The Various Applications of IoT and Analytics in Renewable Energy

Introduction

Ever since the late 2000s, the thrust to push for a sustainable future has been higher in most countries. Climate change, depleting fossil fuel reserves, the impact of the COVID-19 pandemic, and wars on global energy dynamics have been instrumental in creating awareness in the general population about clean energy alternatives and the need to have a sustainable energy ecosystem.

The discussions surrounding renewable energy have gained renewed focus, and studies estimate that the global renewable energy market will be worth over $2.1 trillion by 2025.

The harnessing of renewable energy is not a new concept. From wind turbines to nuclear power stations, we have seen a fair share of progress even in the early 80s. The goal is to take renewable energy into the limelight as the major power contributor globally in today’s economic and geographical context. This can happen only through digital transformation.

The focus is on leveraging digital innovations to distribute and manage renewable energy systems and drive efficiencies across the entire value chain. Two of the most prominent technologies that can drive this journey forward are the Internet of Things (IoT) and Analytics.

Let us explore the top practical use cases for IoT and Analytics in the renewable energy sector:

Sensor-Driven Load Management

The first step to optimizing any kind of energy production and distribution is to ensure failproof measurement and tracking of the same. This is where IoT-enabled sensors coupled with data analytics come into play.

Today, sensors can be deployed across various production and distribution points of renewable energy to get real-time visibility into different energy parameters. The sensors could range from simple pressure and temperature monitoring sensors to complex ones that deal with detection motion or proximity, acoustic signals, or even light.

The data captured by sensors is then processed with data analytics to get insights that help in the load management of grids connected to the renewable energy generation source. For example, a solar farm that generates renewable energy may produce less power on a cloudy or rainy day.

Sensors pick up the data on production as well as from environmental monitoring, and this data is processed to find out how much alternate power must be made available through other sources to keep the grid online. This is how real value is derived from an IoT initiative powered by data analytics.

Lower Capital Expenditure

Renewable energy sources like wind farms, solar farms, tidal parks, etc., require massive capital investments to set up a base location that can eventually supply power from natural sources. However, there should be a clear understanding of weather patterns and geographical and demographic trends in the region to go ahead with investing initiatives.

With IoT and analytics, it becomes easier to simulate and test possible operational conditions in different locations to create power output models that can be checked for maximum electricity generation potential. This helps companies plan and execute projects at locations that are more viable and offer faster time to realization for power parameters.

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