Energy Management: Renewable Energy Integration

Intelligent platform to optimize the use of renewable energies within industrial operations

The energy transition needs more than panels or turbines: it needs intelligence

More and more companies seek to integrate renewable energies to reduce operating costs, improve sustainability, and comply with environmental standards.

However, adopting renewable energy brings new challenges:

• Variability in generation
• Coordination with internal demand
• Balance between traditional and renewable sources
• Storage and availability
• Lack of visibility of energy flow

Intelligent Energy Management, based on IoT, Industry 4.0, and AI, allows you to understand and optimize that flow continuously and precisely.

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Total visibility of energy flow

The platform consolidates information from different sources within the facility:

• Renewable generation (solar, wind, micro-hydro, or other existing sources)
• Consumption by area or process
• Hourly variations of energy production
• Load of critical equipment
• Storage or batteries (if they exist)
• General plant demand

Everything is visualized in real-time from a cloud panel.

The goal is to see how each kWh enters and how it is used to make better operational decisions.

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IoT data for better integration

Information generated by monitoring systems installed in the plant —meters, internal records, connected equipment, or any existing source— feeds the platform.

With this data, the solution can:

• Show real renewable energy coverage
• Analyze the renewable vs. traditional proportion
• Identify areas with higher demand
• Measure internal energy efficiency
• Correlate consumption with renewable production

Regardless of the data source, the value is in the intelligence applied on top of the energy flow.

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AI to balance, optimize, and anticipate

An artificial intelligence module analyzes generation and consumption patterns to:

🌤️ Predict renewable energy availability

Based on trends, climate (if integrated), schedules, and historical behavior.

⚡ Recommend the best time to use renewable energy

To reduce costs or stabilize loads.

🔋 Optimize battery or storage use (if it exists)

Decide when to charge or discharge for greater efficiency.

📉 Identify excesses or shortages in real-time

Alerting about peaks that require operational adjustment.

📊 Calculate the renewable "utilization index"

To know how much of the renewable energy produced is actually used.

This approach allows achieving greater energy stability and operational efficiency.

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Key indicators

The platform offers essential KPIs to supervise renewable energy management:

• Percentage of renewable energy used
• Available vs. consumed generation
• Consumption by area, shift, or process
• Critical demand
• Renewable generation projection
• Consumption curve compared with solar/wind curve
• Overall system efficiency
• Estimated energy cost per hour

These indicators help plan, save, and stabilize operations.

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Operational benefits

✅ Greater utilization of renewable energy generated

✅ Reduction of operating costs

✅ Less dependence on traditional sources

✅ Identification of energy waste

✅ More efficient AI-based planning

✅ Harmonized integration between renewable energy and demand

✅ Less variability in operations

✅ Clear information for strategic decisions

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Practical example

A factory with solar panels experiences significant variations in production during certain times of the day.

The AI detects that during the afternoon there is renewable surplus, but much of it is wasted due to lack of consumption.

The platform recommends:

"Move certain flexible processes to the 1:00 PM–4:00 PM time slot to take advantage of solar generation."

The result: more than 20% of that additional energy is integrated into the production process, reducing costs and improving overall efficiency.

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Flexible for any level of energy maturity

The platform adapts both to companies that already have installed renewable energies and to those in the initial stage.

The focus is to analyze, optimize, and plan, not install physical infrastructure.

Depending on the plant configuration, fully cloud or hybrid schemes with local modules can be evaluated.

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Part of the 2025 Roadmap

Intelligent renewable energy integration is part of Nissi Energy's 2025 Roadmap.

Currently developing modules for:

• Advanced energy analytics
• Generation projection
• Operational recommendation with AI
• Energy balance analysis
• Real-time visualization
• Flexible connectivity with existing energy systems

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🟩 Note for companies interested in AI innovation

We are looking for companies that already have renewable energies or are evaluating their adoption and want to participate as early partners in developing these capabilities.

If your organization wants to:

• Optimize its renewable energy use
• Improve energy stability
• Reduce costs
• Test AI tools for energy management

We can establish an early implementation agreement, with exclusive benefits for the first partners.

Contact us to coordinate an exploratory meeting.

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Conclusion

Integrating renewable energy is not just about generating electricity: it's about knowing when, how, and where to use it to get the maximum benefit.

A platform based on IoT, AI, and advanced analytics allows you to fully leverage renewable energy, reduce costs, and build more stable and sustainable operations.

This solution is designed to accompany companies on their path to the energy efficiency of the future.