# AI for Energy: Smart Grid, Generation Forecasting & Predictive Maintenance Training

> Source: https://sukruyusufkaya.com/en/training/enerji-sektoru-icin-akilli-sebeke-uretim-tahminleme-ve-bakim-ai-egitimi
> Updated: 2026-05-19T15:21:18.683Z
> Level: all
> Topics: Akıllı Şebeke, Smart Grid, Üretim Tahminleme, Generation Forecasting, Predictive Maintenance, Yenilenebilir Enerji, Rüzgâr Tahminleme, Güneş Tahminleme, SCADA, AMI Akıllı Sayaç, EPDK Uyum, Dengeleme Piyasası, Kayıp Kaçak Analizi, CBAM Raporlama, Net Sıfır 2053
**TLDR:** Generation forecasting, smart grid, predictive maintenance and EPDK-compliant AI architecture — an end-to-end hands-on program tailored to Türkiye's energy sector.

## Açıklama

A 2-day hands-on training for production, transmission, distribution and industrial-zone teams in Türkiye's energy sector — covering smart grid, wind/solar/hydro generation forecasting and predictive maintenance AI end-to-end, framed by EPDK, KVKK and EU AI Act compliance.

## Kazanımlar

- Ability to design an end-to-end smart grid AI architecture
- Selecting, training and measuring MAPE of generation forecasting models for wind, solar and hydro
- A predictive maintenance pilot roadmap and a sensor-data strategy
- An approach to enrich SCADA + AMI + weather + EPİAŞ data with AI
- Building a compliant architecture under EPDK, KVKK, the EU AI Act and CBAM
- Designing AI-based signal and bid optimization for the Balancing Market, GÖP and GİP

<h2>About This Training</h2>
<p>Türkiye is entering a critical digital transformation period for the energy sector — driven by the Net Zero 2053 target, rapid renewable capacity growth, the maturing balancing market, and EPDK's algorithmic supervision agenda. Generation companies, distribution operators, industrial-zone (OSB) energy units and YEKA investors are turning AI from a "nice to have" into an operational necessity for generation forecasting, predictive maintenance, non-technical loss analytics and balancing market optimization.</p>
<p>This 2-day hands-on training is designed for technical and management teams across both generation (wind, solar, hydro, cogeneration, gas) and distribution sides of the energy sector. It teaches — through applied scenarios — how to enrich smart meter (AMI), SCADA, OT sensor, EPİAŞ market price and weather data streams with AI; which forecasting models best fit Türkiye's climate and grid characteristics; how to build a compliant architecture under KVKK + EPDK + EU AI Act; and how to take an AI pilot to production in 90 days.</p>

<h3>What You Will Learn</h3>
<ul>
<li><strong>Generation forecasting</strong> for wind (RES), solar (GES) and hydro (HES) plants — ARIMA, Prophet, LSTM, Temporal Fusion Transformer</li>
<li><strong>Predictive maintenance</strong> and Remaining Useful Life (RUL) estimation for transformers, turbines, inverters, breakers and switchgear</li>
<li><strong>Non-technical loss</strong> anomaly detection and fault location using AMI and SCADA data</li>
<li><strong>Price forecasting and bid optimization</strong> for the Balancing Market, Day-Ahead (GÖP) and Intra-Day (GİP) markets</li>
<li><strong>AI-supported architecture</strong> for EPDK reporting, CBAM, Türkiye ETS and ESG disclosures</li>
<li><strong>Compliant energy-AI system design</strong> under KVKK and the EU AI Act, with on-prem / hybrid data residency</li>
<li><strong>Enterprise architecture</strong> for joining SCADA + AMI + weather + ERP + EPİAŞ data</li>
<li>A <strong>90-day pilot roadmap</strong> and KPI framework (MAPE, RUL accuracy, loss ratio, balancing penalty)</li>
</ul>

<h3>Sectoral Focus</h3>
<ul>
<li><strong>Generation:</strong> EÜAŞ; renewable IPPs (Enerjisa Generation, Aksa, Akenerji, Zorlu, Bereket, Aydem, Alarko); cogeneration and YEKA tenders</li>
<li><strong>Transmission &amp; Distribution:</strong> TEİAŞ; operators of the 21 distribution regions (BEDAŞ, AYEDAŞ, Enerjisa Distribution, Toroslar, Başkent, GDZ, Vangölü, Çoruh, Fırat, Boğaziçi, etc.)</li>
<li><strong>Trading &amp; Market:</strong> EPİAŞ members, balancing market participants, GÖP/GİP traders, bilateral contract parties</li>
<li><strong>Industrial &amp; OSB:</strong> Cogeneration operators, OSB energy management units, captive-generation industrials (cement, steel, glass, textile)</li>
<li><strong>Renewables &amp; Hydrogen:</strong> Unlicensed producers, rooftop PV, YEKA RES/GES winners, hydrogen-economy investors</li>
</ul>

<h3>Hands-On Labs</h3>
<p>Throughout the training, participants work on real (anonymized) datasets and sectoral scenarios: improving the daily MAPE of a GES generation forecast, customer-level anomaly scoring on AMI data, early warning from turbine vibration data (vibration-based RUL), RAG-based document summarization for EPDK monthly reports, AI-supported architecture for CBAM Scope 1-2 emission calculation, and bid-signal generation to minimize balancing market penalties.</p>

<h3>Why This Training Matters for Türkiye</h3>
<p>EPDK's expected algorithmic supervision framework for 2026, the EU AI Act entering into force for high-risk systems on 2 August 2026, CBAM reporting becoming a trigger for Türkiye's energy-intensive exporters, and the Net Zero 2053 roadmap together make AI investment in energy companies a non-deferrable agenda. This training prepares applicable AI solutions within the real constraints of the Türkiye energy ecosystem — high non-technical losses, rapid post-YEKDEM transition, and the profitability pressure of the balancing market.</p>