PredAIoT: Improving Economic Decision-Making for Energy Assets Using Open Data to Enhance Market Efficiency and Support Oman Vision 2040 PredAIoT provides an innovative AI-based solution that transforms open data in Oman’s energy sector into real-time economic decisions. The goal is to maximize operational efficiency and reduce financial losses. In 2024, total government support for Oman’s electricity sector reached 602.3 million Omani rials, highlighting the Economic Decision Gap, which results in large, often hidden, financial losses. Our technology focuses on closing the gap between the engineering performance of energy assets and their actual economic performance, helping operators unlock “identified funds” and reducing pressure on the national public budget.

Types of Open Data Used PredAIoT primarily relies on data published by the Ministry of Energy and Minerals and the Public Services Regulatory Authority (APSR), including:

Total electricity complaints received from electricity customers: These data provide insights into operational weaknesses and service quality, enabling PredAIoT to identify areas that need improvement in maintenance and operations to reduce outages and related processing costs. Electricity service connection requests: This helps understand demand growth and its geographic distribution, supporting better grid planning and load distribution. Total connected electricity bills for electricity sector customers: These data provide indicators of consumption and consumption patterns, helping to forecast demand and improve energy management. Meter readings for electricity customers: These enable analysis of the real performance of assets and detection of deviations from expected performance, allowing PredAIoT to deliver optimal economic interventions. Total capacity of renewable energy power plants: This provides critical information about renewable assets, helping PredAIoT operate them and integrate them into the grid with economic efficiency. In addition, PredAIoT can benefit from any other relevant energy and minerals data published by the Ministry of Energy and Minerals, such as generation, consumption, or fuel prices, to enhance the accuracy of its economic models.

Added Value of PredAIoT By analyzing these open datasets, PredAIoT does the following:

Identifies economic loss: Calculates real-time financial losses caused by asset degradation or suboptimal operational decisions. Improves predictive maintenance: Applies the Economic Optimization of Maintenance methodology, where a maintenance decision is made only when the accumulated economic loss exceeds the cost of intervention—ensuring that every maintenance action is a profitable decision. Maximizes return on investment (ROI): Converts engineering efficiency into tangible financial gains. Our analyses show that energy assets can achieve 862,903 Omani rials in additional annual revenue per 500 MW asset (e.g., a Battery Energy Storage System (BESS)) without any new capital expenditure on equipment, representing a profitability increase ranging from 9.1% to 15%. Conclusion PredAIoT is a clear example of how open data can be transformed into tangible economic and strategic value. It supports the goals of Oman Vision 2040 by driving digital transformation and improving the efficiency of vital sectors.

(Additional Use Case / Economic Blindness) PredAIoT also presents an innovative solution that addresses the “Economic Blindness” challenge in managing energy assets and industry. It does so by leveraging open data available through Oman’s Open Data Portal, alongside asset operational data. This use case demonstrates how AI and machine learning can convert raw data into improved economic decisions, leading to the recovery of “lost funds” and enhanced operational efficiency.

The problem being addressed Even though assets often have high engineering efficiency (such as power generation plants), operational decisions (e.g., when to run, shut down, store, or curtail production) are frequently made based on fixed schedules or inaccurate estimations of the immediate economic value. This results in significant economic losses that are often invisible. We call these losses economic blindness. These losses worsen in Oman’s energy market, where prices fluctuate and demand is growing rapidly, as reflected in reports from the APSR and the Ministry of Energy and Minerals.

How PredAIoT uses open data Our methodology integrates and analyzes key data sets from official open sources, including:

Oman electricity market data: such as the System Marginal Price (SMP) and scarcity prices, published in annual reports (e.g., the average SMP for 2024 was 9.120 Omani rials/MWh, and the average scarcity price was 4.022 Omani rials). Electricity demand data: to identify consumption patterns and peak forecasts. Weather data: to forecast renewable generation and its impact on the grid. Innovative solution and methodology PredAIoT develops an Economic Decision Intelligence layer that works on top of existing control systems (SCADA). This layer:

Continuously calculates economic loss: It estimates the real-time loss of value (e.g., revenue losses or additional operating costs) caused by any degradation in asset performance. It is computed based on the difference between expected vs. actual performance while considering spot market prices from open data. Economic optimization for predictive maintenance: It compares accumulated economic loss with the cost of maintenance. Maintenance orders are issued only when accumulated economic loss reaches (or exceeds) the intervention cost. This ensures each maintenance action is economically profitable. Converts data into “unlocked funds”: Helps operators increase revenues by 9% to 15% and improve operational efficiency by up to 30% (based on analytics and the IEA discussions on demand flexibility), without the need for new capital investments in equipment. In 2024, total government support for Oman’s electricity sector amounted to 602.3 million Omani rials, highlighting the Economic Decision Gap that leads to significant financial losses. Our technology focuses on closing the gap between the engineering performance of assets and the actual economic performance, contributing to the recovery of “unlocked funds” for operators and reducing the burden on the state’s public budget.

Added value for Oman and Vision 2040 Enhancing economic efficiency: Helping close the energy-sector support gap by improving asset management and maximizing the economic value of every unit of energy. Supporting the energy transition: Enabling higher integration of renewable energy through better grid flexibility and efficient demand management. Local innovation: Showcasing Omani capabilities in building advanced technology solutions that leverage open data to support sustainable economic development. Transparency and data-driven decision-making: Providing data-driven insights to asset operators and policymakers, improving transparency and efficiency in the sector. Conclusion (Final) PredAIoT is a real example of how open data can become a driver of economic growth and innovation, supporting the goals of Oman Vision 2040 in building a diversified, sustainable economy based on innovation.

Sources Public Services Regulatory Authority (APSR) — Economic cost and collected revenues from electricity customers and financial statistics on government support to the electricity sector (million Omani rials). Public Services Regulatory Authority (APSR) — Total capacity of renewable energy power plants (technical data on solar/wind power plants, including capacity and technology). Ministry of Energy and Minerals — Electricity and renewable energy data (statistical data on electricity generation and renewable energy sources in the Sultanate of Oman). Public Services Regulatory Authority (APSR) — Total electricity complaints received from electricity customers (statistics on customer complaints that provide insights into operational weaknesses). Public Services Regulatory Authority (APSR) — Electricity service connection requests (statistics that show connection-response efficiency). Public Services Regulatory Authority (APSR) — Total connected electricity bills for electricity sector customers (statistics reflecting billing operation efficiency). Public Services Regulatory Authority (APSR) — Meter readings for electricity customers (statistics on meter readings accuracy).