Solar Energy

So you want to build a solar or wind farm? Here’s how to decide where

Published

2 months ago

December 8, 2024

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So you want to build a solar or wind farm? Here’s how to decide where

by David L. Chandler | MIT News

Boston MA (SPX) Dec 08, 2024

Deciding where to build new solar or wind installations is often left up to individual developers or utilities, with limited overall coordination. But a new study shows that regional-level planning using fine-grained weather data, information about energy use, and energy system modeling can make a big difference in the design of such renewable power installations. This also leads to more efficient and economically viable operations.

The findings show the benefits of coordinating the siting of solar farms, wind farms, and storage systems, taking into account local and temporal variations in wind, sunlight, and energy demand to maximize the utilization of renewable resources. This approach can reduce the need for sizable investments in storage, and thus the total system cost, while maximizing availability of clean power when it’s needed, the researchers found.

The study, appearing in the journal Cell Reports Sustainability, was co-authored by Liying Qiu and Rahman Khorramfar, postdocs in MIT’s Department of Civil and Environmental Engineering, and professors Saurabh Amin and Michael Howland.

Qiu, the lead author, says that with the team’s new approach, “we can harness the resource complementarity, which means that renewable resources of different types, such as wind and solar, or different locations can compensate for each other in time and space. This potential for spatial complementarity to improve system design has not been emphasized and quantified in existing large-scale planning.”

Such complementarity will become ever more important as variable renewable energy sources account for a greater proportion of power entering the grid, she says. By coordinating the peaks and valleys of production and demand more smoothly, she says, “we are actually trying to use the natural variability itself to address the variability.”

Typically, in planning large-scale renewable energy installations, Qiu says, “some work on a country level, for example saying that 30 percent of energy should be wind and 20 percent solar. That’s very general.” For this study, the team looked at both weather data and energy system planning modeling on a scale of less than 10-kilometer (about 6-mile) resolution. “It’s a way of determining where should we, exactly, build each renewable energy plant, rather than just saying this city should have this many wind or solar farms,” she explains.

To compile their data and enable high-resolution planning, the researchers relied on a variety of sources that had not previously been integrated. They used high-resolution meteorological data from the National Renewable Energy Laboratory, which is publicly available at 2-kilometer resolution but rarely used in a planning model at such a fine scale. These data were combined with an energy system model they developed to optimize siting at a sub-10-kilometer resolution. To get a sense of how the fine-scale data and model made a difference in different regions, they focused on three U.S. regions – New England, Texas, and California – analyzing up to 138,271 possible siting locations simultaneously for a single region.

By comparing the results of siting based on a typical method vs. their high-resolution approach, the team showed that “resource complementarity really helps us reduce the system cost by aligning renewable power generation with demand,” which should translate directly to real-world decision-making, Qiu says. “If an individual developer wants to build a wind or solar farm and just goes to where there is the most wind or solar resource on average, it may not necessarily guarantee the best fit into a decarbonized energy system.”

That’s because of the complex interactions between production and demand for electricity, as both vary hour by hour, and month by month as seasons change. “What we are trying to do is minimize the difference between the energy supply and demand rather than simply supplying as much renewable energy as possible,” Qiu says. “Sometimes your generation cannot be utilized by the system, while at other times, you don’t have enough to match the demand.”

In New England, for example, the new analysis shows there should be more wind farms in locations where there is a strong wind resource during the night, when solar energy is unavailable. Some locations tend to be windier at night, while others tend to have more wind during the day.

These insights were revealed through the integration of high-resolution weather data and energy system optimization used by the researchers. When planning with lower resolution weather data, which was generated at a 30-kilometer resolution globally and is more commonly used in energy system planning, there was much less complementarity among renewable power plants. Consequently, the total system cost was much higher. The complementarity between wind and solar farms was enhanced by the high-resolution modeling due to improved representation of renewable resource variability.

The researchers say their framework is very flexible and can be easily adapted to any region to account for the local geophysical and other conditions. In Texas, for example, peak winds in the west occur in the morning, while along the south coast they occur in the afternoon, so the two naturally complement each other.

Khorramfar says that this work “highlights the importance of data-driven decision making in energy planning.” The work shows that using such high-resolution data coupled with carefully formulated energy planning model “can drive the system cost down, and ultimately offer more cost-effective pathways for energy transition.”

One thing that was surprising about the findings, says Amin, who is a principal investigator in the MIT Laboratory of Information and Data Systems, is how significant the gains were from analyzing relatively short-term variations in inputs and outputs that take place in a 24-hour period. “The kind of cost-saving potential by trying to harness complementarity within a day was not something that one would have expected before this study,” he says.

