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H Energy's 'SolarOnCare' Uses AI to Minimize Quasi-Centralized Dispatch Prediction Errors

Building Unique Technological Strength Based on Three Domestic Patents Including 'Generation Forecasting System'
Minimizing Generation Errors Through Commercialization of AI Weather Analysis and Precise I-V Curve Diagnostics

H Energy's 'SolarOnCare' Uses AI to Minimize Quasi-Centralized Dispatch Prediction Errors Remote operation and management platform dashboard for solar power plants 'SolarOnCare' by H Energy ?H Energy

With the implementation of the quasi-centralized dispatch power generation system scheduled for the Honam region in March next year, renewable energy operators are actively preparing their responses. Against this backdrop, renewable energy platform company H Energy (CEO Ham Ilhan) is seeking to secure a leading position in the market by leveraging its proprietary patented technology.


On December 15, H Energy announced that it has established a sophisticated control system through its remote operation and management platform for solar power plants, 'SolarOnCare,' which can maximize the profitability of power producers under the quasi-centralized dispatch system.


The quasi-centralized dispatch power generation system, first introduced in Jeju, is a scheme in which power producers must comply with government dispatch instructions to stabilize the grid. The smaller the gap between the pre-submitted forecasted generation and the actual generation, the higher the settlement payment. Conversely, a larger error or a low compliance rate with dispatch instructions results in penalties. As a result, the ability to accurately forecast generation and respond precisely to dispatch instructions has emerged as a key factor determining the actual profitability of operators.


H Energy has advanced SolarOnCare based on six registered patents and ten domestic and international patent applications. In particular, three core patents form the foundation of its technological competitiveness: ▲ Solar power generation forecasting system and method (No. 10-2734320), ▲ Dynamic selection method and system for solar generation prediction models (No. 10-2748532), and ▲ I-V curve-based anomaly detection system and method for solar modules (No. 10-2827506).


The core of SolarOnCare is its artificial intelligence (AI)-based precision analysis of meteorological data. It groups data by similar conditions and matches the optimal prediction model in real time. Notably, by analyzing the I-V (current-voltage) curve, it can remotely and precisely diagnose panel anomalies, enabling early detection of variables and minimizing prediction errors.


By automating the traditionally labor-intensive maintenance system, SolarOnCare reduces operational costs while earning recognition for achieving a high level of 'generation prediction accuracy,' which is essential for participants in the quasi-centralized dispatch market.

Industry experts predict that as the distributed energy market accelerates, field-proven data and AI-based remote operation platforms like SolarOnCare will become indispensable revenue management infrastructure for renewable energy operators, far surpassing the role of simple management tools.


Ham Ilhan, CEO of H Energy, stated, "At this point, it is crucial to identify who contributes to the power grid and generates profit, going beyond merely producing electricity. The ability to consolidate scattered small-scale data resources nationwide into a single, flexible power resource will determine the competitiveness of Korea's electricity market going forward."


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