Investment in solar energy projects has increased in recent years and so has the use of advanced solutions for optimizing solar operations and maintenance like Digital Twin, edge computing, and IoT. We are decoding the concept of Digital Twin in this article and explain to you how Digital Twin technology is helping to transform the way solar plants function and operate.

With the use of advanced IoT solutions and smart sensors, now we can get solar panel-level data insights on any kind of solar plant. Detailed analysis of this data is used to design advanced solutions like Digital Twin. Effective use of Digital Twin can help solar asset managers detect early patterns of system underperformance, which later can be used to predict potential faults and quantify the impact of existing/upcoming faults or losses in solar power plants. Thus, Digital Twin techniques help solar developers anticipate solar power plant system’s future production, plan predictive and corrective maintenance activities, and improve the bankability of future projects.

What is Digital Twin in solar?

A Digital Twin is a virtual model of a real system. While changing the input variables, a Digital twin helps to conduct experiments and test hypotheses, as well as to predict the behavior of the solar power plant’s system and to manage its life cycle. A Digital Twin also helps to prevent equipment failures, and poor system design and minimize operating costs. In the specific case of the solar PV industry, a Digital Twin is a digital copy of the solar power plant, including all relevant design and location information, as well as information from the past; including major losses causes, and performance indicators breakdown.

Why do solar Asset Managers need Digital Twin?

Digital Twin is a faster way of comparing, at specific conditions, PV plant’s current performance with its expected performance drawn from its digital copy. After a Digital Twin of a Solar PV Plant is created, the only required inputs, other than real-time plant data, are irradiance and temperature. Therefore, performance and loss analysis becomes faster and easier to perform. More advanced solar PV plant Digital Twins even include a parameters breakdown and trends to indicate root causes of faults or losses in real-time. Thus, making daily tasks easier for solar Asset Managers and increasing the uptime of the solar plants.

How do you make a solar Digital Twin?

A Digital Twin is a virtual instance of a physical system (twin) that is continually updated with the latter’s performance, maintenance, and health status data throughout the PV solar power plant’s life cycle. A Digital Twin looks like, behaves like, and connects to a solar plant system with the goal of improving or optimizing decision-making for any time horizon. It should be localized by considering the geographical position of a solar power plant, locally measured power and weather data, and power loss factors.

An ideal Solar Digital Twin should be self-adaptive, that means, it should be able to modify and recalibrate its behaviour and likeness under changing operating and external conditions, such that it satisfies operational goals and constraints to accommodate possible future operational uncertainties.

How SmartHelio uses Digital Twin?

In general terms, creating a solar Digital Twin is a faster way to detect even the smallest deviations in performance and make sense out of different trends within the historical data. At SmartHelio, we create and localize Digital Twins of solar power plants by adding design factors, geographical factors, and performance factors and trends. Our Digital Twin models automatically prioritize solar power plant maintenance activities to minimize O&M costs and maximize solar plant’s uptime. It’s a blend of advanced technology and continuous learning with a custom-tailored understanding of O&M costs and resources for each solar plant or company. Our Digital Twins do what a Digital Twin is actually supposed to do- directly derive actionable insights from any kind of solar power plant!

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