In addition, Amin says, it was also surprising how much this kind of modeling could reduce the need for storage as part of these energy systems. “This study shows that there is actually a hidden cost-saving potential in exploiting local patterns in weather, that can result in a monetary reduction in storage cost.”

The system-level analysis and planning suggested by this study, Howland says, “changes how we think about where we site renewable power plants and how we design those renewable plants, so that they maximally serve the energy grid. It has to go beyond just driving down the cost of energy of individual wind or solar farms. And these new insights can only be realized if we continue collaborating across traditional research boundaries, by integrating expertise in fluid dynamics, atmospheric science, and energy engineering.”

Research Report:Decarbonized energy system planning with high-resolution spatial representation of renewables lowers cost

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Solar Energy

Finding better photovoltaic materials faster with AI

Published

21 hours ago

January 24, 2025

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Finding better photovoltaic materials faster with AI

by Robert Schreiber

Berlin, Germany (SPX) Jan 24, 2025

Researchers at the Karlsruhe Institute of Technology (KIT) and the Helmholtz Institute Erlangen-Nurnberg (HI ERN) have developed a novel AI-driven workflow that dramatically accelerates the discovery of high-efficiency materials for perovskite solar cells. By synthesizing and testing just 150 targeted molecules, the team achieved results that would typically require hundreds of thousands of experiments. “The workflow we have developed will open up new ways to quickly and economically discover high-performance materials for a wide range of applications,” said Professor Christoph Brabec of HI ERN. One of the newly identified materials enhanced the efficiency of a reference solar cell by approximately two percentage points, reaching 26.2 percent.

The research began with a database containing the structural formulas of about one million virtual molecules, each potentially synthesizable from commercially available compounds. From this pool, 13,000 molecules were randomly selected. KIT researchers applied advanced quantum mechanical methods to evaluate key properties such as energy levels, polarity, and molecular geometry.

Training AI with Data from 101 Molecules

Out of the 13,000 molecules, the team chose 101 with the most diverse properties for synthesis and testing at HI ERN’s robotic systems. These molecules were used to fabricate identical solar cells, enabling precise comparisons of their efficiency. “The ability to produce comparable samples through our highly automated synthesis platform was crucial to our strategy’s success,” Brabec explained.

The data obtained from these initial experiments were used to train an AI model. This model then identified 48 additional molecules for synthesis, focusing on those predicted to offer high efficiency or exhibit unique, unforeseen properties. “When the machine learning model is uncertain about a prediction, synthesizing and testing the molecule often leads to surprising results,” said Tenure-track Professor Pascal Friederich from KIT’s Institute of Nanotechnology.

The AI-guided workflow enabled the discovery of molecules capable of producing solar cells with above-average efficiencies, surpassing some of the most advanced materials currently in use. “We can’t be sure we’ve found the best molecule among a million, but we are certainly close to the optimum,” Friederich commented.

AI Versus Chemical Intuition

The researchers also gained valuable insights into the AI’s decision-making process. The AI identified chemical groups, such as amines, that are associated with high efficiency but had been overlooked by traditional chemical intuition. This capability underscores the potential of AI to uncover previously unrecognized opportunities in materials science.

The team believes their AI-driven strategy can be adapted for a wide range of applications beyond perovskite solar cells, including the optimization of entire device components. Their findings were achieved in collaboration with scientists from FAU Erlangen-Nurnberg, South Korea’s Ulsan National Institute of Science, and China’s Xiamen University and University of Electronic Science and Technology. The research was published in the journal Science.

Research Report:Inverse design of molecular hole-transporting semiconductors tailored for perovskite solar cells

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Solar Energy

Scale-up fabrication of perovskite quantum dots

Published

21 hours ago

January 24, 2025

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Scale-up fabrication of perovskite quantum dots

by Simon Mansfield

Sydney, Australia (SPX) Jan 24, 2025

Quantum dots, tiny semiconductor nanomaterials known for their color-tunable and highly efficient photoluminescence, have revolutionized display technologies such as liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), and micro light-emitting diodes (Micro-LEDs). In 2023, the Nobel Prize in Chemistry recognized the discovery and development of quantum dots, underscoring their significance in modern technology.

Perovskite quantum dots (PQDs) are a promising class of materials distinguished by their high absorption coefficient, cost-effectiveness, ease of processing, and reduced environmental impact. Their potential for display applications has attracted considerable interest. In 2015, Professor Zhong and his team introduced a groundbreaking method for in-situ fabrication of PQDs within a polymeric matrix. The subsequent establishment of Zhijing Technology (Beijing) Co., Ltd. in 2016 aimed to advance the scale-up production and application of PQDs in display technologies.

