What Is Renewable Energy Technology?
Broadly speaking, renewable energy technology refers to any method of harvesting power from renewable energy sources, be it wind, solar, hydroelectricity, biomass, geothermal, or any of the various nascent forms of clean energy. These methods have made great strides in recent years, accounting for a sizable slice of electricity production in the US and abroad, and are predicted to continue to rise as the energy sector strives to achieve sustainability goals.
Some of the biggest advances in the transition to renewable energy are being made in the area of real-time data and predictive analytics. Artificial intelligence (AI), edge computing, and IoT technologies are converging into modern digital management systems, making it possible for renewables to operate at maximum capability and increasing their competitiveness in the open market. By introducing intelligence into the equipment used to produce and distribute clean energy, the full potential of renewables can be unlocked.
The Internet of Things is largely to thank for these recent strides. IoT devices can capture and transfer energy conversion, storage, and delivery data and then analyze it in near-real time. Being able to predict energy usage patterns accurately is a game-changer for renewables, leading to a greater number of renewable energy sources being incorporated into the energy mix.
From forecasting production to balancing energy flow, IoT technologies and edge analytics are making an impact.
Forecasting Renewable Energy Production
Solar and wind energy generation is inherently variable and intermittent, depending on changing weather conditions and time of day. Turbines are at the mercy of the whims of the wind, while solar thermal and photovoltaics can be affected by colder temperatures and rainy days. Fluctuations in the availability of resources not only impact operational efficiency but also the reliability of the distribution systems that tap into renewables for their energy supply.
AI-enabled prediction systems are helping to address these issues by accurately forecasting how much renewable power will be produced at any given time. For example, a solution currently available for wind farms combines deep learning, machine learning, edge computing, and data from IoT sensors to predict power generation and improve peak regulation capabilities. This helps producers optimize output and allows for the optimal amount of energy to be integrated into the grid.
Reducing Curtailment
Curtailment occurs when more renewable energy sources are available than the grid can safely accommodate, forcing producers to halt production temporarily. Smart management systems, enabled by AI, edge, and IoT technologies, provide insights into the flow of energy, helping to balance supply and demand and eliminating waste from underutilized resources. This ensures the efficient delivery of renewable energy as it travels from capture sites onto distribution infrastructure, maximizing clean energy throughput.
Increasing Smart Grid Integration
A renewable energy grid is conceptually different from a traditional monolithic grid designed around large power stations. It is modular, distributed, and bidirectional, allowing consumers to become producers themselves and feed excess electricity back into the grid—what’s known as distributed energy resources (DERs).
This helps with conserving energy; however, with so many variables and moving parts, it also tends to make the grid less stable and reliable. Grid modernization technology with automation capabilities and near-real-time analytics makes it possible for utility companies to effectively manage highly distributed and inherently variable renewable energy sources. By bringing compute to the “edge” of the grid, or closer to where the data is generated, these resources can be load balanced in real time so that a higher percentage can be used.
Benefits of Renewable Energy Technology
Built using AI, edge, and IoT technologies, renewable energy solutions can help energy providers increase output while lowering costs.
Expanded Sustainable Footprint
By adding more renewables to the energy mix, companies reduce their emissions, helping them to achieve sustainability goals. This allows for compliance with federal and state clean energy mandates and may entitle them to subsidies and government incentives.
Operational Efficiency
Smart energy technologies help producers forecast output and energy demand, integrate more renewables into their energy mix, and keep their generation equipment and renewable energy storage systems operating optimally. Smart grids with substation automation help to integrate more clean energy into the grid.
Stability and Reliability
Predictive analytics deliver insights on load variation and supply/demand balance. This helps keep distribution channels stable by regulating key variables like voltage and frequency.
Improved Customer Experience
Renewable-ready infrastructure provides new ways for customers to collaborate with their electricity providers in conserving electricity. In places such as California and Germany, energy generated behind the meter—such as from a solar rooftop panel—can be fed into the grid in exchange for feed-in tariff (FIT) payments or credit toward electric bills.
Challenges of Renewable Energy Technology
Building intelligent, data-driven systems that can accommodate renewable energy sources can be expensive and complex to implement.
Up-Front Costs
Transformation requires an extensive infrastructure overhaul for energy plants and utilities alike. The initial CapEx investment can be significant, and the ROI time horizon can be long. These expenditures are gradually offset by the ability to run equipment at optimal efficiency, exceed uptime benchmarks, and leverage cost-effective alternative energies to meet demand.
Complexity
Intelligent management systems and the powerful data they provide are a major step toward sustainability and energy independence. They are also immensely complex, and adopting them requires heavy reliance on industry-specific system integrators and OEMs to piece together a custom approach. Having a unified platform as a foundation helps to ensure interoperability and limit complexity.
Renewable Energy Technology Use Cases
Digitized infrastructure improves operations at multiple junctures in the clean energy supply chain as renewables flow from production sites to end users.
Transmission
Renewables are often generated offshore—and at gusty energy farms in remote locations—and then carried along high-voltage transmission lines to electricity consumers. IoT devices, including drones and fault sensors, are ideal for monitoring far-off generation equipment, power lines, and transmission substations. Rugged edge devices help monitoring systems survive in harsh conditions.
Renewable Energy Storage
Smart batteries are critical infrastructure pieces, assisting with load balancing, supply and demand balance, and safe integration of renewable resources. Installed along transmission lines, they use AI to calculate energy flow depending on the moment-to-moment needs of the grid. When natural resources are plentiful—for instance, on a bright and sunny day—the batteries store power; then, they can slowly discharge their load when fewer resources are available to keep the grid stable.
Grid Management
Smart grid management systems are created by installing IoT sensors and devices in equipment throughout the grid infrastructure. This allows grid data to be collected, processed, and analyzed, with the end goal of optimizing manageability across both legacy and modern systems. The result is a more stable and flexible grid, lower operating costs, and the ability to manage energy capacity more effectively, easing the transition to renewable energy sources.
Substation Automation
Substations are the building blocks of any energy grid, responsible for regulating voltage and the flow of electricity. As demand for renewable energy rises and power generation becomes more distributed, automating the edge of the grid becomes imperative. Substation automation allows energy from diverse producers and DERs to be absorbed.
Microgrids
Powered by IoT technologies, these small-scale, local energy systems can disconnect from the traditional utility grid and operate independently, linking back in when more resources are needed. In many cases, they are capable of generating their own renewable energy. Without any large infrastructure to maintain or repair, microgrids are effectively hardened against storms and natural disasters, making them highly suitable for hospitals and military facilities that require a backup power supply.
The Future of Renewable Energy Technology
Moving forward, an effective renewable energy management strategy could be more vital than ever. Looking at some of the technologies on the horizon, renewable energy production is poised to increase by leaps and bounds over the next decade. Ruggedized deep-water wind deployments aim to double offshore wind capacity in the coming years. Research is underway on innovative vanadium flow batteries that could potentially store vast amounts of renewable megawatt hours. Progress is being made on advanced drilling techniques that plumb geothermal reservoirs deep in the Earth’s crust.
As renewables become more cost-effective and widely available, grid modernization will be necessary to integrate them effectively and attain peak profitability. AI, edge computing, and IoT technologies help energy producers and providers transition from their existing infrastructure to a more flexible, secure, and intelligent model that can meet the demands of a sustainable future.