the future of energy management practices across multiple sectors. It has the potential to drastically reduce greenhouse gas emissions by fostering eco-savvy habits.

    These advancements include:

    • Next-generation AI algorithms: Advanced AI algorithms can analyse large data sets and provide better predictions and recommendations for energy optimisation.
    • Quantum computing for energy management: Quantum computing is a technology that can perform complex calculations much faster than traditional computers. Its superior capabilities strengthen environmental applications, such as weather readings and climate comparisons. These valuable insights are used in our fight against climate change and energy management.Three evolving areas: AI, quantum computing, and sustainable facilities could alter the way we design and manage metropolitan environments.

      These technologies hold the potential to boost data collection and analysis, improve building design and management, and optimise resource use – potentially leading to the creation of more sustainable cities and societies.

    • Renewable energy optimisation: Researchers can integrate renewable energy sources, like solar and wind power, with AI-powered systems. AI algorithms analyse weather forecasts, power generation data, and consumption patterns to optimise energy distribution and predict potential disruptions.
      Renewable energy sources enhance sustainable energy production and reduce our reliance on fossil fuels.
    • Blockchain for sustainable energy: Blockchain technology tracks and verifies energy transactions through the supply chain. It encourages renewable energy generation and consumption by improving green energy efficiency. This reduces energy wastage and fosters a more sustainable future.
    • Collaborative energy sharing: This involves sharing energy resources, such as solar panels or batteries between multiple parties. AI algorithms can then control energy usage and ensure that energy is distributed efficiently and fairly.
    • Future energy policies: In Spring 2023, the UK Government published a policy paper titled “A Pro-Innovation Approach To AI Regulation.” It’s part of the UK’s commitment to roll out AI-driven solutions across the country. The paper focuses on how AI is to be deployed, rather than targeting specific technologies. This framework will be developed over the next 12 months.

    Reducing energy waste is the driving force behind AI’s transformative potential. However, this can only be achieved by the collaborative effort between businesses and consumers.

    Conclusion

    Unlocking the full potential of artificial intelligence for energy optimisation requires collaborative efforts. Businesses, consumers, and policymakers must work together to create an environment that fosters innovation and facilitates responsible AI development.

    This collaborative action paves the way for a future where AI empowers us to achieve long-term energy sustainability, cost savings, and reduced energy waste.

    If you need more information, chat with Utility Bidder today.

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