After extensive efforts, the company has developed several in-situ fabrication techniques to enable large-scale manufacturing. These methods include in-situ blade coating, spray drying, extrusion, inkjet printing, and lithography. Recently, the team resolved PQD stability challenges, leading to the integration of PQDs in Skyworth’s TV products. Unlike conventional quantum-dot light-emitting diode (QLED) TVs that utilize 630 nm emissive materials, these innovations introduced deep-red emissive PQDs at 650 nm, enhancing eye care capabilities.

In January 2025, the journal Engineering published a research article titled “Spray-Drying Fabrication of Perovskite Quantum-Dot-Embedded Polymer Microspheres for Display Applications.” This study highlighted the successful scale-up fabrication of PQDs, achieving a production capacity of 2000 kilograms annually. The research also demonstrated the use of PQDs in LCD backlight applications, where PQD-based optical films exhibited exceptional stability under challenging conditions. Aging tests showed brightness decay within 10% after 1000 hours at 60 C with 90% relative humidity and under 70 C conditions with 150 W/m2 455 nm blue light irradiation.

Furthermore, researchers showcased PQD-embedded polymer microspheres as efficient color converters in full-color Micro-LED displays with pixel sizes as small as 10 um. The spray-drying fabrication method provides a cost-effective solution for large-scale PQD production. These PQD-embedded polymer microspheres demonstrated remarkable long-term operational stability, making them highly competitive for use in advanced display technologies.

Research Report:Spray-Drying Fabrication of Perovskite Quantum-Dot-Embedded Polymer Microspheres for Display Applications

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Solar Energy

Solar power surpasses coal in EU for first time

Published

2 days ago

January 23, 2025

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Solar power surpasses coal in EU for first time

by AFP Staff Writers

Paris (AFP) Jan 23, 2025

Solar overtook coal in the European Union’s electricity production in 2024, with the share of renewables rising to almost half the bloc’s power sector, according to a report released Thursday.

Gas generation, meanwhile, declined for the fifth year in a row and fossil-fuelled power dipped to a “historic low”, climate think tank Ember said in its European Electricity Review 2025.

“The European Green Deal has delivered a deep and rapid transformation of the EU power sector,” the think tank said.

“Solar remained the EU’s fastest-growing power source in 2024, rising above coal for the first time. Wind power remained the EU’s second-largest power source, above gas and below nuclear.”

Overall, strong growth in solar and wind have boosted the share of renewables to 47 percent, up from 34 percent in 2019.

Fossil fuels have fallen from 39 to 29 percent.

“A surge in wind and solar generation is the main reason for declining fossil generation. Without wind and solar capacity added since 2019, the EU would have imported 92 billion cubic metres more of fossil gas and 55 million tonnes more of hard coal, costing EUR59 billion,” the report said.

According to Ember, these trends are widespread across Europe, with solar power progressing in all EU countries.

More than half have now either eliminated coal, the most polluting fossil fuel, or reduced its share to less than five percent of their energy mix.

“Fossil fuels are losing their grip on EU energy,” said Chris Rosslowe, lead author of the report.

“At the start of the European Green Deal in 2019, few thought the EU’s energy transition would be where it is today: wind and solar are relegating coal to the margins and pushing gas into decline.”

– Battery storage –

But Rosslowe cautioned much work remains.

“We need to accelerate our efforts, particularly in the wind power sector,” he said.

Europe’s electricity system will also need to increase its storage capacity to make the most of renewable energies, which are by definition intermittent, he added.

In 2024, plentiful solar energy helped drive down prices in the middle of the day, sometimes even resulting in “negative or zero price hours” due to an overabundance of supply compared to demand.

“A readily available solution is a battery co-located with a solar plant. This gives solar power producers more control over the prices they receive and helps them avoid selling for low prices in the middle of the day,” the report said.

The think tank suggested consumers could reduce their bills by shifting usage to periods of abundance (smart electrification), while battery operators could earn revenue from buying power when prices are low and selling it back when demand peaks.

Batteries have advanced significantly in recent years, with installed capacity across the EU doubling to 16 GW in 2023, compared with 8 GW in 2022, according to Ember.

But this capacity is concentrated in just a small number of countries: 70 percent of existing batteries were located in Germany and Italy at the end of 2023.

“More storage and demand flexibility is needed to sustain growth and for consumers to reap the full benefits of abundant solar,” Ember said.

“After a challenging few years for the wind power sector, additions are set to grow, but not by enough to hit EU targets. Closing this gap will require continued policy implementation and political support, such that the rate of additions between now and 2030 is more than double that of recent years.”

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