Solar energy is at the forefront of the present-day renewable energy space, making use of the widely abundant and freely available energy of the sun. Globally, solar energy companies have experienced an ever-increasing growth rate. This has resulted in large-scale solar plants with numerous physical assets distributed in remote and wide-spread areas. With such a scale of operation, come challenges of maintaining performance and profitability while preserving a competitive edge. Advancement in equipment engineering, efficient production techniques and superior energy storage approaches can no longer be the only answers to these challenges. The next phase of innovation will be powered by remote monitoring technologies coupled with data analytics. Optimizing ROI in the solar space will be a balancing act between increasing performance, reducing costs, maintaining productivity while sustaining profits and achieving economies of scale. The Internet of Things (IOT) provides a technological platform to achieve this and will prove to be a significant differentiator in this race-to-the-top by providing access to previously untapped avenues to increasing productivity and maximizing ROI.
Key challenges faced by the stakeholders
Some of the key challenges faced by the solar industry come in the form of expensive modules, low efficiency, unreliable generation and high maintenance costs. Following section discusses these issues in brief:
Efficiency: The power output of a solar plant is highly dependent on the efficiency of the solar cells. Most of the commercial solar cells today have an efficiency of around 20%. This is further hampered due to environmental factors such as module soiling, module shading, etc.
Unreliability: Solar power generation is subject to availability of sun’s energy and thus remains an unreliable source. Due to intermittent weather conditions, insufficient generation may result in unfulfilled demand.
Costs: Periodic maintenance and replacement of equipment add up a significant cost for O&M teams in a solar plant. Contemporary approaches to maintenance result in unplanned and often ineffective maintenance schedules, largely affecting the productivity of the workforce. Also, downtime due to equipment failure results in loss of generation and revenue.
These challenges can be effectively addressed by Internet of Things solution, which enables continuous remote monitoring and asset management. A comprehensive IoT infrastructure provides multifaceted benefits leading to improvements in productivity and profitability of the plant. The following lists the categorical benefits of adopting IoT for O&M: Asset Management:
– Tracking and analysis of sensor data will help monitor physical health of the plant and devices in real-time. A centralized system will provide information on plantlevel performance as well as performance of individual devices such as PV modules, strings, combiner boxes, inverters, transformers, etc.
– Analysis of historical device data will provide insights into plant and device performance bottlenecks. For eg: simple algorithms can be used to estimate losses such shading loss, soiling loss, transmission loss, etc at an aggregated level (plant) as well as at a disaggregated level (device). Addressing these performance issues in a timely manner will result in an overall increase in equipment reliability and efficiency.
– Predictive analytics will enable proactive detection of malfunctions, degradations and failures in devices such as PV modules, Inverters and Transformers. This will lower plant downtime and generation loss due to device failures.
– Data analytics will lead to preventive maintenance activities which will lower equipment failures and repair/replacement costs. Especially for capital-incentive assets, this will greatly fuel profitability and productivity.
– Following preventive maintenance, effective maintenance schedules can be drafted that will eliminate random maintenances, reduce total maintenance costs and improve workforce efficiency.
– Accurate and planned maintenance schedules will benefit inventory forecasting. Timely purchase and inventory maintenance of equipment and spare parts will lower unnecessary delays in case of device malfunctions.
– An IOT application will provide a onestop access to complete energy portfolio containing key KPIs on macro and micro levels across all plants.
– Latest technologies such as Smart Meters can precisely measure and report power consumption. Data from these meters will help provide accurate demand forecasts and optimize energy distribution across portfolio.
– Advancement of Smart Grid technologies has been a boon to renewable energy. Smart Grids optimize energy consumption, ensure reliable supply of energy and provide secure energy distribution. Integration of IOT platform with Smart Grid technologies will make energy management efficient and economical at the same time.
– IOT software solutions such as Machine Learning, Artificial Intelligence, etc. have the ability to accurately predict real-time generation and also give future generation forecasts based on historical plant data. This will greatly benefit power buyers and traders by giving them fairly accurate generation estimates and more control over demand management.
What is IoT?
The Internet of Things (IoT) is the network of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. [Wiki] Specifically for the energy sector, IOT provides an integrated platform that ceaselessly transmits and stores huge volumes of device data, performs simple and complex analysis and provides real-time, quantified insights to end-users.
The development and adoption of IOT in recent years has been driven by three key factors:
Smart Sensors: Smart Sensors are hardware attached to equipment that detect physical environment conditions, process and convert them into signal form. They have inbuilt microcontroller and wireless transmission capabilities, providing automated data collection, pre-processing and transmission.
Big Data and Cloud Computing: Big Data infrastructure provides a framework for fast, real-time simple and complex event processing required to perform advanced analytics on sensor data. A Big Data platform is harnessed by Cloud Computing technology that allows storage of vast amounts of data in a decentralized location, guaranteeing easy data access, data security and reduced storage costs.
Machine Learning and Artificial Intelligence: Machine Learning and Artificial Intelligence software facilitate information discovery and insights generation providing analytical solutions in the form of Energy Forecasting, Predictive Maintenance, Operations Intelligence, etc. which are key to enhancing the efficiency and profitability of energy plants.
The IoT Value Chain
The IOT infrastructure is made up of a plethora of devices and technologies. Each component of the framework requires niche knowledge of module selection and implementation. The following are the 4 key elements in a typical IOT setup:
Hardware typically consists of sensors and actuators which act as the primary point of contact between the equipment and the IOT platform. They continuously detect and capture information about the characteristics such as current, voltage, temperature, light, moisture, etc. of individual devices. The sensor data thus captured (and occasionally preprocessed) is passed on to the Middleware.
Middleware: Middleware is part of the IOT architecture enabling connectivity between sensors and the Cloud/Application layer. It consists of both hardware and software components that interact electrically or logically with sensors. They preprocess and convert raw sensor data into usable form for further analysis. The data thus processed is sent to Cloud via communication modules which are either wired or wireless. Typical examples of such modules are WiFi (wireless LAN based communications) or WAN (wide area network i.e. cellular).
Cloud: Cloud is a central and critical component of any IOT solution. Here data coming in from different devices or Middleware is aggregated and stored in a database. The key feature of Cloud is its ability to scale quickly and handle signals from billions of connected devices. Data on the Cloud is typically product-agnostic and used for generating various real time and historical analytics solutions.
Application: The application layer is basically a User-Interface in the form of a web application, a stand-alone software or a mobile app. The main goal of the application is to act on the data from the Cloud and provide information to customers in welldefined formats such as tables, graphs and reports. It gives a centralized interface to monitor the health and the performance of IOT-enabled devices. The Internet of Things (IOT) is a timely solution to the challenges faced by the solar industry. It provides an ideal platform for continuous remote monitoring, irrespective of the scale, of solar plants. Early IOT adoption will greatly benefit companies by allowing them to monitor and optimize performance of resources located in broadly distributed and remote areas and significantly boost their performance and profitability.