Integrated Maximum Power Extraction for Multiple Renewable Energy Sources

To cope with the global demand, renewable energy is gaining more and more popularity owing to its cleaner production and ample supply. The use of renewable energy sources (RESs) for residential and commercial applications is possible both as a stand-alone microgrid system and as a system that is incorporated into the grid. However, due to the intermittent nature of RESs and the need to harvest clean power with the highest possible efficiency, integrating RESs with the grid presents a number of challenges. As a result, maximum power extraction (MPE) has attracted a lot of attention. This task gets more complicated in the case of numerous RESs, especially when the PVs are coupled in a multi-string topology and receive irregular illumination. In this project, we develop integrated MPE control techniques to reduce the implementation cost for the hybrid FC and multi-string PV systems while optimizing the extracted power from all the RESs.

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Intelligent Next Generation Sustainable Energy Systems

The design procedure of compact and efficient on-chip nano-photonics, which are integral parts of energy conversion systems, are accelerated and are aided computationally by inclusion of machine/ deep-learning data-driven approaches. More recently, these methods have gained attention in this domain primarily due to their ability to make the design optimization process faster. These methods mimic the way humans gain certain types of knowledge, have risen to the forefront in many fields of research where there is a significant amount of data to be processed, and make the overall process quicker, more accurate and bias-free. The greater accuracy associated with these methods stems from making a holistic analysis by including all possible variables into the design process. Additionally, while humans tend to lean towards certain outcomes for a particular design problem, a deep-learning routine is virtually free of any such tendencies and thus yields bias-free results. Similarly, machine-learning based regression models have lent their hands in swift design procedures.

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Novel Photovoltaic Technologies for Energy-Sustainable Infrastructure

Sustainable buildings are key aspects of the smart cities of the future; they are realized through the use of windows to generate solar energy. A transparent/organic photovoltaic cell (basic architecture shown in front) can be made from materials that partially allow the passage of visible light and absorb ultraviolet and infrared light. The most exciting feature of transparent solar cells is their integration with windows, skylights, or even smartphone and tablet screens. However, the working efficiency of transparent solar cells varies depending on the materials and manufacturing methods used. Recently, these cells have achieved an efficiency of only around 5%, significantly lower than traditional solar cells (around 20%). ITL is developing novel and efficient transparent photovoltaics using new materials and manufacturing methods. 

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Intelligent Optimization Strategies for Smart Energy Systems

Energy consumption and related challenges are important concerns of the modern technology-driven society. To cope with increasing demand, several technologies like renewable energy, energy mix, logistics, prosumer, grid storage, etc., are integrated using information and communication technologies like IoT, AI, 5G, etc., to form a smart energy ecosystem. Optimizing smart energy (SE) systems for global challenges like environmental change, control, and optimization algorithms rely on system-wide measurements that can provide an accurate model. The sensing component of SE act as the key component for the efficient deployment of smart algorithms tailored for specific functionality like energy system state estimation, demand side management, transmission parameter calculation, home energy management system, fault location, and theft detection, etc. To enable such an operation, a framework-oriented approach is adopted at ITL, where a flexible smart metering framework is being developed to optimize the system-of-systems in integrated energy for the resource-constrained environment.

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Distributed Applications (dApps) Assisted De-Centralized Operations of Energy Markets

The control and optimization of integrated energy components with currently centralized operations may become inefficient, and hence, a distributed control and optimization framework is required. Blockchain provides a robust and efficient platform for decentralized control without a central authority. This has huge potential for applications in the smart energy domain like decentralized storage and control for the grid, peer-to-peer energy trading, EV-based distributed energy storage and trading, decentralized and plug-anywhere charging of EVs and carbon emissions, and green certificate management and trading, which requires a smart meter that can run the related algorithms as a distributed app (DApp). At ITL, we are investigating a novel smart meter architecture that uses a lightweight DApp engine and federated learning to efficiently solve the practical problems arising in a resource-constrained environment, leading to solutions for decentralized and highly-efficient energy markets.

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Perovskite Materials for Energy Harvesting

In the recent era, ABO3 perovskite-type compounds have performed their role in the fields of energy storage and conversion. These halide perovskites, are traditionally employed in a solar-cell design that exhibits superior energy conversion properties. The scientific community is continuously contemplating the perovskite solar cells (PSCs) owing to their cost effectiveness and high performance. The key features attributed to PSCs include light absorption through a broad-spectrum range, direct and tunable bandgap, long charge carrier’s diffusion lengths, and excellent carrier mobilities. Thanks to their remarkable features, the efficiency values upsurged from 3.8% to a decent value of over 25%, beating the maximum efficiency of copper indium gallium selenide (CIGS) and achieving one of the crystalline-silicon solar cells.

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Perovskite Photovoltaics for Self-Powered Smart Windows

Perovskite photovoltaics use a layer of perovskite to absorb light and convert it into electricity. In perovskites, the utilization of photon energy exceeds 70%; therefore, the technology has acquired popularity and is expected to reach the efficiency of CdTe and CIGS-based photovoltaics. Following a rapid development stemming from the industry's interest in these devices, perovskites-based photovoltaics have so far achieved a PCE of 25.8% but are still limited by stability and scalability issues. ITL is exploring perovskites for efficiency enhancement in their optoelectronic properties to develop semitransparent perovskite with switchable transparency for smart windows. An important goal is to search for the alternatives to toxic materials like lead, which can be present in perovskite-based cells, to increase the stability of the perovskite photovoltaics without compromising their performance and cost efficiency.

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Renewable Energy Devices based on Refractory Materials

Conventional solar photovoltaics have their performance limited by Shockley-Queisser (SQ) limit. The broadband metasurfaces-based solar absorbers composed of refractory materials as intermediate structures of a solar thermophotovoltaic (STPV) systems can overcome the SQ limit for efficient solar energy harvesting. One of the major concerns for STPV systems is the underutilization of available solar power, which results in low conversion efficiency. It is due to the broadband nature of solar energy spanning over 220-2500 nm. Moreover, the photons incident on the solar cell possesses either such low energy that they cannot be absorbed by the absorber or such high energy that causes energy loss in the form of heat. Ideally, STPV systems should transfer solar energy above the SQ limit by absorbing the entire solar spectrum but emitting only a narrow part of infrared frequencies to match the low-bandgap solar cells.

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ITL has been developing novel broadband meta-absorbers with narrowband meta-emitters to realize STPV systems for efficient solar energy harvesting. The use of refractory materials with melting temperatures as high as 2000°C, providing chemical/ thermal stability, is also being explored in the novel and efficient design of STPVs. 

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