#wind sector

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Improving operating margins in the wind sector with monitoring consolidation – Intertrust Technologies

The wind industry is facing a crossroads due to supply and technology issues along with rising interest rates. Discover how some energy comp

The wind sector has always had a challenging business model. Wind energy projects depend on high initial investments with fluctuating production and price levels. To mitigate financial risk, wind project developers secure fixed revenues through power purchasing agreements (PPAs). 

As new recruits are being trained, operators and technicians from other sites can fill in without having to learn an entirely new system. With greater worker availability, energy companies can avoid overuse of overtime and reduce human capital costs.

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The power of AI to transform renewable energy operations – Intertrust Technologies

Today’s energy companies are faced with the complex task of operating and maintaining multiple plants with a diverse portfolio of renewable

The short answer is yes, with the right infrastructure, machine learning, and informed, real-time response. The long answer is more complicated. Until recently, ai energy sites were islanded, operating in a vacuum. The rollout of AI and diversified portfolio management has made this status quo untenable. Coordinating and optimizing sites that run on separate but interdependent systems come with significant difficulties in operations, monitoring, management and compliance.

The short answer is yes, with the right infrastructure, machine learning, and informed, real-time response. The long answer is more complicated. Until recently, ai energy sites were islanded, operating in a vacuum. The rollout of AI and diversified portfolio management has made this status quo untenable. Coordinating and optimizing sites that run on separate but interdependent systems come with significant difficulties in operations, monitoring, management and compliance.

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Why data governance matters

With regulations like GDPR and the CCPA creating considerable rules on data usage, we look at the details and why data governance matters.

Setting data governance policies, roles and responsibilities and instituting processes that ensure data is managed effectively reduces the risk of non–compliance with regulatory and industry standards

Streamlining processes for the sake of regulatory compliance also helps organizations to reduce the cost of non-compliance while increasing operational efficiency and preventing data mismanagement

The framework includes 5 key risk management areas: identify, protect, detect, respond, and recover. Each stage is examined and guidance is provided so organizations can establish the processes, resources, and tools to minimize cybersecurity risks.

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How to ensure secure data processing

The value and scale of data usage is being held back by security and regulatory concerns. Learn how secure data processing can help.

Data virtualization is the core technology that allows for fully compliant and secure data processing across expansive, spread out networks. A virtual representation of data is combined and processed securely according to the existing business rules. This creates an interoperable layer where analytics can be conducted on custom datasets, regardless of where the data is stored, eliminating the need for slow and costly data transfers.

The virtual environment allows secure data processing on sensitive data stored anywhere. When data is combined for querying, all operations take place in secure containers to minimize the chances of security breaches or data leakage.

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The evolution of Web3 tokenization and asset rights management

Discover how Web3 platforms and business models are evolving, especially in how digital and real-world assets are handled through advanced t

Companies and creators can now create and issue their own tokens as a means of fundraising, incentivizing users’ engagement, and providing value to the entire ecosystem. New business models and revenue streams are emerging through the tokenization of assets such as real estate, art, and intellectual property. Purchasing possibilities such as fractional ownership, are allowing more people to invest in high-value assets.

The value of digital products is often determined by the rights that users have to modify, reuse, alter, or monetize them. These rights can range from extensive to limited. For example, where users have broader rights to modify and reuse assets, they are more likely to become an engaged and loyal customer base. On the other hand, restricting usage rights may increase the perceived value of assets and create a more exclusive user base.

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5 common data aggregation mistakes and how to fix them | Intertrust

Data aggregation is a useful tool for data operations. Here’s five common data aggregation mistakes and how to solve them.

 A commonly known example of data aggregation is the Consumer Price Index (CPI) from the Department of Labor which aggregates price changes in a wide variety of goods and services to track the fluctuation of the cost of living in the U.S. Unfortunately, despite the importance of data aggregation and its potential to improve decision-making, organizations still make major data aggregation mistakes. 

To extract data from multiple sources and curate datasets that deliver useful, actionable information to downstream users is a key role of data operations. This includes summary insight derived from the aggregation of multiple data points. However, gathering the required data for querying may be difficult or require lengthy ETL processes, leading to incomplete datasets.

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Best practices for data lifecycle management – Intertrust Technologies

Data lifecycle management ensures your data function works as expected and meets its obligations for all data held by your organization.

Data lifecycle management is a critical process for data operations, as it ensures that data processing, analysis, and sharing are all streamlined. The flow of data is considered and data friction points are reduced to increase data value and ROI. An effective data lifecycle management process can identify and smooth obstacles as soon as they appear. 

Additionally, data lifecycle management is important for delivering on several key functions and responsibilities of your DataOps team, including regulatory compliance and data interoperability. 

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Improving operating margins in the wind sector with monitoring consolidation

Traditional operations in the wind sector often involve multiple, isolated control rooms, each dedicated to a specific site. Different farms use turbines, sensors, and control room software from dozens of vendors. The lack of a unified operational view inhibits operators from optimizing performance and impedes the deployment of innovations in predictive maintenance and AI.

The result is pervasive inefficiency, a death knell in an industry where maximizing uptime and efficiency is essential for profitability. 

With most maintenance occurring during daytime, wind farms require less engaged monitoring during evening hours. By consolidating the monitoring of multiple sites to a single centralized control room during off-hour periods.

wind turbine companies can reduce their staffing. With VOX, night-time operators at remote control rooms share a common operating picture, enabling a seamless handover and limiting operational expenses.